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I am a post-doc at Carnegie Mellon University advised by Zico Kolter. My work focuses on safe and secure ML as well as reasoning in AI systems.
In 2023, I finished my Ph.D. in the Applied Math and Scientific Computation program at the University of Maryland. I was advised by Tom Goldstein on my work in deep learning. My research during my PhD spanned from security to generalization and broadly focused on expanding our understanding of when and why neural networks work. My specific interest in data security and model vulnerability has led to work on adversarial attacks and data poisoning. I also studied neural networks' ability to extrapolate from easy training tasks to more difficult problems at test time.
From June 2022 through March 2023, I was a researcher at Arthur AI in New York City. And before starting at UMD, I received a master's degree in applied math at the University of Washington and a bachelor's degree in applied math at Columbia Engineering.