Jun-Ting (Tim) Hsieh

PhD student, Carnegie Mellon University
juntingh [at] cs [dot] cmu [dot] edu
Github / Google scholar

About me

I am a PhD student in the Computer Science department at Carnegie Mellon University. I am fortunate to be advised by Pravesh Kothari. I am interested in theoretical computer science in general. Recently, I am focusing on the problem of trace reconstruction.

In the past, I have worked on artificial intelligence and machine learning. I did my undergraduate and masters at Stanford University, where I worked with Fei-Fei Li and Juan Carlos Niebles on computer vision and with Stefano Ermon on machine learning. I'd like to thank Li-Yang Tan at Stanford for sparking my interest in theoretical computer science.

I am also very interested in physics and natural sciences in general. Check out my projects in Quantum Complexity (pdf) and Quantum Information (pdf). I have also worked with Prof. Jr-Min Lin on measuring the reaction rates of chemicals related to atmospheric ozone, which was later published in Science, 2015.


Stanford University
Sep. 2017 - Mar. 2019
M.S. in Computer Science

Stanford University
Sep. 2013 - Jun. 2017
B.S. in Computer Science
Terman Award Winner, University Distinction


Artificial Intelligence & Machine Learning

Learning Neural PDE Solvers with Convergence Guarantees
Jun-Ting Hsieh*, Shengjia Zhao*, Stephan Eismann, Lucia Mirabella, Stefano Ermon
International Conference on Learning Representations (ICLR), 2019

Learning to Decompose and Disentangle Representations for Video Prediction
Jun-Ting Hsieh, Bingbin Liu, De-An Huang, Li Fei-Fei, Juan Carlos Niebles
Neural Information Processing Systems (NeurIPS), 2018
Paper Code

Graph Distillation for Action Detection with Privileged Modalities
Zelun Luo, Jun-Ting Hsieh, Lu Jiang, Juan Carlos Niebles, Li Fei-Fei
European Conference on Computer Vision (ECCV), 2018
Paper Project Code

AI-Assisted Healthcare

Computer Vision-based Descriptive Analytics of Seniors' Daily Activities for Long-term Health Monitoring
Jun-Ting Hsieh*, Zelun Luo*, Niranjan Balachandar, Serena Yeung, Guido Pusiol, Jay Luxenberg, Grace Li, Li-Jia Li, N. Lance Downing, Arnold Milstein, Li Fei-Fei
Machine Learning for Healthcare (MLHC), 2018

Physical Chemistry

Direct kinetic measurement of the reaction of the simplest Criegee intermediate with water vapor
Wen Chao, Jun-Ting Hsieh, Chun-Hung Chang, Jim Jr-Min Lin
Science, 2015. Vol. 347, Issue 6223, pp. 751-754


  • Frederick Emmons Terman Engineering Scholastic Award 2017
  • Phi Beta Kappa Honor Society Member 2017
  • Stanford President’s Award for Academic Excellence in the Freshman Year 2014
  • Gold Medalist at International Physics Olympiad (IPhO), 8th overall 2012
  • Gold Medalist at Asian Physics Olympiad (APhO), 10th overall 2012