Alvin Wan[at]

AI PhD student UC Berkeley

Website Google Scholar Github CV

My research produces compact1 computer vision models for applications like virtual reality2 and self-driving cars3. 1. Efficient Machine Learning by a combination of manual design, using domain knowledge, and neural architecture search methods to produce state-of-the-art models.
2. Facebook Reality Labs research from May 2019 to March 2021, under Peizhao Zhang, Peter Vajda. FBNets deployed to Oculus, Portal, Instagram, and more.
3. Tesla AutoPilot research from March 2021 to July 2021, under Andrej Karpathy

I’m advised by Joseph E. Gonzalez and participate in RISELab, BAIR, and Berkeley Deep Drive. I received my B.S. ('18) in EECS from UC Berkeley.


  • NSF GRFP Fellowship (2018)
  • UC Berkeley Undergraduate Research Fellowship (2017)


  • Principles and Techniques of Data Science: Co-Instructor (Fa '21)
  • Teaching Techniques for Computer Science: Co-Instructor (Su '21)
  • Machine Learning: Head TA (Fall '19, Spring '18, Fall '17); TA (Spring '17)
  • Discrete Mathematics and Probability Theory: Head TA (Spring '16, Fall '16, Spring '17)
  • Introductory Computer Science: TA (Fall '15)

External Talks

  • Facebook Workshop on Neural Architecture Search (April '20)
  • Amazon Graduate Research Symposium (March '19)