Our group aims to find fundamental limits, optimal designs, and principled practical implementations of information systems, often by pushing mathematical tools from information theory, signal processing, queuing, and learning theory in new directions. We also analyze extant sociotechnical information systems through network science and data science. A major current focus is on augmenting individual and collective intelligence by understanding computation in various forms: artificial intelligence, collective intelligence, nanoscale information processing, neural computation, blockchain, and computational creativity.
Broadly we are interested in improving health, welfare, and happiness in society. As such, we maintain bodies of work in several application domains including the food pipeline, public health, education, epigenetics, and materials discovery.
The group is led by Lav Varshney.