A bit about me —
I’m a recent Stanford alum (when it comes to my MA; dropout when it comes to my PhD!) now working on EveryMeal, an early-stage food automation startup. At Stanford, I worked on various subfields of AI and machine learning, initially with a focus on educational technology. My research interests have included natural language processing and generative models.
Before Stanford, I was an Associate Product Manager at Google, a consultant in data science and product management, and a software engineer. I went to college at UChicago, where I earned a BS and MS in computer science (AI specialization) and a minor in statistics.
Outside of work, I enjoy climbing, skiing, tennis, sailing, reading and playing music.
- The Case for White-Collar Apprenticeships
- The Importance of India
- What Can AI Really Do?
- A bird’s-eye view of modern AI from NeurIPS 2019
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- Y. Alex Kolchinski*, Sharon Zhou*, Shengjia Zhao, Mitchell Gordon, Stefano Ermon. Approximating Human Judgment of Generated Image Quality. Shared Visual Representations in Human and Machine Intelligence workshop at NeurIPS 2019.
- Y. Alex Kolchinski, Christopher Potts. Representing Social Media Users for Sarcasm Detection. Empirical Methods in Natural Language Processing (EMNLP), 2018.
- Y. Alex Kolchinski*, Sherry Ruan*, Dan Schwartz, Emma Brunskill. Adaptive natural-language targeting for student feedback. WIP Learning at Scale (LAS), 2018.