Kwan Ho Ryan Chan
Making predictions one explanation at a time.
I am on the lookout for Summer 2025 internships! Click here for my resume.
I am a fourth-year Electrical and Systems Engineering PhD student at University of Pennsylvania, supervised by Prof. René Vidal. I am supported by Penn Dean’s Fellowship and NSF Graduate Research Fellowship. I was an AI/ML Intern at Apple’s Health AI team in Seattle for Summer 2024. I received my BA in Applied Mathematics from University of California, Berkeley and was advised by Prof. Yi Ma. Before starting my PhD, I was a machine learning researcher at Lawrence Livermore National Lab.
My research interests center on the development of trustworthy machine learning systems. From small-scale medical problems to large-scale multi-modal challenges, the goal is to not only understand modern deep learning on both theoretical and practical fronts, but also ensure they are implementable, accessible, and intuitive to those who rely on such systems. To achieve this, I build frameworks and algorithms that impose well-structured assumptions about the data, make use of interpretable features, and generate human-aligned explanations.
Feel free to contact me for potential collaborations and discussions.
Email: ryanckh (at) seas (d0t) upenn (d0t) edu Github: @ryanchankh Linkedin: /in/ryanchankh X: @ryanchankh Google Scholar: Click Here. |
News
Sep 28, 2024 | Our work “PaCE: Parsimonious Concept Engineering for Large Language Models” has been accpeted to NeurIPS 2024! |
---|---|
May 06, 2024 | Starting as an AIML Intern at Apple’s Health AI team in Seattle for Summer 2024. Say Hi if you are in the area! :) |
Mar 11, 2024 | Renovated my personal website! |
Jan 16, 2024 | Our work “Bootstrapping Variational Information Pursuit with Foundation Models for Interpretable Image Classification” has been accpeted to ICLR 2024! |