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University of Illinois
Coordinated Science Laboratory
Grainger College of Engineering
Center for Advanced Electronics through Machine Learning (CAEML)
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Research
Modular Machine Learning for Behavioral Modeling of Microelectronic Circuits and Systems
High-Dimensional Structural Inference for Non-Linear Deep Markov or State Space Time Series Models
Applying Machine Learning to Back End IC Design
NL2PPA: Netlist‐to‐PPA Prediction Using Machine Learning
Fast, Accurate PPA Model‐Extraction
Design Space Exploration Using DNN
High-Speed Bus Physical Design Analysis through Machine Learning
RNN Models for Computationally‐Efficient Simulation of Circuit Aging Including Stochastic Effects
Machine Learning for Trusted Platform Design
Enabling Side‐Channel Attacks on Post‐Quantum Protocols through Machine Learning
Completed Projects
Models to Enable System-level Electrostatic Discharge Analysis
Design Rule Checking with Deep Networks
Intellectual Property Reuse through Machine Learning
Causal Inference for Early Detection of Hardware Failure
Optimization of Power Delivery Networks for Maximizing Signal Integrity
Machine Learning to Predict Successful FPGA Compilation Strategy
Behavioral Model Development for High-Speed Links
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