Publications

Preprints and Working Papers

[] R. Singhal, K. Ponkshe, R. Vartak, L. R. Varshney, and P. Vepakomma, “Fed-SB: A Silver Bullet for Extreme Communication Efficiency and Performance in (Private) Federated LoRA Fine-Tuning,” arXiv:2502.15436 [cs.LG].

[] D. Alabi and L. R. Varshney, “Inaccessible Entropy for Watermarking Generative Agents,” Cryptology ePrint 2025/256.

[] S. Jha, R. Arora, Y. Watanabe, T. Yanagawa, Y. Chen, J. Clark, B. Bhavya, M. Verma, H. Kumar, H. Kitahara, N. Zheutlin, S. Takano, D. Pathak, F. George, X. Wu, B. O. Turkkan, G. Vanloo, M. Nidd, T. Dai, O. Chatterjee, P. Gupta, S. Samanta, P. Aggarwal, R. Lee, P. Murali, J.-W. Ahn, D. Kar, A. Rahane, C. Fonseca, A. Paradkar, Y. Deng, P. Moogi, P. Mohapatra, N. Abe, C. Narayanaswami, T. Xu, L. R. Varshney, R. Mahindru, A. Sailer, L. Shwartz, D. Sow, N. C. M. Fuller, and R. Puri, “ITBench: Evaluating AI Agents across Diverse Real-World IT Automation Tasks.” arXiv:2502.05352 [cs.AI].

[] L. Huang, L. R. Varshney, and K. E. Willcox, “Formal Verification of Digital Twins with TLA and Information Leakage Control,” arXiv:2411.18798 [cs.CR].

[] D. Chen, A. Youssef, et al., “Transforming the Hybrid Cloud for Emerging AI Workloads,” arXiv:2411.13239 [cs.DC].

[] R. Kaur, S. Zhang, B. Berwal, S. Ray, R. Kumar, and L. R. Varshney, “From Phytochemicals to Recipes: Health Indications and Culinary Uses of Herbs and Spices,” arXiv:2410.17286 [physics.soc-ph].

[] X. Wu, M. Hartman, V. A. Jayaraman, and L. R. Varshney, “SwitchCIT: Switching for Continual Instruction Tuning of Large Language Models,” arXiv:2407.11780 [cs.CL].

[] M. Choraria, N. Sekhar, Y. Wu, X. Zhang, P. Singhal, and L. R. Varshney, “Language Grounded QFormer for Efficient Vision Language Understanding,” arXiv:2311.07449 [cs.CV].

[] R. Baltaji, S. Pujar, L. Mandel, M. Hirzel, L. Buratti, and L. R. Varshney, “Learning Transfers over Several Programming Languages,” arXiv:2310.16937 [cs.CL].

[] A. Bhimaraju, S. R. Etesami, and L. R. Varshney, “Dynamic Batching of Online Arrivals to Leverage Economies of Scale,” arXiv:2309.16911 [cs.DS].

[] E. D. Anderson, L. R. Varshney, B. Hemmatian, P. D. Robles-Granda, A. K. Nayak, R. R. Wilcox, C. E. Zwilling, B. Kim, and A. K. Barbey, “Human Intelligence and the Connectome are Driven by Structural Brain Network Control,” bioRxiv 2023.08.02.551642.

[] R. Kanungo, S. Siva, N. Bleier, M. H. Mubarik, L. R. Varshney, and R. Kumar, “Understanding Interactions Between Chip Architecture and Uncertainties in Semiconductor Supply and Demand,” arXiv:2305.11059 [cs.AR].

[] I. Ferwana, S. Park, T.-Y. Wu, and L. R. Varshney, “Designing Discontinuities,” arXiv:2305.08859 [cs.IT].

[] I. Ferwana and L. R. Varshney, “Optimal Recovery for Causal Inference,” arXiv:2208.06729 [stat.ME].

[] H. Yu, I. Mineyev, L. R. Varshney, and J. A. Evans, “Learning from One and Only One Shot,” arXiv:2201.08815 [cs.CV].

[] L. R. Varshney and R. Socher, “COVID-19 Growth Rate Decreases with Social Capital,” medRxiv 2020.04.23.20077321

[] N. S. Keskar, B. McCann, L. R. Varshney, C. Xiong, and R. Socher, “CTRL: A Conditional Transformer Language Model for Controllable Generation,” arXiv:1909.05858 [cs.CL].

[] L. R. Varshney, N. S. Keskar, and R. Socher, “Pretrained AI Models: Performativity, Mobility, and Change,” arXiv:1909.03290 [cs.CY].

[] T. Nishida, L. R. Varshney, and Y. Ishikawa, “Dynamic Network Signatures of Labor Flows: Evidence from a Large Business Social Network,” submitted.

Long/Selective Computing Conference Papers

[32] X. Wu and L. R. Varshney, “Transformer-based Causal Language Models Perform Clustering,” in Findings of the 2025 Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL), Albuquerque, New Mexico, 29 April – 4 May 2025.

[31] A. Bhimaraju, E. W. Robson, L. R. Varshney, and A. K. Umrawal, “Fractional Budget Allocation for Influence Maximization under General Marketing Strategies,” in Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (CIKM 2024), Boise, Idaho, 21-25 October 2024.

[30] X. Wu and L. R. Varshney, “A Meta-Learning Perspective on Transformers for Causal Language Modeling,” in Findings of the Associational for Computational Linguistics: ACL 2024, Bangkok, Thailand, 11-16 August 2024.

[29] S. Basu, P. Katdare, P. Sattigeri, V. Chenthamarakshan, K. R. Driggs-Campbell, P. Das, and L. R. Varshney, “Efficient Equivariant Transfer Learning from Pretrained Models,” in Proceedings of the Thirty-Seventh Conference on Neural Information Processing Systems (NeurIPS), New Orleans, Louisiana, 10-16 December 2023.

[28] N. Bleier, A. Wezelis, L. R. Varshney, and R. Kumar, “Programmable Olfactory Computing,” in Proceedings of the 50th International Symposium on Computer Architecture (ISCA-50), Orlando, Florida, 17-21 June 2023. (IEEE MICRO Top Pick)

[27] M. Choraria, I. Ferwana, A. Mani, and L. R. Varshney, “Learning Optimal Features via Partial Invariance,” in Proceedings of the 37th AAAI Conference on Artificial Intelligence, Washington, DC, 7-14 February 2023.

[26] S. Basu, P. Sattigeri, K. Natesan Ramamurthy, V. Chenthamarakshan, K. R. Varshney, L. R. Varshney, and P. Das, “Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models,” in Proceedings of the 37th AAAI Conference on Artificial Intelligence, Washington, DC, 7-14 February 2023.

[25] X. Ge, R. T. Goodwin, H. Yu, P. Romero, O. Abdelrahman, A. Sudhalkar, J. Kusuma, R. Cialdella, N. Garg, and L. R. Varshney, “Accelerated Design and Deployment of Low-Carbon Concrete for Data Centers,” in Proceedings of the 5th ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS ’22), Seattle, Washington, 29 June – 1 July 2022.

[24] R. Theisen, H. Wang, L. R. Varshney, C. Xiong, and R. Socher, “Evaluating State-of-the-Art Classification Models Against Bayes Optimality,” in Proceedings of the Thirty-Fifth Conference on Neural Information Processing Systems (NeurIPS), 6-14 December 2021.

[23] G. S. Ramachandran, I. Brugere, L. R. Varshney, and C. Xiong, “GAEA: Graph Augmentation for Equitable Access via Reinforcement Learning,” in Proceedings of the 4th AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES), 19-21 May 2021.

[22] S. Basu, G. S. Ramachandran, N. S. Keskar, and L. R. Varshney, “Mirostat: A Neural Text Decoding Algorithm That Directly Controls Perplexity,” in Proceedings of the 9th International Conference on Learning Representations (ICLR), [Vienna, Austria], 4-8 May 2021.

[21] J. Vig, A. Madani, L. R. Varshney, C. Xiong, R. Socher, and N. F. Rajani, “BERTology Meets Biology: Interpreting Attention in Protein Language Models,” in Proceedings of the 9th International Conference on Learning Representations (ICLR), [Vienna, Austria], 4-8 May 2021.

[20] S. Tan, S. Joty, L. R. Varshney, and M.-Y. Kan, “Mind Your Inflections! Improving NLP for Non-Standard English with Base-Inflection Encoding,” in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020), [Punta Cana, Dominican Republic], 16–20 November 2020.

[19] L. Wang, B. Li, H. Zhou, G. B. Giannakis, L. R. Varshney, and Z. Zhao, “Adversarial Linear Contextual Bandits with Graph-Structured Side Observations,” in Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), 2-9 February 2021.

[18] H. H. Lee, K. Shu, P. Achananuparp, P. K. Prasetyo, Y. Liu, E.-P. Lim, and L. R. Varshney, “RecipeGPT: Generative Pre-training Based Cooking Recipe Generation and Evaluation System,” in Proceedings of the Web Conference (WWW), Taipei, Taiwan, 20-24 April 2020.

[17] H. Zhou, L. Wang, L. R. Varshney, and E.-P. Lim, “A Near-Optimal Change-Detection Based Algorithm for Piecewise-Stationary Combinatorial Semi-Bandits,” in Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), New York, New York, 7-12 February 2020.

[16] I. Chien, H. Zhou, and P. Li, “HS²: Active Learning over Hypergraphs,” in Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019), Okinawa, Japan, 16-18 April 2019.

[15] D. Somaya and L. R. Varshney, “Embodiment, Anthropomorphism, and Intellectual Property Rights for AI Creations,” in Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society, New Orleans, Louisiana, 2-3 February 2018.

[14] H. Yu, T. Li, and L. R. Varshney, “Probabilistic Rule Realization and Selection,” in Proceedings of the Thirtieth Annual Conference on Neural Information Processing Systems (NIPS), Long Beach, California, 4-9 December 2017.

[13] H. Yu and L. R. Varshney, “Towards Deep Interpretability (MUS-ROVER II): Learning Hierarchical Representations of Tonal Music,” in Proceedings of the 5th International Conference on Learning Representations (ICLR), Toulon, France, 24-26 April 2017. 

[12] A. Chatterjee, M. Borokhovich, L. R. Varshney, and S. Vishwanath, “Efficient and Flexible Crowdsourcing of Specialized Tasks with Precedence Constraints,” in Proceedings of the 2016 IEEE Conference on Computer Communications (INFOCOM), San Francisco, California, 10-15 April 2016.

[11] A. Chatterjee, L. R. Varshney, and S. Vishwanath, “Work Capacity of Freelance Markets: Fundamental Limits and Decentralized Schemes,” in Proceedings of the 2015 IEEE Conference on Computer Communications (INFOCOM), Hong Kong, 26 April – 1 May, 2015.

[10] F. Pinel and L. R. Varshney, “Computational Creativity for Culinary Recipes,” in Proceedings of the ACM CHI Conference on Human Factors in Computing Systems, Toronto, Canada, 26 April – 1 May 2014.

[9] L. R. Varshney and K. C. Ratakonda, “An Information-Theoretic View of Cloud Workloads,” in Proceedings of the IEEE International Conference on Cloud Engineering (IC2E 2014), Boston, Massachusetts, 10-14 March 2014.

[8] A. Karbasi, A. H. Salavati, A. Shokrollahi, and L. R. Varshney, “Noise-Enhanced Associative Memories,” in Proceedings of the Twenty-Seventh Annual Conference on Neural Information Processing Systems (NIPS), Lake Tahoe, Nevada, 5-8 December 2013. (Spotlight, 2013 Best Student Paper Award of the IEEE Data Storage Technical Committee)

[7] S. Mehta, R. Pimplikar, A. Singh, L. R. Varshney, and K. Visweswariah, “Efficient Multifaceted Screening of Job Applicants,” in Proceedings of the 16th International Conference on Extending Database Technology (EDBT), Genoa, Italy, 18-22 March 2013.

[6] G. V. Ranade and L. R. Varshney, “To Crowdsource or not to Crowdsource?,” in Proceedings of the 4th Human Computation Workshop (HCOMP), Toronto, Canada, 23 July 2012.

[5] L. R. Varshney, “Toward a Comparative Cognitive History: Archimedes and D. H. J. Polymath,” in Proceedings of Collective Intelligence 2012, Cambridge, Massachusetts, 18-20 March 2012.

[4] A. K. Fletcher, S. Rangan, L. R. Varshney, and A. Bhargava, “Neural Reconstruction with Approximate Message Passing (NeuRAMP),” in Proceedings of the Twenty-Fifth Annual Conference on Neural Information Processing Systems (NIPS), Granada, Spain, 13-15 December 2011.

[3] D. V. Oppenheim, L. R. Varshney, and Y.-M. Chee, “Work as a Service,” in Proceedings of the Ninth International Conference on Service Oriented Computing (ICSOC), Paphos, Cyprus, 5-8 December 2011.

[2] L. R. Varshney and D. V. Oppenheim, “On Cross-Enterprise Collaboration,” in Proceedings of the 9th International Conference on Business Process Management (BPM), Clermont-Ferrand, France, 28 August – 2 September 2011. (Invited)

[1] L. R. Varshney and D. V. Oppenheim, “Coordinating Global Service Delivery in the Presence of Uncertainty,” in Proceedings of the 12th International Research Symposium on Service Excellence in Management (QUIS12), Ithaca, New York, 2-5 June 2011.

Journal Papers and Magazine Articles

[113] B. K. Das, L. R. Varshney, and V. Madhok, “Simultaneous Information and Energy Transmission through Quantum Channels,” Physical Review A, vol. 111, no. 1, 012609, Jan. 2025.

[112] S. M. Azimi-Abarghouyi and L. R. Varshney, “Compute-Update Federated Learning: A Lattice Coding Approach,” IEEE Transactions on Signal Processing, vol. 72, pp. 5213-5227, 2024.

[111] R. Baltaji, S. Basu, and L. R. Varshney, “Efficient Model-Agnostic Multi-Group Equivariant Networks,” Transactions on Machine Learning Research, to appear.

[110] A. K. Nayak, E. Chitambar, and L. R. Varshney, “Reliable Quantum Memories with Unreliable Components,” Physical Review A, vol. 110, no. 3, 032423, Sept. 2024.

[109] N. Bleier, A. Wezelis, L. R. Varshney, and R. Kumar, “Programmable Olfactory Computing,” IEEE MICRO, vol. 44, no. 4, pp. 88-96, Jul.-Aug. 2024. (IEEE MICRO Top Pick)

[108] X. Cheng, T. Mamalis, S. Bose, and L. R. Varshney, “On Carsharing Platforms with Electric Vehicles as Energy Service Providers,” IEEE Transactions on Intelligent Transportation Systems, vol. 25, no. 7, pp. 8158-8170, July 2024.

[107] K.-Y. Huang, G. Upadhyay, Y. Ahn, M. Sakakura, G. J. Pagan-Diaz, Y. Cho, A. C. Weiss, C. Huang, J. W. Mitchell, J. Li, Y. Tan, Y.-H. Deng, A. R. Ellis-Mohr, Z. Dou, X. Zhang, S. Kang, Q. Chen, J. V. Sweedler, S. G. Im, R. Bashir, H. J. Chung, G. Popescu, M. U. Gillette, M. Gazzola, H. Kong, “Neuronal Innervation Regulates the Secretion of Neurotrophic Myokines and Exosomes from Skeletal Muscle,” Proceedings of the National Academy of Sciences USA, vol. 121, no. 19, e2313590121, Apr. 2024.

[106] Z. Fang, Z. Wu, X. Wu, S. Chen, X. Wang, S. Umrao, and A. Dwivedy, “APIPred: An XGBoost-Based Method for Predicting Aptamer-Protein Interactions,” Journal of Chemical Information and Modeling, vol. 64, no. 7, pp. 2290-2301, Apr. 2024.

[105] I. Ferwana and L. R. Varshney, “The Impact of COVID-19 Lockdowns on Mental Health Patient Populations in the United States,” Scientific Reports, vol. 14, 5689, 2024.

[104] N. Bosch, A. S. Chan, J. L. Davis, R. Gutierrez, J. He, K. Karahalios, S. Koyejo, M. C. Loui, R. Mendenhall, M. R. Sanfilippo, H. Tong, L. R. Varshney, and Y. Wang, “Artificial Intelligence, Social Responsibility, and the Roles of the University,” Communications of the ACM, vol. 67, no. 8, pp. 22-25, Aug. 2024.

[103] X. Zhang, Z. Dou, S. H. Kim, G. Upadhyay, D. Havert, S. Kang, K. Kazemi, K.-Y. Huang, O. Aydin, R. Huang, S. Rahman, A. Ellis-Mohr, H. A. Noblet, K. H. Lim, H. J. Chung, H. J. Gritton, M. T. A. Saif, H. J. Kong, J. M. Beggs, and M. Gazzola, “Mind In Vitro Platforms: Versatile, Scalable, Robust, and Open Solutions to Interfacing with Living Neurons,” Advanced Science, vol. 11, no. 11, 2306826, Mar. 2024.

[102] B. Hemmatian, L. R. Varshney, F. Pi, and A. K. Barbey, “The Utilitarian Brain: Moving Beyond the Free Energy Principle,” Cortex, vol. 170, pp. 69-79, Jan. 2024.

[101] A. Bhimaraju, A. Chatterjee, and L. R. Varshney, “Dynamic Resource Allocation to Minimize Concave Costs of Shortfalls,” IEEE Control Systems Letters, vol. 7, pp. 3633-3638, 2023.

[100] Uthirakalyani G., A. K. Nayak, A. Chatterjee, and L. R. Varshney, “Limits of Fault-Tolerance on Resource-Constrained Quantum Circuits for Classical Problems,” Physical Review A, vol. 108, no. 5, 052425, Nov. 2023.

[99] T. Bergquist, T. Schaffter, Y. Yan, T. Yu, J. Prosser, J. Gao, G. Chen, L. Charzewski, Z. Nawalany, I. Brugere, R. Retkute, A. Prusokas, A. Prusokas, Y. Choi, S. Lee, J. Choe, I. Lee, S. Kim, J. Kang, S. D. Mooney, J. Guinney, and Patient Mortality Prediction DREAM Challenge Consortium, “Evaluation of Crowdsourced Mortality Prediction Models as a Framework for Assessing Artificial Intelligence in Medicine,” Journal of the American Medical Informatics Association, vol. 31, no. 1, pp. 35-44, Jan. 2024.

[98] Uthirakalyani G., A. K. Nayak, and A. Chatterjee, “A Converse for Fault-tolerant Quantum Computation,” Quantum, vol. 7, 1087, Aug. 2023.

[97] D. B. Karakoc, M. Konar, M. J. Puma, and L. R. Varshney, “Structural Chokepoints Determine the Resilience of Agri-Food Supply Chains in the United States,” Nature Food, vol. 4, no. 7, pp. 607–615, July 2023.

[96] H. Yu, J. A. Evans, and L. R. Varshney, “Information Lattice Learning,” Journal of Artificial Intelligence Research, vol. 77, pp. 971–1019, July 2023.

[95] H. Yu, I. Mineyev, and L. R. Varshney, “A Group-Theoretic Approach to Computational Abstraction: Symmetry-Driven Hierarchical Clustering,” Journal of Machine Learning Research, vol. 24, no. 47, pp. 1–61, 2023.

[94] S. Basu and L. R. Varshney, “Universal and Succinct Source Coding of Deep Neural Networks,” IEEE Journal on Selected Areas in Information Theory, vol. 3, no. 4, pp. 732–745, Dec. 2022.

[93] S. Basu, D. Seo, and L. R. Varshney, “Hypergraph-based Source Codes for Function Computation Under Maximal Distortion,” IEEE Journal on Selected Areas in Information Theory, vol. 3, no. 4, pp. 824–838, Dec. 2022.

[92] P. Rana and L. R. Varshney, “Exploring Limits to Tree-Planting as a Natural Climate Solution,” Journal of Cleaner Production, vol. 384, ar. 135566, Jan. 2023. 

[91] H. Zhou, J. Chen, L. R. Varshney, and A. Jagmohan, “Nonstationary Reinforcement Learning with Linear Function Approximation,” Transactions on Machine Learning Research, Oct. 2022.

[90] Y. Kim, J. Shin, Y. Cassuto, and L. R. Varshney, “Distributed Boosting Classification over Noisy Communication Channels,” IEEE Journal on Selected Areas in Communications, vol. 41, no. 1, pp. 141–154, Jan. 2023.

[89] M. R. O’Shaughnessy, D. S. Schiff, L. R. Varshney, C. J. Rozell, and M. A. Davenport, “What Governs Attitudes toward Artificial Intelligence Adoption and Governance?,” Science and Public Policy, vol. 50, no. 2, pp. 161–176, April 2023.

[88] H. Yu, L. R. Varshney, H. Taube, and J. A. Evans, “(Re)discovering Laws of Music Theory using Information Lattice Learning,” IEEE BITS Information Theory Magazine, vol. 2, no. 1, pp. 58–75, Oct. 2022.

[87] S. Basu, J. Gallego-Posada, F. Viganò, J. Rowbottom, and T. Cohen, “Equivariant Mesh Attention Networks,” Transactions on Machine Learning Research, Aug. 2022.

[86] R. Smith, L. R. Varshney, S. Nagayama, M. Kazama, T. Kitagawa, S. Managi, and Y. Ishikawa, “A Computational Neuroscience Perspective on Subjective Wellbeing within the Active Inference Framework,” International Journal of Wellbeing, vol. 12, no. 4, pp. 102–131, Oct. 2022.

[85] A. Naik, L. R. Varshney, W. Hassaneen, and P. M. Arnold, “Development of Machine Learning–Based Models to Predict Treatment Response to Spinal Cord Stimulation,” Neurosurgery, vol. 91, no. 1, e30, July 2022.

[84] D. Yang, A. D. Smith, E. Smith, A. Naik, M. Janbahan, C. Thompson, L. R. Varshney, and W. Hassaneen, “The State of Machine Learning in Outcomes Prediction of Transsphenoidal Surgery: A Systematic Review,” Journal of Neurological Surgery Part B: Skull Base, vol. 84, no. 6, pp. 548-559, Dec. 2023.

[83] J. Kern, E. Dupraz, A. Aïssa-El-Bey, L. R. Varshney, and F. Leduc-Primeau, “Optimizing the Energy Efficiency of Unreliable Memories for Quantized Kalman Filtering,” Sensors, vol. 22, no. 3, 853, 2022.

[82] P. Das and L. R. Varshney, “Explaining AI Generation and Creativity,” IEEE Signal Processing Magazine, vol. 39, no. 4, pp. 85–95, July 2022.

[81] I. Ferwana and L. R. Varshney, “Social Capital Dimensions are Differentially Associated with COVID-19 Vaccinations, Masks, and Physical Distancing,” PLoS ONE, vol. 16, no. 12, e0260818, Dec. 2021.

[80] N. M. Lee, L. R. Varshney, H. C. Michelson, P. Goldsmith, and A. Davis, “Digital Trust Substitution Technologies to Support Smallholder Livelihoods in Sub-Saharan Africa,” Global Food Security, vol. 32, 100604, Mar. 2022.

[79] A. Bhimaraju, A. Chatterjee, and L. R. Varshney, “Expected Extinction Times of Epidemics with State-Dependent Infectiousness,” IEEE Transactions on Network Science and Engineering, vol. 9, no. 3, pp. 1104–1116, May-June 2022.

[78] L. R. Varshney and A. K. Barbey, “Beyond IQ: The Importance of Metacognition for the Promotion of Global Wellbeing,” Journal of Intelligence, vol. 9, no. 4, 54, Nov. 2021.

[77] D. Seo, R. K. Raman, and L. R. Varshney, “Decision Making in Star Networks with Incorrect Beliefs,” IEEE Transactions on Signal Processing, vol. 69, pp. 6221–6236, 2021.

[76] L. Marla, L. R. Varshney, D. Shah, N. A. Prakash, and M. E. Gale, “Short and Wide Network Paths,” IEEE Transactions on Network Science and Engineering, vol. 9, no. 2, pp. 524–537, Mar.-Apr. 2022.

[75] A. Kafizov, A. Elzanaty, L. R. Varshney, and M.-S. Alouini, “Wireless Network Coding with Intelligent Reflecting Surfaces,” IEEE Communications Letters, vol. 25, no. 10, pp. 3427–3431, Oct. 2021.

[74] B. Clerckx, K. Huang, L. R. Varshney, S. Ulukus, and M.-S. Alouini, “Wireless Power Transfer for Future Networks: Signal Processing, Machine Learning, Computing, and Sensing,” IEEE Journal of Selected Topics in Signal Processing, vol. 5, no. 5, pp. 1060–1094, Aug. 2021.

[73] Y. Yan, T. Schaffter, T. Bergquist, T. Yu, J. Prosser, Z. Aydin, A. Jabeer, I. Brugere, J. Gao, G. Chen, J. Causey, Y. Yao, K. Bryson, D. R. Long, J. G. Jarvik, C. I. Lee, A. Wilcox, J. Guinney, S. Mooney, and the DREAM Challenge Consortium, “A Continuously Benchmarked and Crowdsourced Challenge for Rapid Development and Evaluation of Models to Predict COVID-19 Diagnosis and Hospitalization,” JAMA Network Open, vol. 4, no. 10, e2124946, Oct. 2021.

[72] R. K. Raman and L. R. Varshney, “Coding for Scalable Blockchains via Dynamic Distributed Storage,” IEEE/ACM Transactions on Networking, vol. 29, no. 6, pp. 2588–2601, Dec. 2021.

[71] A. Mani, L. R. Varshney, and A. Pentland, “Quantization Games on Social Networks and Language Evolution,” IEEE Transactions on Signal Processing, vol. 69, pp. 3922–3934, 2021.

[70] H. Yu, I. Mineyev, and L. R. Varshney, “Orbit Computation for Atomically Generated Subgroups of Isometries of Zⁿ,” SIAM Journal on Applied Algebra and Geometry, vol. 5, no. 3, pp. 479–505, Sept. 2021.

[69] D. Seo and L. R. Varshney, “The CEO Problem with rth Power of Difference and Logarithmic Distortions,” IEEE Transactions on Information Theory, vol. 67, no. 6, pp. 3873–3891, Jun. 2021.

[68] R. C. Dean and L. R. Varshney, “Optimal Recovery of Missing Values for Non-negative Matrix Factorization,” IEEE Open Journal of Signal Processing, vol. 2, pp. 207–216, Mar. 2021.

[67] T.-Y. Wu, A. Tandon, L. R. Varshney, and M. Motani, “Skip-Sliding Window Codes,” IEEE Transactions on Communications, vol. 69, no. 5, pp. 2824–2836, May 2021.

[66] P. Rana and L. R. Varshney, “Trustworthy Predictive Algorithms for Complex Forest System Decision Making,” Frontiers in Forests and Global Change, vol. 3, 587178, Jan. 2021.

[65] A. Tandon, V. Y. F. Tan, and L. R. Varshney, “The Bee-Identification Error Exponent with Absentee Bees,” IEEE Transactions on Information Theory, vol. 66, no. 12, pp. 7602–7614, December 2020.

[64] D. Seo, A. Chatterjee, and L. R. Varshney, “On Multiple-Access in Queue-Length Sensitive Systems,” IEEE Open Journal of the Communications Society, vol. 1, pp. 1244–1255, 2020.

[63] L. R. Varshney, “Impact of AI on Employment,” Digital Skills Insights, International Telecommunications Union, pp. 40-47, 2020.

[62] M. A. Donmez, M. Raginsky, A. C. Singer, and L. R. Varshney, “Cost-Performance Tradeoffs in Fusing Unreliable Computational Units,” IEEE Open Journal of Signal Processing, vol. 1, pp. 77–89, 2020.

[61] T.-Y. Wu, A. Tandon, M. Motani, and L. R. Varshney, “Outage-Constrained Rate of Skip-Sliding Window Codes,” IEEE Transactions on Green Communications and Networking, vol. 4, no. 4, pp. 506–514, June 2020.

[60] D. Seo, A. Chaaban, L. R. Varshney, and M.-S. Alouini, “Classes of Full-Duplex Channels With Capacity Achieved Without Adaptation,” IEEE Transactions on Communications, vol. 68, no. 7, pp. 4141–4149, July 2020.

[59] A. Chatterjee and L. R. Varshney, “Energy-Reliability Limits in Nanoscale Feedforward Neural Networks and Formulas,” IEEE Journal on Selected Areas in Information Theory, vol. 1, no. 1, pp. 250–266, May 2020.

[58] D. Somaya and L. R. Varshney, “Ownership Dilemmas in an Age of Creative Machines,” Issues in Science and Technology, vol. 36, no. 2, pp. 79–85, Winter 2020.

[57] A. Tandon, V. Y. F. Tan, and L. R. Varshney, “The Bee-Identification Problem: Bounds on the Error Exponent,” IEEE Transactions on Communications, vol. 67, no. 11, pp. 7405–7416, November 2019.

[56] D. Seo, R. K. Raman, J. B. Rhim, V. K. Goyal, and L. R. Varshney, “Beliefs in Decision-Making Cascades,” IEEE Transactions on Signal Processing, vol. 67, no. 19, pp. 5103–5117, October 2019.

[55] J. Mulrow, N. Kshetry, D. A. Brose, K. Kumar, D. Jain, M. Shah, T. E. Kunetz, and L. R. Varshney, “Prediction of Odor Complaints at a Large Composite Reservoir in a Highly Urbanized Area,” Water Environment Research, vol. 92, no. 3, pp. 418–429, March 2020.

[54] N. C. Sevuktekin, L. R. Varshney, P. K. Hanumolu, and A. C. Singer, “Signal Processing Foundations for Time-based Signal Representations,” IEEE Signal Processing Magazine, vol. 36, no. 6, pp. 38–50, November 2019.

[53] A. Tandon, M. Motani, and L. R. Varshney, “Are RLL Codes Suitable for Simultaneous Energy and Information Transfer?,” IEEE Transactions on Green Communications and Networking, vol. 3, no. 4, pp. 988–996, December 2019.

[52] T.-Y. Wu, L. R. Varshney, and V. Y. F. Tan, “On the Throughput of Channels that Wear Out,” IEEE Transactions on Communications, vol. 67, no. 8, pp. 5311–5320, August 2019.

[51] D. Seo and L. R. Varshney, “Information and Energy Transmission with Experimentally-Sampled Harvesting Functions,” IEEE Transactions on Communications, vol. 67, no. 6, pp. 4479–4490, June 2019.

[50] L. R. Varshney, “Mathematical Limit Theorems for Computational Creativity,” IBM Journal of Research and Development, vol. 63, no. 1, pp. 2:1–2:12, January/February 2019.

[49] L. R. Varshney, F. Pinel, K. R. Varshney, D. Bhattacharjya, A. Schoergendorfer, and Y.-M. Chee, “A Big Data Approach to Computational Creativity: The Curious Case of Chef Watson,” IBM Journal of Research and Development, vol. 63, no. 1, pp. 7:1–7:18, January/February 2019.

[48] L. R. Varshney, “Must Surprise Trump Information?,” IEEE Technology and Society Magazine, vol. 38, no. 1, pp. 81–87, March 2019. 

[47] Y. Kim, R. K. Raman, Y.-S. Kim, L. R. Varshney, and N. R. Shanbhag, “Efficient Local Secret Sharing for Distributed Blockchain Systems,” IEEE Communications Letters, vol. 23, no. 2, pp. 282–285, February 2019. 

[46] N. R. Shanbhag, N. Verma, Y. Kim, A. D. Patil, and L. R. Varshney, “Shannon-inspired Statistical Computing for the Nanoscale Era,” Proceedings of the IEEE, vol. 107, no. 1, pp. 90–107, January 2019. 

[45] A. Sarathy, N. B. M. Athreya,  L. R. Varshney, and J.-P. Leburton, “Classification of Epigenetic Biomarkers with Atomically Thin Nanopores,” Journal of Physical Chemistry Letters, vol. 9, no. 19, pp. 5718–5725, October 2018. 

[44] R. K. Raman and L. R. Varshney, “Universal Joint Image Clustering and Registration using Multivariate Information Measures,” IEEE Journal of Selected Topics in Signal Processing, vol. 12, no. 4, pp. 928–943, October 2018. 

[43] Y. Kim, M. Kang, L. R. Varshney, and N. R. Shanbhag, “Generalized Water-Filling for Source-Aware Energy-Efficient SRAMs,” IEEE Transactions on Communications, vol. 66, no. 10, pp. 4826–4841, October 2018. 

[42] M. Kazama, M. Sugimoto, C. Hosokawa, K. Matsushima, L. R. Varshney, and Y. Ishikawa, “A Neural Network System for Transformation of Regional Cuisine Style,” Frontiers in ICT, vol. 5, no. 14, July 2018. 

[41] A. Vempaty, L. R. Varshney, G. J. Koop, A. H. Criss, and P. K. Varshney, “Experiments and Models for Decision Fusion by Humans in Inference Networks,” IEEE Transactions on Signal Processing, vol. 66, no. 11, pp. 2960–2971, June 2018. 

[40] A. Chatterjee, M. Borokhovich, L. R. Varshney, and S. Vishwanath, “Efficient and Flexible Crowdsourcing of Specialized Tasks with Precedence Constraints,” IEEE/ACM Transactions on Networking, vol. 26, no. 2, pp. 879–892, April 2018. 

[39] A. J. Gross, D. Murthy, and L. R. Varshney, “Pace of Life in Cities and the Emergence of Town Tweeters,” SAGE Open, vol. 7, no. 4, October-December 2017. 

[38] A. Chatterjee, L. R. Varshney, and S. Vishwanath, “Work Capacity of Regulated Freelance Platforms: Fundamental Limits and Decentralized Schemes,” IEEE/ACM Transactions on Networking, vol. 25, no. 6, pp. 3641–3654, December 2017.

[37] I. Lobel, E. Sadler, and L. R. Varshney, “Customer Referral Incentives and Social Media,” Management Science, vol. 63, no. 10, pp. 3514–3529, October 2017.

[36] A. Sharma, K. Jagannathan, and L. R. Varshney, “Queuing Approaches to Principal-Agent Communication under Information Overload,” IEEE Transactions on Information Theory, vol. 63, no. 9, pp. 6041–6058, September 2017. 

[35] N. Kshetry and L. R. Varshney, “Foodsheds in Virtual Water Flow Networks: A Spectral Graph Theory Approach,” Frontiers in ICT, vol. 4, no. 17, June 2017. 

[34] A. Chatterjee, D. Seo, and L. R. Varshney, “Capacity of Systems with Queue-Length Dependent Service Quality,” IEEE Transactions on Information Theory, vol. 63, no. 6, pp. 3950–3963, June 2017. 

[33] F. Ji, W. P. Tay, and L. R. Varshney, “An Algorithmic Framework for Estimating Rumor Sources with Different Start Times,” IEEE Transactions on Signal Processing, vol. 65, no. 10, pp. 2517–2530, May 2017.

[32] L. Chang, A. Chatterjee, and L. R. Varshney, “Performance of LDPC Decoders with Missing Connections,” IEEE Transactions on Communications, vol. 65, no. 2, pp. 511–524, February 2017.

[31] Q. Li, A. Vempaty, L. R. Varshney, and P. K. Varshney, “Multi-object Classification via Crowdsourcing with a Reject Option,” IEEE Transactions on Signal Processing, vol. 65, no. 4, pp. 1068–1081, February 2017.

[30] L. R. Varshney and K. R. Varshney, “Decision Making with Quantized Priors Leads to Discrimination,” Proceedings of the IEEE, vol. 105, no. 2, pp. 241–255, February 2017.

[29] L. R. Varshney, J. Kusuma, and V. K. Goyal, “On Palimpsests in Neural Memory: An Information Theory Viewpoint,” IEEE Transactions on Molecular, Biological, and Multi-Scale Communications, vol. 2, no. 2, pp. 143–153, December 2016.

[28] L. R. Varshney, J. Kusuma, and V. K. Goyal, “Malleable Coding for Updatable Cloud Caching,” IEEE Transactions on Communications, vol. 64, no. 12, pp. 4946–4955, December 2016.

[27] L. R. Varshney, J. Wang, and K. R. Varshney, “Associative Algorithms for Computational Creativity,” Journal of Creative Behavior, vol. 50, no. 3, pp. 211–223, September 2016.

[26] A. Tandon, M. Motani, and L. R. Varshney, “Subblock-Constrained Codes for Real-Time Simultaneous Energy and Information Transfer,” IEEE Transactions on Information Theory, vol. 62, no. 7, pp. 4212–4227, July 2016.

[25] L. R. Varshney, “Fundamental Limits of Data Analytics in Sociotechnical Systems,” Frontiers in ICT, vol. 3, no. 2, February 2016. (Inaugural Article)

[24] K. R. Varshney and L. R. Varshney, “Olfactory Signal Processing,” Digital Signal Processing, vol. 48, pp. 84–92, January 2016.

[23] M. Hasegawa-Johnson, J. Cole, P. Jyothi, and L. R. Varshney, “Models of Dataset Size, Question Design, and Cross-Language Speech Perception for Speech Crowdsourcing Applications,” Laboratory Phonology, vol. 6, no. 3-4, pp. 381–431, October 2015.

[22] B. He, A. Wein, L. R. Varshney, J. Kusuma, A. G. Richardson, and L. Srinivasan, “Generalized Analog Thresholding for Spike Acquisition at Ultra-Low Sampling Rates,” Journal of Neurophysiology, vol. 114, no. 1, pp. 746–760, July 2015.

[21] A. Vempaty and L. R. Varshney, “The Non-Regular CEO Problem,” IEEE Transactions on Information Theory, vol. 61, no. 5, pp. 2764–2775, May 2015.

[20] K. R. Varshney and L. R. Varshney, “Optimal Grouping for Group Minimax Hypothesis Testing,” IEEE Transactions on Information Theory, vol. 60, no. 10, pp. 6511–6521, October 2014.

[19] H. Chen, L. R. Varshney, and P. K. Varshney, “Noise-Enhanced Information Systems,” Proceedings of the IEEE, vol. 102, no. 10, pp. 1607–1621, October 2014.

[18] A. Karbasi, A. H. Salavati, A. Shokrollahi, and L. R. Varshney, “Noise Facilitation in Associative Memories of Exponential Capacity,” Neural Computation, vol. 26, no. 11, pp. 2493–2526, November 2014.

[17] A. Vempaty, L. R. Varshney, and P. K. Varshney, “Reliable Crowdsourcing for Multi-Class Labeling using Coding Theory,” IEEE Journal of Selected Topics in Signal Processing, vol. 8, no. 4, pp. 667–679, August 2014.

[16] S. U. Appel, D. Botti, J. Jamison, L. Plant, J. Y. Shyr, and L. R. Varshney, “Predictive Analytics can Facilitate Proactive Property Vacancy Policies for Cities,” Technological Forecasting and Social Change, vol. 89, pp. 161–173, November 2014.

[15] L. R. Varshney, “The Wiring Economy Principle for Designing Inference Networks,” IEEE Journal on Selected Areas in Communications, vol. 31, no. 6, pp. 1095–1104, June 2013.

[14] L. R. Varshney and J. Z. Sun, “Why Do We Perceive Logarithmically?,” Significance, vol. 10, no. 1, pp. 28–31, February 2013.

[13] J. Z. Sun, G. I. Wang, V. K. Goyal, and L. R. Varshney, “A Framework for Bayesian Optimality of Psychophysical Laws,” Journal of Mathematical Psychology, vol. 56, no. 6, pp. 495–501, December 2012.

[12] L. R. Varshney, S. K. Mitter, and V. K. Goyal, “An Information-Theoretic Characterization of Channels That Die,” IEEE Transactions on Information Theory, vol. 58, no. 9, pp. 5711–5724, September 2012.

[11] J. B. Rhim, L. R. Varshney, and V. K. Goyal, “Quantization of Prior Probabilities for Collaborative Distributed Hypothesis Testing,” IEEE Transactions on Signal Processing, vol. 60, no. 9, pp. 4537–4550, September 2012.

[10] L. R. Varshney, “The Google Effect in Doctoral Theses,” Scientometrics, vol. 92, no. 3, pp. 785–793, September 2012.

[9] L. R. Varshney and S. K. Mitter, “Sensitivity of Quadratic Gaussian Matching to Interference,” IEEE Communications Letters, vol. 15, no. 9, pp. 922–924, September 2011.

[8] V. Misra, V. K. Goyal, and L. R. Varshney, “Distributed Scalar Quantization for Computing: High-Resolution Analysis and Extensions,” IEEE Transactions on Information Theory, vol. 57, no. 8, pp. 5298–5325, August 2011.

[7] H. Q. Nguyen, V. K. Goyal, and L. R. Varshney, “Frame Permutation Quantization,” Applied and Computational Harmonic Analysis, vol. 31, no. 1, pp. 74–97, July 2011.

[6] L. R. Varshney “Performance of LDPC Codes Under Faulty Iterative Decoding,” IEEE Transactions on Information Theory, vol. 57, no. 7, pp. 4427–4444, July 2011.

[5] L. R. Varshney, B. L. Chen, E. Paniagua, D. H. Hall, and D. B. Chklovskii, “Structural Properties of the Caenorhabditis elegans Neuronal Network,” PLoS Computational Biology, vol. 7, no. 2, e1001066, February 2011.

[4] H. Q. Nguyen, L. R. Varshney, and V. K. Goyal, “Concentric Permutation Source Codes,” IEEE Transactions on Communications, vol. 58, no. 11, pp. 3154–3164, November 2010.

[3] K. R. Varshney and L. R. Varshney, “Quantization of Prior Probabilities for Hypothesis Testing,” IEEE Transactions on Signal Processing, vol. 56, no. 10, pp. 4553–4562, October 2008.

[2] L. R. Varshney, “Local Fidelity, Constrained Codes, and the Meru Prastara,” IEEE Potentials, vol. 27, no. 2, pp. 27–32, March/April 2008.

[1] L. R. Varshney, P. J. Sjöström, and D. B. Chklovskii, “Optimal Information Storage in Noisy Synapses under Resource Constraints,” Neuron, vol. 52, no. 3, pp. 409–423, November 2006. 

Anthology Contributions

[1] L. R. Varshney and J. Z. Sun, “Why Do We Perceive Logarithmically?,” in The Best Writing on Mathematics 2014, M. Pitici (ed.), Princeton University Press, 2014: pp. 64-73.

Book Reviews

[1] L. R. Varshney, “Mathematizing the World,” Issues in Science and Technology, vol. 35, no. 2, pp. 93–95, Winter 2019. [review of J. Soni and R. Goodman, A Mind at Play: How Claude Shannon Invented the Information Age, New York, NY: Simon & Schuster, 2017.]

Book Chapters (excluding conference proceedings)

[12] F. J. Alexander, K.-R. Reyes, L. R. Varshney, and B.-J. Yoon, “AI for Optimal Experimental Design and Decision-Making,” Artificial Intelligence for Science: A Deep Learning Revolution, A. Choudhary, G. Fox, and T. Hey (eds.), World Scientific, 2023, pp. 609–625.

[11] R. K. Raman and L. R. Varshney, “Information-Theoretic Approaches to Scalable Blockchain Systems and Distributed Trust,” Handbook on Blockchain, M. Thai, B. Krishnamachari, and D. Tran (eds.), Springer, 2022, pp. 257–296.

[10] H. Zhou, A. Jagmohan, and L. R. Varshney, “Algorithms to Localize Food Contamination Events in Blockchain-based Trusted Food Supply Chains,” in Harnessing Big Data in Food Safety, J. M. Farber, R. Dara, and J. Ronholm (eds.), Springer, 2023, pp. 113–124.

[9] R. K. Raman and L. R. Varshney, “Universal Clustering,” in Information-Theoretic Methods in Data Science, Y. Eldar and M. Rodrigues (eds.), Cambridge University Press, 2021, pp. 263–301.

[8] A. Chatterjee and L. R. Varshney, “Optimal Energy Allocation in Reliable Neural Sensory Processing,” in Encyclopedia of Computational Neuroscience, D. Jaeger and R. Jung (eds.), Springer, 2019.

[7] L. R. Varshney, “Dimensions, Bits, and Wows in Accelerating Materials Discovery,” in Materials Discovery and Design, T. Lookman, S. Eidenbenz, F. Alexander, and C. Barnes (eds.), Springer Nature, 2018, pp. 1–14. 

[6] G. V. Ranade and L. R. Varshney, “The Role of Information Patterns in Designing Crowdsourcing Contests,” in Creating and Capturing Value Through Crowdsourcing, C. Tucci, A. Afuah, and G. Viscusi (eds.), Oxford University Press, 2018, pp. 154–177.

[5] R. Vaculin, Y.-M. Chee, D. V. Oppenheim, and L. R. Varshney, “A Service-Oriented Algebra for Optimizing the Management of Service Requests,” in Maximizing Management Performance and Quality with Service Analytics, Y. Diao and D. Rosu (eds.), IGI Global, 2015, pp. 347–375.

[4] F. Pinel, L. R. Varshney, and D. Bhattacharjya, “A Culinary Computational Creativity System,” in Computational Creativity Research: Towards Creative Machines, T. R. Besold, M. Schorlemmer, and A. Smaill (eds.), Springer, 2015: pp. 327–346.

[3] D. V. Oppenheim, L. R. Varshney, and Y.-M. Chee, “Work as a Service,” in Advanced Web Services, A. Bouguettaya, Q. Z. Sheng, and F. Daniel (eds.), Springer, 2014: pp. 409–430.

[2] J. B. Rhim, L. R. Varshney, and V. K. Goyal, “Distributed Decision Making by Categorically-Thinking Agents,” in Decision Making and Imperfection, T. V. Guy, M. Karny, and D. H. Wolpert (eds.), Springer, 2013: pp. 37–63.

[1] L. R. Varshney and S. D. Servetto, “A Distributed Transmitter for the Sensor Reachback Problem Based on Radar Signals,” in Advances in Pervasive Computing and Networking, B. K. Szymanski and B. Yener (eds.), Boston: Kluwer Academic Publishers, 2005: pp. 37–63.

Conference Papers

[171] A. Chin, L. R. Varshney, G. Singh, J. Riel, R. Avadhanam, and V. Sachdev, “A Conceptual Framework for Guiding the Workforce on Using Responsible AI,” in Proceedings of the IEEE International Symposium on Ethics in Engineering, Science, and Technology (ETHICS), Evanston, IL, 6-8 June 2025.

[170] A. Zhang and L. R. Varshney, “Conceptualizing Agency: A Framework for Human-AI Interaction,” in Proceedings of the 6th Workshop on Human-AI Co-Creation with Generative Models (HAI-GEN), Cagliari, Italy, 24 March 2025.

[169] L. Huang, L. R. Varshney, and K. E. Willcox, “Formal Verification of Digital Twins,” in 2025 Digital Engineering Conference, Idaho Falls, ID, 20-21 May 2025.

[168] A. Pattanaik and L. R. Varshney, “Online Reinforcement Learning with Passive Memory,” in Proceedings of the American Control Conference, Denver, CO, 8-10 July 2025.

[167] X. Qian, B.-J. Yoon, L .R. Varshney, K.-R. Reyes, H. G. Martin, and N. M. Urban, “Objective-driven AI for Automated Synthetic Biology,” in DOE BER/ASCR Workshop on Envisioning Frontiers in AI and Computing for Biological Research, Rockville, MD, 4-6 February 2025.

[166] B. Akpa, F. J. Alexander, B. Al-Lazikani, A. Attia, C. Blaby-Haas, N. Chia, C. Chung, P. Coveney, I. Foster, D. Jafray, S. Jha, A. Kapadia, R. Madduri, M. McKerns, H. Mukundan, P. Nugent, Y. Paschalidis, A. Ramanathan, D. Ratner, A. Singh, E. Stahlberg, L. R. Varshney, M. Wang, T. Yankeelov, B.-J. Yoon, and Y. Zhu, “Accelerating Goal-driven Science by Optimizing Operational Decisions,” in DOE BER/ASCR Workshop on Envisioning Frontiers in AI and Computing for Biological Research, Rockville, MD, 4-6 February 2025.

[165] M. Chisolm-Straker and L. R. Varshney, “Leveraging Privacy-Enhancing Technology to Better Serve the United States’ Public,” in Proceedings of the 2024 IEEE International Conference on Big Data, Washington, D.C., 15-18 December 2024.

[164] A. K. Nayak and L. R. Varshney, “An Information Theory of Compute-Optimal Size Scaling, Emergence, and Plateaus in Language Models,” in Compression Workshop @ NeurIPS 2024, 15 December 2024. (Oral Presentation)

[163] X. Wu and L. R. Varshney, “Clusters Emerge in Transformer-based Causal Language Models,” in 7th BlackboxNLP Workshop, Miami, Florida, 15 November 2024.

[162] L. R. Varshney, J. Schutt-Ainé, S. Rakheja, and S. Ghose, “Co-Design Methodologies for Integrating Small Organism-Inspired Chiplets,” in DOE Neuromorphic Computing for Science Workshop, Bethesda, Maryland, 12-13 September 2024.

[161] A. R. Ellis-Mohr, M. Gazzola, and L. R. Varshney, “Synthetic Neurocomputers: Advancing Scientific Research through Computing with Living Neurons,” in DOE Analog Computing for Science Workshop, Bethesda, Maryland, 11-13 September 2024.

[160] R. Baltaji, B. Hemmatian, and L. R. Varshney, “Conformity, Confabulation, and Impersonation: Persona Inconstancy in Multi-Agent LLM Collaboration,” in 2nd Workshop on Cross-Cultural Considerations in NLP, Bangkok, Thailand, 16 August 2024.

[159] S. M. Azimi-Abarghouyi and L. R. Varshney, “Federated Learning via Lattice Joint Source-Channel Coding,” in Proceedings of the IEEE International Symposium on Information Theory, Athens, Greece, 7-12 July 2024.

[158] H. Yu and L. R. Varshney, “Semantic Compression with Information Lattice Learning,” in Proceedings of the IEEE International Symposium on Information Theory Workshops, Athens, Greece, 7-12 July 2024.

[157] A. R. Ellis-Mohr and L. R. Varshney, “Directed Information Flow in Computing Systems with Living Neurons,” in Proceedings of the IEEE International Symposium on Information Theory Workshops, Athens, Greece, 7-12 July 2024.

[156] A. Naik, P. M. Arnold, and L. R. Varshney, “Modeling Clinical Symptoms of Cognitive Decline in Neurodegenerative Disease as Faulty Computing,” in Proceedings of the IEEE International Symposium on Information Theory Workshops, Athens, Greece, 7-12 July 2024.

[155] A. Bhimaraju, A. Chatterjee, and L. R. Varshney, “Dynamic Resource Allocation to Minimize Concave Costs of Shortfalls,” in Proceedings of the American Control Conference, Toronto, Canada, 10-12 July 2024.

[154] X. Wu and L. R. Varshney, “Transformer-based Causal Language Models from a Meta-Learning Perspective,” in NeurIPS Workshop on Attributing Model Behavior at Scale, New Orleans, Louisiana, 15 December 2023.

[153] B. Hemmatian, R. Baltaji, and L. R. Varshney, “Muslim-Violence Bias Persists in Debiased GPT Models,” in Muslims in Machine Learning Workshop (NeurIPS 2023), New Orleans, Louisiana, 11 December 2023.

[152] S. Basu, M. Choraria, and L. R. Varshney, “Transformers are Universal Predictors,” in Neural Compression Workshop (ICML 2023), Honolulu, Hawaii, 29 July 2023.

[151] I. Ferwana, S. Park, T.-Y. Wu, and L. R. Varshney, “Designing Discontinuities,” in Neural Compression Workshop (ICML 2023), Honolulu, Hawaii, 29 July 2023.

[150] R. Baltaji and P. Thakkar, “Probing Numeracy and Logic of Language Models of Code,” in 1st International Workshop on Interpretability and Robustness in Neural Software Engineering (InteNSE’23), Melbourne, Australia, 14 May 2023.

[149] A. Issak and L. R. Varshney, “Prompt Programming for the Visual Domain,” in Proceedings of the 11th International Conference on Learning Representations (ICLR), Kigali, Rwanda, 5 May 2023.

[148] K. R. Varshney and L. R. Varshney, “A Banal Account of a Safety-Creativity Tradeoff in Generative AI,” in IUI Workshop on Designing for Safety in Human-AI Interactions, Sydney, Australia, 27 March 2023.

[147] I. George, X. Chen, and L. R. Varshney, “Search for Extraterrestrial Intelligence As One-Shot Hypothesis Testing,” in Proceedings of the 57th Annual Conference on Information Sciences and Systems, Baltimore, Maryland, 22-24 March 2023.

[146] M. Choraria, D. Szwarcman, B. Zadrozny, C. Watson, and L. R. Varshney, “Controllable Generation for Climate Modeling,” in NeurIPS 2022 Workshop on Tackling Climate Change with Machine Learning, 9 December 2022.

[145] S. Spencer and L. R. Varshney, “Awareness-Constrained Discrete Choice in Multilayer Network Formation and Evolution,” in Conference Record of the Fifty-Sixth Asilomar Conference on Signals, Systems and Computers, Pacific Grove, California, 30 October – 2 November 2022.

[144] X. Wu, A. Hanganu, A. Hoshino, and L. R. Varshney, “Source Identification for Exosomal Communication via Protein Language Models,” in Proceedings of the 32nd IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2022), Xi’an, China, 22-25 August 2022.

[143] A. A. Issak and L. R. Varshney, “Artistic Autonomy in AI Art,” in Proceedings of the 13th International Conference on Computational Creativity (ICCC’22), Bozen-Bolzano, Italy, 27 June – 1 July 2022.

[142] A. Bhimaraju and L. R. Varshney, “Scheduling Group Tests Over Time,” in Proceedings of the IEEE International Symposium on Information Theory, Espoo, Finland, 26 June – 1 July 2022.

[141] S. Basu, P. Katdare, K. R. Driggs-Campbell, and L. R. Varshney, “Gauge Equivariant Deep Q-Learning on Discrete Manifolds,” in ICLR Workshop on Geometrical and Topological Representation Learning, 29 April 2022.

[140] E. Anderson, R. Wilcox, A. K. Nayak, C. Zwilling, P. Robles-Granda, L. R. Varshney, B. Kim, and A. K. Barbey, “Advanced Methods for Connectome-Based Predictive Modeling of Human Intelligence: A Novel Approach Based on Individual Differences in Cortical Topography,” in NeurIPS 2021 AI for Science Workshop, 13 December 2021.

[139] A. A. Issak, “Artistic Autonomy in AI Art,” in NeurIPS Workshop on ML for Creativity and Design 2021, 13 December 2021.

[138] M. Choraria, I. Ferwana, A. Mani, and L. R. Varshney, “Balancing Robustness and Fairness via Partial Invariance,” in NeurIPS 2021 Workshop on Algorithmic Fairness through the Lens of Causality and Robustness, 13 December 2021.

[137] J. A. Evans, K. Opoku-Agyemang, K. Ratakonda, K. R. Varshney, and L. R. Varshney, “Blockchain and the Scientific Method,” in ASCR Workshop on Cybersecurity and Privacy for Scientific Computing Ecosystems, November 2021.

[136] A. Jain, D. Oliveira, A. Sharma, L. R. Varshney, C. Watson, K. Weldemariam, D. Wuebbles, and B. Zadrozny, “Toward an AI-based Framework for Accelerated Discovery of Climate Impacts on Agriculture,” in AAAI Fall Symposium on AI Meets Food Security: Intelligent Approaches for Climate-Aware Agriculture, 4-6 November 2021.

[135] P. Sharma and L. R. Varshney, “Rational Inattention in Choice Overload: Clustering for Discrete Choices,” in Conference Record of the Fifty-Fifth Asilomar Conference on Signals, Systems and Computers, [Pacific Grove, California], 31 October – 3 November 2021.

[134] E. Dupraz, L. R. Varshney, and F. Leduc-Primeau, “Power-Efficient Deep Neural Networks with Noisy Memristor Implementation,” in Proceedings of the 2021 IEEE Information Theory Workshop, [Kanazawa, Japan], 17-21 October 2021.

[133] H. Yu, J. A. Evans, D. Gallo, A. J. Kruse, W. M. Patterson, and L. R. Varshney, “AI-Aided Co-Creation for Wellbeing,” in Proceedings of the Second Workshop on the Future of Co-Creative Systems, 14-15 September 2021.

[132] H. Zhou, J. Chen, L. R. Varshney, and A. Jagmohan, “Nonstationary Reinforcement Learning with Linear Function Approximation,” in Workshop on Reinforcement Learning Theory at ICML, 24 July 2021.

[131] S. Spencer and L. R. Varshney, “Social Bubbles and Superspreaders: Source Identification for Contagion Processes on Hypertrees,” in Proceedings of the 2021 IEEE Statistical Signal Processing Workshop (SSP), [Rio de Janeiro, Brazil], 11-14 July 2021.

[130] L. Wang, H. Zhou, B. Li, L. R. Varshney, and Z. Zhao, “Near-Optimal Algorithms for Piecewise-Stationary Cascading Bandits,” in Proceedings of the 2021 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), [Toronto, Canada], 6-11 June 2021.

[129] V. S. S. Nadendla and L. R. Varshney, “A Predicament in Securing Blockchain Consensus via Controlling Cryptopuzzle Difficulty,” in Proceedings of the 2021 IEEE International Conference on Blockchain and Cryptocurrency (ICBC 2021), [Sydney, Australia], 3-6 May 2021.

[128] T. Ameen ur Rahman, A. S. Barbehenn, X. Chen, H. Dbouk, J. A. Douglas, Y. Geng, I. George, J. B. Harvill, S. W. Jeon, K. K. Kansal, K. Lee, K. A. Levick, B. Li, Z. Li, Y. Murthy, A. Muthuveeru-Subramaniam, S. Y. Olmez, M. J. Tomei, T. Veeravalli, X. Wang, E. A. Wayman, F. Wu, P. Xu, S. Yan, H. Zhang, Y. Zhang, Y. Zhang, Y. Zhao, S. Basu, and L. R. Varshney, “The Twelvefold Way of Non-Sequential Lossless Compression,” in Proceedings of the IEEE Data Compression Conference (DCC), [Snowbird, Utah], 23-26 March 2021.

[127] H. Yu, J. A. Evans, and L. R. Varshney, “Mimicking Human Minds via Information Lattices,” in NeurIPS 2020 Workshop on BabyMind: How Babies Learn and How Machines Can Imitate, 11 December 2020.

[126] Y. Kim, Y. Cassuto, and L. R. Varshney, “Distributed Boosting Classifiers over Noisy Channels,” in Conference Record of the Fifty-Fourth Asilomar Conference on Signals, Systems and Computers, [Pacific Grove, California], 1-4 November 2020.

[125] L. R. Varshney, “Respect for Human Autonomy in Recommender Systems,” in 3rd FAccTRec Workshop on Responsible Recommendation at RecSys 2020, [Rio de Janeiro, Brazil], 26 September 2020.

[124] L. R. Varshney, “Limits Theorems for Creativity with Intentionality,” in Proceedings of the Eleventh International Conference on Computational Creativity (ICCC), [Coimbra, Portugal], 7-11 September 2020.

[123] L. R. Varshney, N. F. Rajani, and R. Socher, “Explaining Creative Artifacts,” in ICML 2020 Workshop on Human Interpretability in Machine Learning (WHI), [Vienna, Austria], 17 July 2020.

[122] R. Chen and L. R. Varshney, “Optimal Recovery of Missing Values for Non-negative Matrix Factorization: A Probabilistic Error Bound,” in ICML 2020 Workshop on The Art of Learning with Missing Values (ARTEMISS), [Vienna, Austria], 17 July 2020. see

[121] J. Vig, A. Madani, L. R. Varshney, and N. F. Rajani, “(Re)Discovering Protein Structure and Function Through Language Modeling,” in ICML 2020 Workshop on ML Interpretability for Scientific Discovery, [Vienna, Austria], 17 July 2020. see

[120] R. K. Raman and L. R. Varshney, “Registration of Finite Resolution Images: Second-Order Analysis,” in Proceedings of the 2020 IEEE International Symposium on Information Theory (ISIT), [Los Angeles, California], 21-26 June 2020.

[119] E. Dupraz and L. R. Varshney, “Noisy In-Memory Recursive Computation with Memristor Crossbars,” in Proceedings of the 2020 IEEE International Symposium on Information Theory (ISIT), [Los Angeles, California], 21-26 June 2020.

[118] S. Basu, D. Seo, and L. R. Varshney, “Hypergraph-based Coding Schemes for Two Source Coding Problems under Maximal Distortion,” in Proceedings of the 2020 IEEE International Symposium on Information Theory (ISIT), [Los Angeles, California], 21-26 June 2020.

[117] D. Seo, R. K. Raman, and L. R. Varshney, “Social Learning with Beliefs in a Parallel Network,” in Proceedings of the 2020 IEEE International Symposium on Information Theory (ISIT), [Los Angeles, California], 21-26 June 2020.

[116] A. Tandon, V. Y. F. Tan, and L. R. Varshney, “Bee-Identification Error Exponent with Absentee Bees,” in Proceedings of the 2020 IEEE International Symposium on Information Theory (ISIT), [Los Angeles, California], 21-26 June 2020.

[115] H. Yu, H. Taube, J. A. Evans, and L. R. Varshney, “Human Evaluation of Interpretability: The Case of AI-Generated Music Knowledge,” in ACM CHI 2020 Workshop on Artificial Intelligence for HCI: A Modern Approach, [Honolulu, Hawaii], 25 April 2020.

[114] S. Basu, D. Seo, and L. R. Varshney, “Functional Epsilon Entropy,” in Proceedings of the IEEE Data Compression Conference, [Snowbird, Utah], 24-27 March 2020.

[113] L. R. Varshney, N. S. Keskar, and R. Socher, “Limits of Detecting Text Generated by Large-Scale Language Models,” in Proceedings of the 2020 Information Theory and its Applications Workshop (ITA), San Diego, California, 2-7 February 2020.

[112] H. Lee, P. Achananuparp, Y. Liu, E.-P. Lim and L. R. Varshney, “Estimating Glycemic Impact of Cooking Recipes via Online Crowdsourcing and Machine Learning,” in Proceedings of the 9th International Digital Public Health Conference (DPH 2019), Marseille, France, 20-23 November 2019.

[111] A. Tandon, V. Y. F. Tan, and L. R. Varshney, “Random Coding Error Exponent for the Bee-Identification Problem,” in Proceedings of the 2019 IEEE Information Theory Workshop (ITW), Visby, Sweden, 25-28 August 2019.

[110] T.-Y. Wu, A. Tandon, M. Motani, and L. R. Varshney, “On the Outage-Constrained Capacity of Skip-Sliding Window Codes,” in Proceedings of the 2019 IEEE Information Theory Workshop (ITW), Visby, Sweden, 25-28 August 2019.

[109] D. Seo and L. R. Varshney, “The CEO Problem with rth Power of Difference Distortion,” in Proceedings of the 2019 IEEE International Symposium on Information Theory (ISIT), Paris, France, 7-12 July 2019.

[108] D. Seo and L. R. Varshney, “Information and Energy Transmission with Experimentally-Sampled Harvesting Functions,” in Proceedings of the 2019 IEEE International Symposium on Information Theory (ISIT), Paris, France, 7-12 July 2019.

[107] E. Dupraz and L. R. Varshney, “Binary Recursive Estimation on Noisy Hardware,” in Proceedings of the 2019 IEEE International Symposium on Information Theory (ISIT), Paris, France, 7-12 July 2019.

[106] T.-Y. Wu, A. Tandon, L. R. Varshney, and M. Motani, “Multicasting Energy and Information Simultaneously,” in Proceedings of the 2019 IEEE International Symposium on Information Theory (ISIT), Paris, France, 7-12 July 2019.

[105] T. Mamalis, S. Bose, and L. R. Varshney, “Ridesharing Systems with Electric Vehicles,” in Proceedings of the 2019 American Control Conference (ACC), Philadelphia, Pennsylvania, 10-12 July 2019.

[104] S. Basu and L. R. Varshney, “Polar Codes for Simultaneous Information and Energy Transmission,” in Proceedings of the 20th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Cannes, France, 2-5 July 2019.

[103] S. Agarwal and L. R. Varshney, “Limits of Deepfake Detection: A Robust Estimation Viewpoint,” in Proceedings of the ICML Workshop on Deep Learning for Detecting AudioVisual Fakes, Long Beach, California, 15 June 2019.

[102] H. Zhou, A. Jagmohan, and L. R. Varshney, “Generalized Jordan Center: A Source Localization Heuristic for Noisy and Incomplete Observations,” in Proceedings of the IEEE Data Science Workshop (DSW), Minneapolis, Minnesota, 2-5 June 2019.

[101] R. Chen and L. R. Varshney, “Non-negative Matrix Factorization of Clustered Data with Missing Values,” in Proceedings of the IEEE Data Science Workshop (DSW), Minneapolis, Minnesota, 2-5 June 2019.

[100] N. Kshetry and L. R. Varshney, “Safety in the Face of Unknown Unknowns: Algorithm Fusion in Data-Driven Engineering Systems,” in Proceedings of the 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Brighton, England, 12-17 May 2019.

[99] X. Ge, R. T. Goodwin, J. R. Gregory, R. E. Kirchain, J. Maria, and L. R. Varshney,” Accelerated Discovery of Sustainable Building Materials,” in Proceedings of the AAAI Spring Symposium on Towards AI for Collaborative Open Science, Palo Alto, California, 25-27 March 2019.

[98] L. R. Varshney, “Towards Information-Theoretic Limits of the Global Neuronal Workspace Architecture,” in Proceedings of the AAAI Spring Symposium on Towards Conscious AI Systems, Palo Alto, California, 25-27 March 2019.

[97] R. Chen, A. B. Das, and L. R. Varshney, “Registration for Image-Based Transcriptomics: Parametric Signal Features and Multivariate Information Measures,” in Proceedings of the 53rd Annual Conference on Information Sciences and Systems (CISS), Baltimore, Maryland, 20-22 March 2019.

[96] T. Mamalis, S. Bose, and L. R. Varshney, “Business-to-Peer Carsharing Systems with Electric Vehicles,” in Proceedings of the 53rd Annual Conference on Information Sciences and Systems (CISS), Baltimore, Maryland, 20-22 March 2019.

[95] H. Yu, I. Mineyev, and L. R. Varshney, “To Abstract via Algebraic Innateness: Hierarchical, Interpretable, and Task-Free Clustering,” in Proceedings of the 2019 Information Theory and its Applications Workshop (ITA), San Diego, California, 10-15 February 2019.

[94] S. Basu and L. R. Varshney, “Succinct Source Coding of Deep Neural Networks,” in Proceedings of NeurIPS Compact Deep Neural Network Representation with Industrial Applications Workshop (CDNNRIA), Montreal, Canada, 7 December 2018.

[93] S. E. Brown, X. Ge, P. Rana, L. R. Varshney, and D. C. Miller, “Network Analysis as a Tool for Shaping Conservation and Development Policy: A Case Study of Timber Market Optimization in India,” in Proceedings of the Data for Good Exchange (D4GX), New York, New York, 16 September 2018.

[92] X. Ge, J. Xiong, and L. R. Varshney, “Computational Creativity for Valid Rube Goldberg Machines,” in Proceedings of the Ninth International Conference on Computational Creativity (ICCC), Salamanca, Spain, 25-29 June 2018.

[91] D. Bhattacharjya, D. Subramanian, and L. R. Varshney, “Generalization across Contexts in Unsupervised Computational Creativity,” in Proceedings of the Ninth International Conference on Computational Creativity (ICCC), Salamanca, Spain, 25-29 June 2018.

[90] R. K. Raman and L. R. Varshney, “Dynamic Distributed Storage for Blockchains,” in Proceedings of the 2018 IEEE International Symposium on Information Theory (ISIT), Vail, Colorado, 17-22 June 2018.

[89] D. Seo, A. Chatterjee, and L. R. Varshney, “On Multiuser Systems with Queue-Length Dependent Service Quality,” in Proceedings of the 2018 IEEE International Symposium on Information Theory (ISIT), Vail, Colorado, 17-22 June 2018.

[88] Y. Kim, M. Kang, L. R. Varshney, and N. R. Shanbhag, “SRAM Bit-line Swings Optimization using Generalized Waterfilling,” in Proceedings of the 2018 IEEE International Symposium on Information Theory (ISIT), Vail, Colorado, 17-22 June 2018.

[87] T.-Y. Wu, A. Tandon, L. R. Varshney, and M. Motani, “Skip Sliding Window Codes,” in Proceedings of the 2018 IEEE International Symposium on Information Theory (ISIT), Vail, Colorado, 17-22 June 2018.

[86] R. K. Raman and S. Pattabiraman, “Selfish Learning: Leveraging the Greed in Social Learning,” in Proceedings of the 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Calgary, Canada, 15-20 April 2018. 

[85] D. Seo, R. K. Raman, and L. R. Varshney, “Probability Reweighting in Social Learning: Optimality and Suboptimality,” in Proceedings of the 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Calgary, Canada, 15-20 April 2018. 

[84] T.-Y. Wu, X. Ge, and L. R. Varshney, “Surprising Sequences for Communication and Conversation,” in Proceedings of the 52nd Annual Conference on Information Sciences and Systems (CISS), Princeton, New Jersey, 21-23 March 2018. (LRV Invited)

[83] R. K. Raman and L. R. Varshney, “Distributed Storage Meets Secret Sharing on the Blockchain,” in Proceedings of the 2018 Information Theory and its Applications Workshop (ITA), San Diego, California, 11-16 February 2018. (LRV Invited)

[82] D. G. Dobakhshari, L. R. Varshney, and V. Gupta, “A Game-Theoretic Approach to a Task Delegation Problem,” in Conference Record of the Fifty-First Asilomar Conference on Signals, Systems and Computers, Pacific Grove, California, 29 October – 1 November 2017.

[81] B. S. Newell and L. R. Varshney, “The First Cohort in a New Innovation, Leadership, and Engineering Entrepreneurship B. S. Degree Program,” in Proceedings of the 2017 IEEE Frontiers in Education Conference (FIE), Indianapolis, Indiana, 18-21 October 2017. 

[80] T.-Y. Wu, L. R. Varshney, and V. Y. F. Tan, “Communication over a Channel that Wears Out,” in Proceedings of the IEEE International Symposium on Information Theory (ISIT), Aachen, Germany, 25-30 June 2017. 

[79] A. Chatterjee and L. R. Varshney, “Towards Optimal Quantization of Neural Networks,” in Proceedings of the IEEE International Symposium on Information Theory (ISIT), Aachen, Germany, 25-30 June 2017. 

[78] R. K. Raman and L. R. Varshney, “Universal Joint Image Clustering and Registration using Partition Information,” in Proceedings of the IEEE International Symposium on Information Theory (ISIT), Aachen, Germany, 25-30 June 2017. 

[77] R. K. Raman and L. R. Varshney, “Budget-Optimal Clustering via Crowdsourcing,” in Proceedings of the IEEE International Symposium on Information Theory (ISIT), Aachen, Germany, 25-30 June 2017. 

[76] A. Chaaban, L. R. Varshney, and M.-S. Alouini, “The Capacity of Injective Semi-Deterministic Two-Way Channels,” in Proceedings of the IEEE International Symposium on Information Theory (ISIT), Aachen, Germany, 25-30 June 2017. 

[75] M. Amencherla and L. R. Varshney, “Color-Based Visual Sentiment for Social Communication,” in Proceedings of the 15th Canadian Workshop on Information Theory, Quebec City, Canada, 11-14 June 2017. 

[74] S. Basu and L. R. Varshney, “Universal Source Coding of Deep Neural Networks,” in Proceedings of the IEEE Data Compression Conference, Snowbird, Utah, 4-7 April 2017. 

[73] A. Chatterjee and L. R. Varshney, “Energy-Reliability Limits in Nanoscale Neural Networks,” in Proceedings of the Conference on Information Sciences and Systems (CISS), Baltimore, Maryland, 22-24 March 2017. 

[72] R. K. Raman, H. Yu, and L. R. Varshney, “Illum Information,” in Proceedings of the 2017 Information Theory and its Applications Workshop (ITA), San Diego, California, 12-17 February 2017. (LRV Invited) 

[71] W. Chen, M. Hasegawa-Johnson, N. F. Chen, P. Jyothi, and L. R. Varshney, “Mismatched Crowdsourcing with Clustering-Based Phonetic Projection for Low-Resourced ASR,” in Proceedings of the 26th International Conference on Computational Linguistics Workshops (COLING 2016), Osaka, Japan, 11 December 2016.

[70] J. Feng, W. P. Tay, and L. R. Varshney, “Estimating the Number of Infection Sources in a Tree,” in Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP), Washington, D.C., 7-9 December 2016. 

[69] M. A. Donmez, M. Raginsky, A. C. Singer, and L. R. Varshney, “Cost-Performance Tradeoffs in Unreliable Computation Architectures,” in Conference Record of the Fiftieth Asilomar Conference on Signals, Systems and Computers, Pacific Grove, California, 6-9 November 2016. 

[68] A. Chatterjee, D. Seo, and L. R. Varshney, “Capacity of Systems with Queue-Length Dependent Service Quality,” in Proceedings of the International Symposium on Information Theory and Its Applications (ISITA), Monterey, California, 30 October – 2 November 2016.

[67] D. Seo and L. R. Varshney, “Information-Theoretic Limits of Algorithmic Noise Tolerance,” in Proceedings of the IEEE International Conference on Rebooting Computing (ICRC 2016), San Diego, California, 17-19 October 2016. 

[66] L. Chang, A. Chatterjee, and L. R. Varshney, “LDPC Decoders with Missing Connections,” in Proceedings of the 2016 IEEE International Symposium on Information Theory (ISIT), Barcelona, Spain, 10-15 July 2016.

[65] A. Tandon, M. Motani, and L. R. Varshney, “Subblock Energy-Constrained Codes for Simultaneous Energy and Information Transfer,” in Proceedings of the 2016 IEEE International Symposium on Information Theory (ISIT), Barcelona, Spain, 10-15 July 2016.

[64] H. Yu, L. R. Varshney, G. E. Garnett, and R. Kumar, “MUS-ROVER: A Self-Learning System for Musical Compositional Rules,” in Proceedings of the 4th International Workshop on Musical Metacreation (MUME 2016), Paris, France, 27 June 2016.

[63] H. Yu, L. R. Varshney, G. E. Garnett, and R. Kumar, “Learning Interpretable Musical Compositional Rules and Traces,” in 2016 ICML Workshop on Human Interpretability in Machine Learning (WHI 2016), New York, New York, 23 June 2016.

[62] C.-S. Yang and L. R. Varshney, “Self-Sustainable OFDM Transmissions with Smooth Energy Delivery,” in Proceedings of the 5th International Symposium on Next-Generation Electronics (ISNE 2016), Hsinchu, Taiwan, 3-6 May 2016.

[61] L. R. Varshney, “Bottleneck Capacity of Random Graphs for Connectomics,” in Proceedings of the 2016 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Shanghai, China, 20-25 March 2016.

[60] Song Jianhan, V. W. I. Phua, and L. R. Varshney, “Distributed Estimation via Paid Crowd Work,” in Proceedings of the 2016 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Shanghai, China, 20-25 March 2016.

[59] L. R. Varshney and K. R. Varshney, “Fidelity Loss in Distribution-Preserving Anonymization and Histogram Equalization,” in Proceedings of the 50th Annual Conference on Information Sciences and Systems (CISS), Princeton, New Jersey, 16-18 March 2016.

[58] A. Chatterjee and L. R. Varshney, “Energy-Reliability Limits in Nanoscale Circuits,” in Proceedings of the 2016 Information Theory and its Applications Workshop (ITA), San Diego, California, 31 January – 5 February 2016. (AC Invited) 

[57] L. R. Varshney, P. Jyothi, and M. Hasegawa-Johnson, “Language Coverage for Mismatched Crowdsourcing,” in Proceedings of the 2016 Information Theory and its Applications Workshop (ITA), San Diego, California, 31 January – 5 February 2016. (PJ Invited) 

[56] H. Bai, R. Chunara, and L. R. Varshney, “Social Capital Deserts: Obesity Surveillance using a Location-Based Social Network,” in Proceedings of the Data for Good Exchange (D4GX), New York, New York, 28 September 2015. (NYC Media Lab – Bloomberg Data for Good Exchange Paper Award)

[55] M. Borokhovich, A. Chatterjee, J. Rogers, L. R. Varshney, and S. Vishwanath, “Improving Impact Sourcing via Efficient Global Service Delivery,” in Proceedings of the Data for Good Exchange (D4GX), New York, New York, 28 September 2015.

[54] A. Vempaty, L. R. Varshney, G. J. Koop, A. H. Criss, and P. K. Varshney, “Decision Fusion by People: Experiments, Models, and Sociotechnical System Design,” in Proceedings of the 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP), Orlando, Florida, 14-16 December 2015.

[53] L. R. Varshney, “Toward Limits of Constructing Reliable Memories from Unreliable Components,” in Proceedings of the IEEE Information Theory Workshop (ITW), Jeju Island, Korea, 11-15 October 2015.

[52] M. Karzand and L. R. Varshney, “Communication Strategies for Low Latency Trading,” in Proceedings of the 2015 IEEE International Symposium on Information Theory (ISIT), Hong Kong, 14-19 June 2015.

[51] A. Tandon, M. Motani, and L. R. Varshney, “Real-time Simultaneous Energy and Information Transfer,” in Proceedings of the 2015 IEEE International Symposium on Information Theory (ISIT), Hong Kong, 14-19 June 2015.

[50] A. Vempaty and L. R. Varshney, “CEO Problem for Belief Sharing,” in Proceedings of the IEEE Information Theory Workshop (ITW), Jerusalem, 26 April – 1 May, 2015.

[49] A. Tandon, M. Motani, and L. R. Varshney, “On the Capacity and Applications of Codes with Certain Subblock Constraints,” in Proceedings of the 2015 Information Theory and its Applications Workshop (ITA), San Diego, California, 1-6 February 2015. (MM Invited)

[48] A. Tandon, M. Motani, and L. R. Varshney, “Constant Subblock Composition Codes for Simultaneous Energy and Information Transfer,” in Proceedings of the IEEE SECON 2014 Workshop on Energy Harvesting Communications, Singapore, 30 June 2014. 

[47] K. R. Varshney and L. R. Varshney, “Active Odor Cancellation,” in Proceedings of the 2014 IEEE Statistical Signal Processing Workshop (SSP), Jupiters, Gold Coast, Australia, 29 June – 2 July 2014. 

[46] K. R. Varshney and L. R. Varshney, “Food Steganography with Olfactory White,” in Proceedings of the 2014 IEEE Statistical Signal Processing Workshop (SSP), Jupiters, Gold Coast, Australia, 29 June – 2 July 2014. 

[45] A. Sharma, K. Jagannathan, and L. R. Varshney, “Information Overload and Human Priority Queuing,” in Proceedings of the 2014 IEEE International Symposium on Information Theory (ISIT), Honolulu, Hawaii, 29 June – 4 July 2014. 

[44] A. Jagmohan, Y. Li, N. Shao, A. Sheopuri, D. Wang, L. R. Varshney, and P. Huang, “Exploring Application Domains for Computational Creativity,” in Proceedings of the 5th International Conference on Computational Creativity (ICCC), Ljublijana, Slovenia, 10-13 June 2014. 

[43] L. R. Varshney, “Engineering for Problems of Excess,” in Proceedings of the 2014 IEEE International Symposium on Ethics in Engineering, Science, and Technology, Chicago, Illinois, 23-24 May 2014.

[42] A. Tandon, M. Motani, and L. R. Varshney, “On Code Design for Simultaneous Energy and Information Transfer,” in Proceedings of the 2014 Information Theory and its Applications Workshop (ITA), San Diego, 9-14 February 2014. (MM Invited)

[41] L. R. Varshney, A. Vempaty, and P. K. Varshney, “Assuring Privacy and Reliability in Crowdsourcing with Coding,” in Proceedings of the 2014 Information Theory and its Applications Workshop (ITA), San Diego, 9-14 February 2014. (LRV Invited)

[40] A. Vempaty, Y. S. Han, L. R. Varshney, and P. K. Varshney, “Coding Theory for Reliable Signal Processing,” in Proceedings of the 2014 IEEE International Conference on Computing, Networking, and Communications (ICNC), Honolulu, Hawaii, 3-6 February 2014. (YSH Invited)

[39] K. R. Varshney, L. R. Varshney, J. Wang, and D. Meyers, “Flavor Pairing in Medieval European Cuisine: A Study in Cooking with Dirty Data,” in Proceedings of the International Joint Conference on Artificial Intelligence Workshops, Beijing, China, 3 August 2013.

[38] L. R. Varshney, F. Pinel, K. R. Varshney, A. Schörgendorfer, and Y.-M. Chee, “Cognition as a Part of Computational Creativity,” in Proceedings of the 12th IEEE International Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC), New York, New York, 16-18 July 2013.

[37] L. R. Varshney, “To Surprise and Inform,” in Proceedings of the 2013 IEEE International Symposium on Information Theory (ISIT), Istanbul, Turkey, 7-12 July 2013.

[36] L. R. Varshney, “Two Way Communication over Exponential Family Type Channels,” in Proceedings of the 2013 IEEE International Symposium on Information Theory (ISIT), Istanbul, Turkey, 7-12 July 2013.

[35] A. Vempaty, L. R. Varshney, and P. K. Varshney, “Reliable Classification by Unreliable Crowds,” in Proceedings of the 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Vancouver, Canada, 26-31 May 2013.

[34] A. Mani, L. R. Varshney, and A. Pentland, “Quantization Games on Networks,” in Proceedings of the IEEE Data Compression Conference (DCC), Snowbird, Utah, 20-22 March 2013.

[33] L. R. Varshney, “Participation in Crowd Systems,” in Proceedings of the Fiftieth Annual Allerton Conference on Communication, Control, and Computing, Monticello, Illinois, 1-5 October 2012. (LRV Invited)

[32] L. R. Varshney, “Privacy and Reliability in Crowdsourcing Service Delivery,” in Proceedings of the 2012 SRII Global Conference, San Jose, California, 24-27 July 2012. (Best Cross-Enterprise Collaboration Paper Award)

[31] R. Vaculin, Y.-M. Chee, D. V. Oppenheim, and L. R. Varshney, “Work as a Service Meta-model and Protocol for Adjustable Visibility, Coordination, and Control,” in Proceedings of the 2012 SRII Global Conference, San Jose, California, 24-27 July 2012.

[30] L. Limonad, L. R. Varshney, D. V. Oppenheim, E. Fein, P. Soffer, Y. Wand, M. Gavish, and A. Anaby-Tavor, “The WaaSABE Model: Marrying WaaS and Business-Entities to Support Cross-Enterprise Collaboration,” in Proceedings of the 2012 SRII Global Conference, San Jose, California, 24-27 July 2012.

[29] D. V. Oppenheim, Y.-M. Chee, and L. R. Varshney, “Allegro: A Metrics Framework for Globally Distributed Service Delivery,” in Proceedings of the 2012 SRII Global Conference, San Jose, California, 24-27 July 2012.

[28] L. R. Varshney, “On Energy/Information Cross-Layer Architectures,” in Proceedings of the 2012 IEEE International Symposium on Information Theory (ISIT), Cambridge, Massachusetts, 1-6 July 2012.

[27] J. B. Rhim, L. R. Varshney, and V. K. Goyal, “Benefits of Collaboration and Diversity in Teams of Categorically-Thinking Decision Makers,” in Proceedings of the IEEE 7th Sensor Array and Multichannel Signal Processing Workshop (SAM), Hoboken, New Jersey, 17-20 June 2012. (1st Place in Student Paper Contest)

[26] L. R. Varshney, P. Grover, and A. Sahai, “Securing Inductively Coupled Communication,” in Proceedings of the 2012 Information Theory and its Applications Workshop (ITA), San Diego, California, 5-10 February 2012. (LRV Invited)

[25] J. B. Rhim, L. R. Varshney, and V. K. Goyal, “Distributed Decision Making by Categorically-Thinking Agents,” in Proceedings of the NIPS 2011 Workshop on Decision Making with Multiple Imperfect Decision Makers, Sierra Nevada, Spain, 16 December 2011.

[24] L. R. Varshney and D. Shah, “Informational Limits of Neural Circuits,” in Proceedings of the Forty-Ninth Annual Allerton Conference on Communication, Control, and Computing, Monticello, Illinois, 28-30 September 2011.

[23] J. Kusuma, L. R. Varshney, and V. K. Goyal, “Malleable Coding with Fixed Segment Reuse,” in Proceedings of the 2011 IEEE International Symposium on Information Theory (ISIT), St. Petersburg, Russia, 31 July – 5 August 2011.

[22] K. R. Varshney and L. R. Varshney, “Multilevel Minimax Hypothesis Testing,” in Proceedings of the IEEE International Workshop on Statistical Signal Processing (SSP), Nice, France, 28-30 June 2011.

[21] J. B. Rhim, L. R. Varshney, and V. K. Goyal, “Collaboration in Distributed Hypothesis Testing with Quantized Prior Probabilities,” in Proceedings of the IEEE Data Compression Conference (DCC), Snowbird, Utah, 29-31 March 2011.

[20] J. B. Rhim, L. R. Varshney, and V. K. Goyal, “Conflict in Distributed Hypothesis Testing with Quantized Prior Probabilities,” in Proceedings of the IEEE Data Compression Conference (DCC), Snowbird, Utah, 29-31 March 2011.

[19] L. R. Varshney, J. B. Rhim, K. R. Varshney, and V. K. Goyal, “Categorical Decision Making by People, Committees, and Crowds,” in Proceedings of the 2011 Information Theory and its Applications Workshop (ITA), La Jolla, California, 6-11 February 2011. (LRV Invited)

[18] L. R. Varshney and D. V. Oppenheim, “Towards a Stochastic Systems Theory of Coordination,” in Proceedings of the Workshop on Coordination, Collaboration and Ad-hoc Processes (COCOA), Palo Alto, California, 6 December 2010. (LRV Invited)

[17] L. Srinivasan, L. R. Varshney, and J. Kusuma, “Acquisition of Action Potentials with Ultra-Low Sampling Rates,” in Proceedings of the 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Buenos Aires, Argentina, 31 August – 4 September 2010.

[16] L. R. Varshney, “Distributed Inference Networks with Costly Wires,” in Proceedings of the 2010 American Control Conference (ACC), Baltimore, Maryland, 30 June – 2 July 2010.

[15] H. Q. Nguyen, V. K. Goyal, and L. R. Varshney, “Frame Permutation Quantization,” in Proceedings of the Forty-Fourth Annual Conference on Information Sciences and Systems (CISS), Princeton, New Jersey, 17-19 March 2010.

[14] L. R. Varshney, S. K. Mitter, and V. K. Goyal, “Channels That Die,” in Proceedings of the Forty-Seventh Annual Allerton Conference on Communication, Control, and Computing, Monticello, Illinois, 30 September – 2 October 2009.

[13] L. R. Varshney, J. Kusuma, and V. K. Goyal, “Malleable Coding with Edit-Distance Cost,” in Proceedings of the 2009 IEEE International Symposium on Information Theory (ISIT), Seoul, Korea, 28 June – 3 July 2009.

[12] H. Q. Nguyen, V. K. Goyal, and L. R. Varshney, “On Concentric Spherical Codes and Permutation Codes With Multiple Initial Codewords,” in Proceedings of the 2009 IEEE International Symposium on Information Theory (ISIT), Seoul, Korea, 28 June – 3 July 2009.

[11] L. R. Varshney, “Transporting Information and Energy Simultaneously,” in Proceedings of the 2008 IEEE International Symposium on Information Theory (ISIT), Toronto, Canada, 6-11 July 2008.

[10] K. R. Varshney and L. R. Varshney, “Minimum Mean Bayes Risk Error Quantization of Prior Probabilities,” in Proceedings of the 2008 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Las Vegas, Nevada, 30 March – 4 April 2008.

[9] V. Misra, V. K. Goyal, and L. R. Varshney, “High-Resolution Functional Quantization,” in Proceedings of the IEEE Data Compression Conference (DCC), Snowbird, Utah, 25-27 March 2008.

[8] V. Misra, V. K. Goyal, and L. R. Varshney, “High-Resolution Distributed Functional Quantization,” in Proceedings of the 2008 Information Theory and its Applications Workshop (ITA), La Jolla, California, 27 January – 1 February 2008. (VKG Invited)

[7] L. R. Varshney, “Performance of LDPC Codes Under Noisy Message-Passing Decoding,” in Proceedings of the 2007 IEEE Information Theory Workshop (ITW), Lake Tahoe, California, 2-6 September 2007.

[6] L. R. Varshney and D. B. Chklovskii, “On Optimal Information Storage in Synapses,” in Proceedings of the 2007 IEEE Information Theory Workshop (ITW), Lake Tahoe, California, 2-6 September 2007. (LRV Invited)

[5] L. R. Varshney and V. K. Goyal, “On Universal Coding of Unordered Data,” in Proceedings of the 2007 Information Theory and its Applications Workshop (ITA), La Jolla, California, 29 January – 2 February 2007. (VKG Invited)

[4] L. R. Varshney and V. K. Goyal, “Toward a Source Coding Theory for Sets,” in Proceedings of the IEEE Data Compression Conference (DCC), Snowbird, Utah, 28-30 March 2006. (Capocelli Prize)

[3] L. R. Varshney and V. K. Goyal, “Ordered and Disordered Source Coding,” in Proceedings of the Information Theory and its Applications Inaugural Workshop (ITA), La Jolla, California, 6-10 February 2006. (VKG Invited)

[2] L. R. Varshney, “Engineering Theory and Mathematics in the Early Development of Information Theory,” in Proceedings of the 2004 IEEE Conference on the History of Electronics, Bletchley Park, England, 28-30 June 2004. (IEEE Region 1 Student Paper Contest Winner)

[1] L. R. Varshney and D. Thomas, “Sidelobe Reduction for Matched Filter Range Processing,” in Proceedings of the 2003 IEEE Radar Conference, Huntsville, Alabama, 5-8 May 2003. (Best Student Paper Award)

Conference Presentations

[77] O.-H. Kwon, J. Yoon, L. R. Varshney, and H. Yoon, “Suspense and surprise in the book of technology: Understanding innovation dynamics,” presented at International Conference on the Science of Science and Innovation (ICSSI), Copenhagen, Denmark, 16-18 June 2025.

[76] S. Prakash and L. R. Varshney, “Federated Digital Twins,” presented at 2025 Digital Engineering Conference, Idaho Falls, ID, 20-21 May 2025.

[75] X. Wu, A. Hanganu, A. Hoshino, and L. R. Varshney, “Source Organ Prediction for Exosomal Communication,” presented at AAAS Annual Meeting, Boston, MA, 13-15 February 2025.

[74] A. Pattanaik and L. R. Varshney, “Generalized Fenchel-Young Divergence,” presented at 2025 Information Theory and Applications Workshop (ITA), San Diego, CA, 9-14 February 2025.

[73] O.-H. Kwon, J. Yoon, L. R. Varshney, and H. Yoon, “Suspense and surprise in technological innovation,” presented at Thirteenth International Conference on Complex Networks and their Applications, Istanbul, Turkey, 10-12 December 2024.

[72] L. R. Varshney, H. Yu, and H. Ni, “AI-Driven Music Co-Creativity Games,” presented at 3rd International Conference on Playful by Design, Urbana, IL, 7-9 November 2024.

[71] A. O. Deshmukh and L. R. Varshney, “Multi-objective Prompt Optimization for Scientific Discovery at the Information-Theoretic Limit,” presented at AAAI Fall Symposium on Integrated Approaches to Computational Scientific Discovery, Arlington, VA, 7-9 November 2024.

[70] S. Basu, A. Magesh, H. Yadav, and L. R. Varshney, “Autoequivariant Network Search via Group Decomposition,” presented at SIAM Conference on Mathematics of Data Science (MDS24), Atlanta, GA, 21-25 October 2024.

[69] V. Patel, B. Hemmatian, R. Wilcox, J. Wu, L. R. Varshney, and A. Barbey, “Anxiety Predicts Everyday Decision Outcomes Beyond General Intelligence,” presented at Neuroscience 2024: Society for Neuroscience 54th Annual Meeting, Chicago, IL, 5-9 October 2024.

[68] Y. Song, G. D. Pinilla-Monsalve, O. Monchi, L. R. Varshney, A. Hoshino, and A. Hanganu, “Sex-Related Differences in Exosomal Proteins Concentrations throughout Age,” presented at American Geriatrics Society Annual Scientific Meeting, 8-11 May 2024.

[67] R. R. Wilcox, B. Hemmatian, E. D. Anderson, P. Robles-Granda, C. Zwilling, A. Nayak, L. R. Varshney, and A. K. Barbey, “Joint Structure-Function Network Modeling of General Intelligence,” presented at Neuroscience 2023: Society for Neuroscience 53rd Annual Meeting, Program No. PSTR299.01, Washington, D.C., 11-15 November 2023.

[66] M. Choraria, T.-S. Lin, D. Szwarcman, C. Watson, A. Jain, and L. R. Varshney, “Machine Learning Methods for Climate Change,” presented at INFORMS Annual Meeting, Phoenix, AZ, 15-18 October 2023.

[65] I. Ferwana and L. R. Varshney, “Optimal Recovery for Causal Inference,” presented at ACM FCRC Workshop on Causal Inference for Engineers, Orlando, FL, 19 June 2023.

[64] I. Ferwana and L. R. Varshney, “Collision of Scientific Fields,” presented at 2nd Annual International Conference on the Science of Science and Innovation (ICSSI), Evanston, IL, 26-28 June 2023.

[63] I. Ferwana and L. R. Varshney, “Sleeping and Waking of Disruptors,” presented at 2nd Annual International Conference on the Science of Science and Innovation (ICSSI), Evanston, IL, 26-28 June 2023.

[62] B. K. Das, L. R. Varshney, and V. Madhok, “Simultaneous Transfer of Energy and Information through a Quantum Channel,” presented at 26th Conference on Quantum Information Processing (QIP), Ghent, Belgium, 4-10 February 2023.

[61] X. Cheng, T. Mamalis, S. Bose, and L. R. Varshney, “On Carsharing Platforms with Electric Vehicles as Energy Service Providers,” presented at Transportation Research Board (TRB) 102nd Annual Meeting, Washington, DC, 8-12 January 2023.

[60] T.-S. Lin, M. Choraria, C. Watson, L. R. Varshney, and A. Jain, “Accelerated Discovery of Crop Yield Responses to Climate Change by Combining Machine Learning and Process-based Modeling,” presented at AGU Fall Meeting, Chicago, IL, 12-16 December 2022.

[59] X. Ge, H. Yu, R. T. Goodwin, P. Romero, O. Abdelrahman, N. Garg, and L. R. Varshney, “Generative Artificial Intelligence for Accelerated Design and Deployment of Sustainable Concrete,” presented at 26th Annual Green Chemistry & Engineering Conference, Reston, VA, 6-8 June 2022.

[58] S. Basu, D. Seo, and L. R. Varshney, “Hypergraph Source Codes Under Maximal Distortion,” presented at Conference on Information Sciences and Systems (CISS), [Princeton, NJ], 11-13 March 2022.

[57] X. Wu, A. Hanganu, A. Hoshino, and L. R. Varshney, “Organ Source Prediction for Exosomal Proteomics via Protein Language Models,” presented at Learning Meaningful Representations of Life Workshop at NeurIPS 2021, 13 December 2021.

[55] L. R. Varshney, H. V. Kshetry, and N. Kshetry, “Combining Reinforcement Learning with Physics-Based Model Predictive Control for Nutrient Removal in Water Resource Recovery,” presented at New York Scientific Data Summit 2021, 26–29 October 2021.

[54] L. R. Varshney, L. Xie, and S. K. Mitter, “Modularity and Integration in Energy Grids: Data-Driven Definitions, Benefits, and Drawbacks of Energysheds,” presented at New York Scientific Data Summit 2021, 26–29 October 2021.

[53] I. George, X. Chen, and L. R. Varshney, “Limits of Detecting Extraterrestrial Civilizations,” presented at Beyond IID in Information Theory 9 (BIID’9), 27 September – 1 October 2021.

[52] A. Naik, P. Arnold, and L. R. Varshney, “The Representation of Cognitive Decline in Neurodegeneration as Faults in Neural Networks: A Novel Paradigm,” presented at Network Neuroscience Satellite of Networks2021 , [Washington, DC], 30 June – 1 July 2021.

[51] G. S. Ramachandran, I. Brugere, L. R. Varshney, and C. Xiong, “Graph Augmentation for Equitable Access to Networked Resources,” presented at Networked Justice Satellite of Networks2021, [Washington, DC], 28 June 2021.

[50] A. Kafizov, A. Elzanaty, L. R. Varshney, and M.-S. Alouini, “Network Coding in IRS-Aided Butterfly Network,” presented at Wireless World Research Forum, 18-21 January 2021.

[49] C. Bhatia and L. R. Varshney, “Structural Properties of the Ciona intestinalis (L.) Connectome,” presented at SfN Global Connectome, 11-13 January 2021.

[48] L. R. Varshney, “Addressing Difference in Orientation toward Competition by Bringing Fundamental Limits to AI Challenges,” presented at NeurIPS workshop, ML Competitions at the Grassroots (CiML 2020), 11 December 2020.

[47] R. Mehta, D. Somaya, and L. R. Varshney, “Creative AI and Human-AI Team Performance,” presented at 80th Annual Meeting of the Academy of Management, Vancouver, Canada, 7-11 August 2020.

[46] H. Yu, L. R. Varshney, and G. Stein-O’Brien, “Towards Learning Human-Interpretable Laws of Neurogenesis from Single-Cell RNA-Seq Data via Information Lattices,” presented at Learning Meaningful Representations of Life Workshop at NeurIPS 2019, Vancouver, Canada, 13 December 2019.

[45] S. Basu and L. R. Varshney, “Universal and Succinct Source Coding of Deep Neural Networks,” presented at Stanford Compression Workshop 2019, Palo Alto, California, 15 February 2019.

[44] T.-Y. Wu, A. Tandon, L. R. Varshney, and M. Motani, “Multicasting Energy and Information Simultaneously,” presented at 2018 IEEE Information Theory Workshop, Guangzhou, China, 25-29 November 2018.

[43] H. Ito, T. Nishida, L. R. Varshney, and Y. Ishikawa, “Weak Ties in Job Change: Evidence from Business Card Exchange in Japan,” presented at 2018 International Conference on Computational Social Science, Evanston, Illinois, 13-15 July 2018.

[42] M. Kazama, M. Sugimoto, C. Hosokawa, K. Matsushima, L. R. Varshney, and Y. Ishikawa, “A Novel System for Transformation of Regional Cuisine Style,” presented at 2018 International Conference on Computational Social Science, Evanston, Illinois, 13-15 July 2018.

[41] H. Ito, T. Nishida, L. R. Varshney, and Y. Ishikawa, “Weak Ties in Job Change: Evidence from Business Card Exchange in Japan,” presented at NetSci: International School and Conference on Network Science, Paris, France, 11-15 June 2018.

[40] L. R. Varshney, L. Marla, and D. Shah, “Computing Information-Theoretic Limits on Behavioral Speed in C. elegans and Ciona  intestinalis (L.),” presented at Analysis and Interpretation of Connectomes, Janelia Research Campus, Ashburn, Virginia, 20-23 May 2018.

[39] N. Kshetry and L. R. Varshney, “Optimal Wastewater Management Using Advanced Analytics,” presented at 2018 Illinois Wastewater Professionals Conference, Springfield, 16-18 April 2018.

[38] L. R. Varshney and K. R. Varshney, “Decision Making With Quantized Priors Leads to Discrimination,” presented at Illinois Summit on Diversity in Psychological Science, Champaign, 26-28 March 2018.

[37] T.-Y. Wu, A. Tandon, L. R. Varshney, and M. Motani, “On Skip Sliding Window Codes,” presented at 2018 Information Theory and its Applications Workshop (ITA), San Diego, California, 11-16 February 2018.

[36] A. Chatterjee and L. R. Varshney, “Optimal Energy Allocation in Reliable Neural Sensory Processing,” presented at Inaugural Conference on Cognitive Computational Neuroscience (CCN), New York, New York, 6-8 September 2017. 

[35] A. Vempaty, L. R. Varshney, and P. K. Varshney, “A Coupon-Collector Model of Machine-Aided Discovery,” presented at KDD Workshop on Data-Driven Discovery, Halifax, Canada, 14 August 2017.

[34] X. Ge, J. Xiong, and L. R. Varshney, “CELA: Creating Experiential Learning Activities,” presented at International Conference on Computational Creativity, Atlanta, Georgia, 19-23 June 2017.

[33] A. D. Patil, N. R. Shanbhag, L. R. Varshney, E. Pop, H.-S. P. Wong, S. Mitra, J. Rabaey, J. Weldon, L. Pileggi, S. Manipatruni, D. Nikonov, and I. A. Young, “A Systems Approach to Computing in Beyond CMOS Fabrics,” presented at Design Automation Conference (DAC 2017), Austin, Texas, 18-22 June 2017.

[32] A. Sarathy, J.-P. Leburton, and L. R. Varshney, “On Nanopore Sequencing of the Epigenome in the Presence of Noise,” presented at 15th Canadian Workshop on Information Theory, Quebec City, Canada, 11-14 June 2017.

[31] M. Jere, R. K. Raman, and L. R. Varshney, “The Eurekometric Connectome: Discovering Unexplored Areas of Neuroscience Research,” presented at NetSci: International School and Conference on Network Science, Indianapolis, Indiana, 19-23 June 2017.

[30] D. Bhattacharjya and L. R. Varshney, “Multiattribute Preference Models for Computational Creativity,” presented at INFORMS Annual Meeting, Nashville, Tennessee, 13-16 November 2016.

[29] A. Chatterjee and L. R. Varshney, “The Role of Information Theory and Queuing Theory in Human Computation Systems,” presented at HCOMP 2016 Workshop on Mathematical Foundations of Human Computation, 3 November 2016.

[28] N. Kshetry and L. R. Varshney, “Foodsheds in Virtual Water Flow Networks: A Spectral Graph Theory Approach,” presented at Food and Data Workshop: Interoperability through the Food Pipeline, 12-13 September 2016.

[27] L. Chang and L. R. Varshney, “World Culture of Food Texture Networks,” presented at Food and Data Workshop: Interoperability through the Food Pipeline, 12-13 September 2016.

[26] A. J. Gross, D. Murthy, and L. R. Varshney, “Pace of Life in Cities and the Emergence of Town Tweeters,” presented at 66th Annual Conference of the International Communication Association (ICA), Fukuoka, Japan, 9-13 June 2016.

[25] Z. He and L. R. Varshney, “Inducement Prizes in Data Science: Specialization, Community, and National Performance,” presented at International Symposium on Science of Science, Washington, DC, 22-23 March 2016.

[24] A. Tandon, M. Motani, and L. R. Varshney, “Coding for Constrained Communication Systems,” presented at Information Theory and its Applications Workshop (ITA), San Diego, California, 31 January – 5 February 2016.

[23] I. Lobel, E. Sadler, and L. R. Varshney, “Customer Referral Incentives and Social Media,” presented at 16th ACM Conference on Economics and Computation (EC 2015), Portland, Oregon, 15-19 June 2015.

[22] A. J. Gross, D. Murthy, and L. R. Varshney, “Pace of Life in Cities and the Emergence of Town Tweeters,” presented at International Conference on Computational Social Science (IC2S2), Helsinki, Finland, 8-11 June 2015.

[21] L. R. Varshney, “Are there Informational Limits to Creativity?,” presented at Information Theory and its Applications Workshop (ITA), San Diego, California, 1-6 February 2015. (LRV Invited)

[20] L. R. Varshney, “Block Diagrams in Information Theory: Drawing Things Closed,” presented at SHOT Special Interest Group on Computers, Information, and Society Workshop 2014, Dearborn, Michigan, 9 November 2014.

[19] E. Sadler, I. Lobel, and L. R. Varshney, “Customer Referral Incentives and Social Media,” presented at INFORMS Annual Meeting, San Francisco, California, 9-12 November 2014.

[18] N. Shao, K. R. Varshney, L. R. Varshney, and F. Pinel, “Personalization of Product Novelty Assessment via Bayesian Surprise,” presented at 2014 Joint Statistical Meetings (JSM), Boston, Massachusetts, 2-7 August 2014.

[17] A. Vempaty, L. R. Varshney, and P. K. Varshney, “Error-Correcting Codes allow Privacy and Quality Assurance in Crowdsourcing,” presented at CrowdConf 2013, San Francisco, California, 22 October 2013.

[16] F. Pinel, L. R. Varshney, and L. Tounsi, “Information in Networks as Inspiration: Value for Culinary Computational Creativity,” presented at Workshop on Information in Networks (WIN), New York, New York, 4-5 October 2013.

[15] L. R. Varshney, “Fundamental Limits of Data Analytics for Sequential Selection,” presented at 2013 Information Theory and its Applications Workshop (ITA), San Diego, California, 10-15 February 2013. (LRV Invited)

[14] A. Mani, L. R. Varshney, and A. Pentland, “Focal Vocabularies vs. Shared Vocabularies in Social Networks: Balancing Individual Concerns and Social Exchange,” presented at Interdisciplinary Workshop on Information and Decision in Social Networks (WIDS), Cambridge, Massachusetts, 8-9 November 2012.

[13] L. R. Varshney, “Directed Acyclic Motifs for Conversation Analytics,” presented at Interdisciplinary Workshop on Information and Decision in Social Networks (WIDS), Cambridge, Massachusetts, 8-9 November 2012.

[12] D. Bhattacharjya, L. R. Varshney, F. Pinel, and Y.-M. Chee, “Computational Creativity: A Two-attribute Search Technique,” presented at INFORMS Annual Meeting, Phoenix, Arizona, 14-17 October 2012.

[11] A. Wein, J. Kusuma, L. R. Varshney, A. Richardson, and L. Srinivasan, “A Path towards Robust Sub-Nyquist Spike Acquisition for Neuroscience Applications,” presented at 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, San Diego, California, 28 August – 1 September 2012.

[10] R. Williams, W. M. Gifford, and L. R. Varshney, “Using Statistical Algorithms to Predict Abuse against Children and Prioritize Cases,” presented at 18th National Conference on Child Abuse and Neglect, Washington, DC, 16-20 April 2012.

[9] A. K. Fletcher, S. Rangan, L. R. Varshney, and A. Bhargava, “Neural Connectivity and Receptive Field Estimation via Hybrid Message Passing,” presented at 2012 Information Theory and its Applications Workshop (ITA), San Diego, California, 5-10 February 2012.

[8] L. Srinivasan, L. R. Varshney, and J. Kusuma, “Spike Acquisition at Ultra-Low Sampling Rates for Neuroprosthetic Devices,” presented at Neuroscience 2010: Society for Neuroscience 40th Annual Meeting, Program No. 20.13, San Diego, California, 13-17 November 2010.

[7] L. R. Varshney, “Communication with Unreliable Receivers,” presented at 2010 Information Theory and its Applications Workshop (ITA), La Jolla, California, 1-5 February 2010.

[6] V. Misra, V. K. Goyal, and L. R. Varshney, “Distributed Functional Scalar Quantization with Limited Encoder Interaction,” presented at 2009 Information Theory and its Applications Workshop (ITA), La Jolla, California, 8-13 February 2009. (VKG Invited)

[5] L. R. Varshney, “Meeting Shannon: Information-Theoretic Thinking in Engineering and Science,” presented at 2008 IEEE Information Theory Workshop (ITW), Porto, Portugal, 5-9 May 2008. (LRV Invited)

[4] L. R. Varshney, P. J. Sjöström, and D. B. Chklovskii, “Optimal Information Storage in Noisy Synapses,” presented at 2006 Cold Spring Harbor Laboratory Meeting on Channels, Receptors & Synapses, Cold Spring Harbor, New York, 18-22 April 2006.

[3] D. B. Chklovskii and L. R. Varshney, “Noisy Synapses and Information Storage,” presented at Neuroscience 2005: Society for Neuroscience 35th Annual Meeting, Program No. 965.17, Washington, D.C., 12-16 November 2005.

[2] L. R. Varshney and D. B. Chklovskii, “Reliability and Information Storage Capacity of Synapses,” presented at 2005 Cold Spring Harbor Laboratory Meeting on Learning & Memory, Cold Spring Harbor, New York, 20-24 April 2005.

[1] L. R. Varshney and S. D. Servetto, “A Distributed Transmitter for the Sensor Reachback Problem based on Radar Signals,” presented at NSF-RPI Workshop on Pervasive Computing and Networking, Troy, New York, 29-30 April 2004.

Invited Festschrift Contributions

[1] L. R. Varshney, “Mathematization and Novel Systems,” in Glimpses of Systems Theory and Novel Applications, H. S. Sekhon, et al., Eds. Aligarh, India: Systems Society of India Punjab Chapter, 2005, pp. 144-148.

M.S. and Ph.D. Theses

[11] S. Spencer, “Rumor Source Identification, Contagion Processes, and Dynamics of Social Network Formation and Evolution,” Ph.D. dissertation, University of Illinois at Urbana-Champaign, Urbana, IL, Dec. 2020.

[10] S. Basu, “Universal and Succinct Source Coding of Deep Neural Networks,” M.S. thesis, University of Illinois at Urbana-Champaign, Urbana, IL, May 2020.

[9] H. Zhou, “Algorithms on Graph-Structured Data with Imperfect Information,” M.S. thesis, University of Illinois at Urbana-Champaign, Urbana, IL, Aug. 2019.

[8] D. Seo, “Information-Theoretic Analysis of Human-Machine Mixed Systems,” Ph.D. dissertation, University of Illinois at Urbana-Champaign, Urbana, IL, Aug. 2019.

[7] H. Yu, “Automatic Concept Learning via Information Lattices,” Ph.D. dissertation, University of Illinois at Urbana-Champaign, Urbana, IL, May 2019.

[6] R. K. Raman, “On the Information Theory of Clustering, Registration, and Blockchains,” Ph.D. dissertation, University of Illinois at Urbana-Champaign, Urbana, IL, May 2019.

[5] R. Chen, “Missing Values Imputation and Image Registration for Genetics Applications,” M.S. thesis, University of Illinois at Urbana-Champaign, Urbana, IL, May 2019.

[4] S. Agarwal, “A Study on Creativity: Detection and Network Structures,” M.S. thesis, University of Illinois at Urbana-Champaign, Urbana, IL, May 2019.

[3] R. Zhuang, “Science of Science: Biological Research Network,” M.S. thesis, University of Illinois at Urbana-Champaign, Urbana, IL, May 2019.

[2] X. Ge, “Computational Creativity Applications in Engineering,” M.S. thesis, University of Illinois at Urbana-Champaign, Urbana, IL, Dec. 2018. 

[1] L. Chang, “Changing Edges in Graphical Model Algorithms,” M.S. thesis, University of Illinois at Urbana-Champaign, Urbana, IL, Dec. 2016. 

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