His current research interests are in stochastic computing, low power and error resilient computer systems, and architectures for inference and machine learning. His past research on single-ISA heterogeneous multi-core architecture and conjoined-core architectures has directly influenced processor products and roadmaps from several companies. His research recognitions include several best paper awards and best paper award nominations, ARO Young Investigator Award, Arnold O Beckman Research Award, FAA Creative Research Award, UCSD CSE Best Dissertation Award, and an IBM PhD Fellowship. Teaching recognitions include appearance on UIUC's List of Teachers Ranked as Excellent. Advising recognitions include Engineering Council Outstanding Advisor Award. Rakesh has a BS from IIT Kharagpur and a PhD from University of California at San Diego.