Kwan Ho Ryan Chan

Making predictions one explanation at a time.

KwanHoRyanChan_Headshot.jpg

I am a third-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 am a Machine Learning Intern at Apple in 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

May 06, 2024 Starting as a Machine Learning 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!