Mitchell is a computer science PhD student at Stanford University in the HCI group, advised by Michael Bernstein and James Landay. He designs interactive systems and evaluation approaches that bridge principles of human-computer interaction with the realities of statistical machine learning.

His work has won awards at top conferences in human-computer interaction and artificial intelligence, including a Best Paper award at CHI and an Oral at NeurIPS. He is supported by an Apple PhD Fellowship in AI/ML. Mitchell has interned at Apple, Google, and CMU HCII, and holds a bachelor’s degree in computer science from the University of Rochester, where he was advised by Philip Guo and Jeffrey Bigham.

Highlights

Latest News

  • Jury learning wins a Best Paper award at CHI 2022
  • I passed my dissertation proposal
  • Presenting the disagreement deconvolution at CHI 2021
  • Excited and honored to be an Apple PhD Fellow in AI/ML
  • Named a finalist for the Facebook Fellowship
  • HYPE accepted to NeurIPS 2019 as an oral (top 0.5%)

Upcoming Travel

May 1–5, '22 CHI, New Orleans