Philip Brisk

Professor, University of California, Riverside

Dr. Brisk's interests span all aspects of computer system design, including but not limited to computer architecture, FPGAs and reconfigurable computing, electronic design automation, and VLSI. Like every subfield of computing, machine learning, and deep neural networks in particular, have become the primary target of interest, as well as the underlying methodology of choice. He has also branched out into emerging technologies, including programmable microfluidics, DNA-based models of computation, and processing-in-memory.


  • Machine Learning
  • Data Mining
  • Computer Systems
  • Applied Science