Sunnie S. Y. Kim
I’m a first-year CS PhD student at Princeton University working with Prof. Olga Russakovsky in the Princeton Visual AI Lab. I’m interested in computer vision and machine learning, especially in the space of fairness and interpretabilty.
Previously, I was at Yale University where I received a B.S. degree in Statistics and Data Science and worked with Prof. John Lafferty on projects in generative models and computational neuroscience in the Yale Statistical Machine Learning Group. I also worked on various environmental data analytics projects with Prof. Jay Emerson. After graduation, I spent a year at Toyota Technological Institute at Chicago as a visiting student doing computer vision and machine learning research with Prof. Greg Shakhnarovich.
My go-to hobby is watching tv (to be honest😊) but I also like reading Korean books and trying out different coffee & wine. Sometimes when I feel like I need more physical activity in my life, I play tennis and take long walks.
Jan 2021: A Shallow Artificial Neural Network Recovers Structure of Visual Loom-Selective Neurons by Baohua Zhou, Zifan Li, me, John Lafferty, and Damon Clark has been accepted to Cosyne 2021!
Dec 2020: Another preprint: Information-Theoretic Segmentation by Inpainting Error Maximization by Pedro Savarese, me, Michael Maire, Greg Shakhnarovich, and David McAllester.
Dec 2020: New paper on arXiv! Check out Fair Attribute Classification through Latent Space De-biasing by Vikram V. Ramaswamy, me, and Olga Russakovsky.
Nov 2020: Gave a short guest lecture on image synthesis in Princeton’s undergraduate computer vision course.
Sep 2020: Gave a talk on Deformable Style Transfer at Princeton PIXL lunch talks.
Aug 2020: Started my PhD at Princeton University!
Aug 2020: Attended ECCV 2020 and presented Deformable Style Transfer by me, Nicholas Kolkin, Jason Salavon, and Greg Shakhnarovich at the main conference and the WiCV workshop.
July 2020: Wrapped up my time at TTIC as a visiting student. The year went by very quickly. I’ll especially miss the Perception and Learning Systems group, the 2019-2020 cohort friends, and the Girls Who Code team!