Hi, I'm Dylan! I'm a PhD student in the Machine Learning Department at CMU, where I am advised by Zico Kolter. My research interests are in developing machine learning and deep learning algorithms, especially in settings with limited labeled data. I am also interested in weak supervision, representation learning, 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!
- [Nov 2022]: Our paper "Losses over Labels: Weak Supervision via Direct Loss Construction" was accepted to AAAI 2023! The paper will be released soon :)
- [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.
- [Feb 2021]: Our paper "Semi-Supervised Aggregation of Dependent Weak Supervision Sources with Performance Guarantees" was accepted to AISTATS 2021.
- [Dec 2020]: I was selected as an honorable mention for the 2021 CRA Outstanding Undergraduate Researcher Award!