About

Hi, I'm Dylan! I'm a fourth year PhD student in the Machine Learning Department at CMU, where I am fortunate to be advised by Zico Kolter. I'm also student researcher at Google Research. My work is supported by a NSF Graduate Research Fellowship and an ARCS Scholarship.

I'm broadly interested in making large frontier models behave in ways that we expect. Recently, this has invovled creating safe large language models and curating better training data. In the past, this has invovled studying the behavior and generalization of deep learning models and their interactions with weak supervision and interpretable domain knowledge.

Before, I studied math and computer science at Brown University, where I was advised by Stephen Bach. In the past, I served as a research intern at Amazon AWS, the Bosch Center for AI, MIT, and NASA JPL. Outside of my studies and research, I enjoy playing tennis and am an avid soccer player/fan. If you are interested in my work, feel free to get in touch. I am always looking to chat about research and form new collaborations!

News

• [May 2024]: Spending the summer at Google Research in NYC, where I'll be working on data curation for LLM pretraining.
• [Apr 2024]: I'll be traveling to AISTATS to present "Auditing Fairness under Unobserved Confounding" and to ICLR to present work on providing generalization bounds for prompt engineering VLMs.
• [Sep 2023]: Our work on analyzing the benefits of explanations/prior knowledge from a learning theoretic perspective is accepted to NeurIPS 2023!
• [Jan 2023]: Our paper on label propagation with weak supervision is accepted to ICLR 2023!
• [Sep 2022]: I'm visiting Germany for the 9th Heidleberg Laureate Forum, as a PhD scholar!
• [May 2022]: Spending the summer as an AWS applied scientist intern in Santa Clara!
• [Aug 2021]: Started my PhD in the Machine Learning Department @ CMU!