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.
- mgord@cs.stanford.edu
- Gates 360
- Curriculum vitae
Highlights
Mitchell L. Gordon, Michelle Lam, Joon Sung Park, Kayur Patel, Jeffrey T. Hancock, Tatsunori Hashimoto, Michael S. Bernstein. CHI 2022
Best Paper award (1% of submissions)
Mitchell L. Gordon, Kaitlyn Zhou, Kayur Patel, Tatsunori Hashimoto, Michael Bernstein. CHI 2021
Mitchell L. Gordon*, Sharon Zhou*, Ranjay Krishna, Austin Narcomey, Li Fei-Fei, Michael Bernstein. NeurIPS 2019
Oral (0.5% of submissions)
*equal contribution
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 |