Jaijeet Roychowdhury
Micro/Nano Electro Mechanical Systems
University of California, Berkeley (UCB)
United States of America
Biography
Jaijeet Roychowdhury is a Professor of EECS at the University of California at Berkeley. His research interests include machine learning, novel computational paradigms, and the analysis, simulation, verification and design of cyber-physical, electronic, biological, nanoscale and mixed-domain systems. Contributions his group has made include the concept of self-sustaining oscillators for Ising-based and von Neumann computation, novel machine-learning techniques for dynamical systems, theory and techniques for oscillator phase macromodels, injection locking and phase noise, multi-time partial differential equations, techniques for model reduction of time-varying and nonlinear systems, and open-source infrastructures for reproducible research.
Research Interest
Artificial Intelligence (AI) Design, Modeling and Analysis (DMA) Computer Architecture & Engineering (ARC) Control, Intelligent Systems, and Robotics (CIR)
