Jing Yu Koh
jingyuk@cs.cmu.edu
I am a first year PhD student in the Machine Learning Department at Carnegie Mellon University. I am advised by Daniel Fried and Ruslan Salakhutdinov. I work on grounded language understanding, usually in the context of vision-and-language problems.
Prior to this, I was a Research Engineer (and previously an AI Resident) at Google Research, where I worked on vision-and-language problems and generative models. I completed my undergraduate studies at the Singapore University of Technology and Design summa cum laude (highest honors) in 2019.
My first name is "Jing Yu" and informally I go by the nickname "JY". I'm from Singapore.

News
- (Apr 2023) 1 paper accepted to ICML 2023!
- (Spring 2023) Gave invited talks at Microsoft Research, Apple AI/ML, Georgia Tech, and the London ML Meetup (recording, slides).
- (Dec 2022) I made a bet on LLM capabilities with my office mate Ben Chugg. Bubble tea is on the line.
- (Nov 2022) Parti was accepted to TMLR with a Featured Certification!
- (Oct 2022) In the spirit of paying it forward, I'm sharing my Statement of Purpose publicly. Hope it helps future applicants!
- (Jul 2022) After 2.73 wonderful years at Google, I've left to pursue my PhD at Carnegie Mellon University!
- (January 2022) 1 paper accepted to ICLR 2022!
- (December 2021) Serving as a reviewer for CVPR 2022.
- (July 2021) 1 paper accepted to ICCV 2021!
- (July 2021) Presenting an invited talk at Microsoft Research.
- (July 2021) Serving as a reviewer for NeurIPS 2021.
- (March 2021) 1 paper accepted to CVPR 2021!
- (January 2021) 1 paper accepted to ICLR 2021!
- (October 2020) 1 paper accepted to WACV 2021!
- (July 2020) 1 paper accepted to ECCV 2020!
- (October 2019) Officially joined Google as an AI Resident in Mountain View, California.
Selected Publications [Google Scholar]
2023

Grounding Language Models to Images for Multimodal Inputs and Outputs
To appear in The International Conference on Machine Learning (ICML), 2023.
2022
2021

Vector-quantized Image Modeling with Improved VQGAN
In The International Conference on Learning Representations (ICLR), 2022.