Wayne Chi

Computer Science Ph.D. Student at Carnegie Mellon University
Previously, Applied Scientist at Amazon and NASA JPL

Wayne-1.jpg

waynechi[AT]cs[DOT]cmu[DOT]edu

Gates Hillman Centers 7121

Hi, my name is Wayne. I am a first year Ph.D. Student in the Computer Science Department at CMU advised by Chris Donahue and Ameet Talwalkar.

My research interests are 1. in the application of machine learning for creativity and 2. human-centric machine learning (I like to think of this as a middle-ground between HCI and Machine Learning). Topics I’m interested in include (but are not limited to):

  • Improved controllability for generative models
  • Automated game design / development
  • Language Models as Agents
  • LLM Evaluation (especially in real-world settings)

I completed my undergraduate and master’s at the University of Southern California. Before starting my Ph.D., I spent around 7 years in industry working as an Applied Scientist at AWS (2019-2023) and NASA’s Jet Propulsion Laboratory (2016-2019). If you are interested in any of my research topics or considering a Ph.D. after industry feel free to reach out.

news

Mar 5, 2025 Preprint for Copilot Arena
Oct 16, 2024 Launched Copilot Arena.
Aug 28, 2023 Started my Ph.D. at CMU!

selected publications

2021

  1. AAAI
    Symbolic music generation with transformer-gans
    Aashiq Muhamed, Liang Li, Xingjian Shi, Suri Yaddanapudi, Wayne Chi, Dylan Jackson, Rahul Suresh, Zachary C Lipton, and Alex J Smola
    In AAAI conference on artificial intelligence, 2021

2020

  1. ICAPS
    Scheduling with complex consumptive resources for a planetary rover
    Wayne Chi, Steve Chien, and Jagriti Agrawal
    In International Conference on Automated Planning and Scheduling, 2020
  2. ISMIR
    Generating Music with a Self-Correcting Non-Chronological Autoregressive Model
    Wayne Chi, Prachi Kumar, Suri Yaddanapudi, Rahul Suresh, and Umut Isik
    International Society for Music Information Retrieval, 2020
  3. ICML ML4MD
    Self-Correcting Non-Chronological Autoregressive Music Generation
    Wayne Chi, Prachi Kumar, Suri Yaddanapudi, Rahul Suresh, and Umut Isik
    In ICML 2020 Workshop, Machine Learning for Music Discovery (ML4MD), 2020

2019

  1. ICAPS
    Optimizing parameters for uncertain execution and rescheduling robustness
    Wayne Chi, Jagriti Agrawal, Steve Chien, Elyse Fosse, and Usha Guduri
    In International Conference on Automated Planning and Scheduling, 2019

2018

  1. ICAPS
    Embedding a Scheduler in Execution for a Planetary Rover
    Wayne Chi, Steve A Chien, Jagriti Agrawal, Gregg Rabideau, Edward Benowitz, Daniel M Gaines, Elyse Fosse, Stephen Kuhn, and James Biehl
    In International Conference on Automated Planning and Scheduling, 2018
  2. ICAPS
    Using Squeaky Wheel Optimization to Derive Problem Specific Control Information for a One Shot Scheduler for a Planetary Rover
    Wayne Chi, Steve Chien, and Jagriti Agrawal
    In International Conference on Automated Planning and Scheduling, 2018