Bio


Chris Gregg received his Ph.D. in Computer Engineering from the University of Virginia in 2012, has a Master's of Education from Harvard University (2002), and a BS in Electrical Engineering from Johns Hopkins University (1994). Prior to becoming a lecturer at Stanford, Chris was a lecturer in the computer science department at Tufts University, and prior to that he taught high school physics in Massachusetts and California for seven years. Chris was on active duty in the Navy for seven years, and remains as a Commander in the Navy Reserves in the Information Warfare / Cryptology community.

Chris's research interests include computer architecture (specifically, general purpose computing on GPUs) and the pedagogy of computer science teaching and instruction.

Academic Appointments


Boards, Advisory Committees, Professional Organizations


  • Member, Association of Computing Machinery (2009 - Present)
  • Member, Institute of Electrical and Electronics Engineers (1990 - Present)

Professional Education


  • Ph.D., University of Virginia, Computer Engineering (2012)
  • M.Ed., Harvard University, Education (Physics) (2002)
  • B.S., Johns Hopkins University, Electrical Engineering (1994)

2024-25 Courses


All Publications


  • Datacenter-Scale Analysis and Optimization of GPU Machine Learning Workloads IEEE MICRO Wesolowski, L., Acun, B., Andrei, V., Aziz, A., Dankel, G., Gregg, C., Meng, X., Meurillon, C., Sheahan, D., Tian, L., Yang, J., Yu, P., Hazelwood, K. 2021; 41 (5): 101-112
  • How Do We Provide Effective Student Advising and Mentoring During Record Growth? Gregg, C., Hescott, B., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2018: 1069
  • How Do You Teach Debugging?: Resources and Strategies for Better Student Debugging Special Interest Group on Computer Science Education (SIGCSE) Lewis, C. M., Gregg, C. 2016

    View details for DOI 10.1145/2839509.2850473

  • Working with Undergraduate Teaching Assistants: Best Practices and Lessons Learned Special Interest Group on Computer Science Education (SIGCSE) Gregg, C., Lewis, C. M. 2015

    View details for DOI 10.1145/2676723.2691864

  • Fine-Grained Resource Sharing for Concurrent GPGPU Kernels 4th USENIX Workshop on Hot Topics in Parallelism (HOTPAR) Gregg, C., Dorn, J., Skadron, K., Hazelwood, K. 2012