About

Hi, I'm Dylan! I'm a second year PhD student in the Machine Learning Department at CMU, where I am fortunate to be advised by Zico Kolter. My research interests are in developing machine learning and deep learning algorithms in settings with limited labeled data. This broadly includes semi-supervised learning, representation learning, adapting pre-trained/foundation models, weak supervision, and out-of-distribution generalization.

Before, I studied math and computer science at Brown University, where I was advised by Stephen Bach. I was also very fortunate to collaborate with Eli Upfal and Brenda Rubenstein. In the past, I served as a research intern at Amazon AWS, 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 form new collaborations!

News

• [Jan 2023]: Our paper on label propagation with weak supervision is accepted to ICLR 2023!
• [Dec 2022]: I presented my summer internship work @ Amazon at the NeurIPS 2022 SSL workshop!
• [Nov 2022]: Our paper "Losses over Labels: Weak Supervision via Direct Loss Construction" is accepted to AAAI 2023!
• [Sep 2022]: I'm visiting Germany for the 9th Heidleberg Laureate Forum, as a PhD scholar!
• [May 2022]: Spent the summer as an applied scientist intern at Amazon AWS in the Santa Clara office, working on self-supervised learning!
• [Aug 2021]: Started my PhD in the Machine Learning Department @ CMU!
• [May 2021]: Our work on performance-guarantees for an adversarial multi class learning with weak supervision is accepted to ICML 2021.
• [Dec 2020]: I was selected as an honorable mention for the 2021 CRA Outstanding Undergraduate Researcher Award!