Yi-Chung (Andrew) Chen

PhD Student in Electrical and Computer Engineering at Purdue University

prof_pic_andrew.jpg

Purdue University

West Lafayette, IN

chen5262@purdue.edu

I am a third-year PhD student in Electrical and Computer Engineering at Purdue University (started 2024), co-advised by Prof. Jing Gao and Prof. David Inouye. My research focuses on trustworthy machine learning and physical AI.

Prior to my PhD, I earned my M.S. in Communication Engineering from National Taiwan University (2021-2023), where I was advised by Prof. Ming-Syan Chen. I completed my B.S. in Electronic Engineering at National Yang Ming Chiao Tung University (2017-2021), where I was mentored by Prof. Hong-Han Shuai and Prof. Wen-Huang Cheng.

My primary research interest lies at the intersection of trustworthy machine learning and physical AI, with a focus on robustness, interpretability, and uncertainty. I am currently interested in uncertainty-aware planning with world models. Previously, I have explored generative classification, multi-agent behavior prediction, diffusion model quantization, and federated learning.

news

Sep 2026 Our paper StarCraft Motion: A Dataset for Agent Simulation in Adversarial and Partially Observable Scenarios was accepted to the NeurIPS 2026 Evaluations & Datasets (E&D) Track.
May 2026 Joined Uber AV Labs in Sunnyvale, CA as a PhD Software Engineer Intern for the summer.
Jan 2026 Our paper Your VAR Model is Secretly an Efficient and Explainable Generative Classifier was accepted to ICLR 2026.
Sep 2024 Our paper StepbaQ: Stepping backward as Correction for Quantized Diffusion Models was accepted to NeurIPS 2024.
Aug 2024 Started my PhD in ECE at Purdue University, co-advised by Prof. Jing Gao and Prof. David Inouye.

experience

PhD Software Engineer Intern May 2026 – Aug 2026
Uber AV Labs · Sunnyvale, CA
Developed TraVEL, a trajectory-guided GRPO framework that adapts vision-language embeddings for motion-aware driving-video retrieval.
Engineer Sep 2023 – Sep 2024
MediaTek · Hsinchu, Taiwan
Led the team's first research project on diffusion model quantization for on-device image generation (NeurIPS 2024).
Co-founder Nov 2021 – Feb 2023
Stylins · Taipei, Taiwan
Built a high-resolution, real-time virtual try-on service with size-aware clothing adjustment (ICCV 2023).

selected publications

  1. NeurIPS E&D
    StarCraft Motion: A Dataset for Agent Simulation in Adversarial and Partially Observable Scenarios
    Yi-Chung Chen, Mingyu Kim, Ruqi Bai, and 3 more authors
    In Advances in Neural Information Processing Systems, Evaluations & Datasets Track, 2026
  2. ICLR
    Your VAR Model is Secretly an Efficient and Explainable Generative Classifier
    Yi-Chung Chen, David I Inouye, and Jing Gao
    In International Conference on Learning Representations, 2026
  3. NeurIPS
    StepbaQ: Stepping backward as Correction for Quantized Diffusion Models
    Yi-Chung Chen, Zhi-Kai Huang, and Jing-Ren Chen
    Advances in Neural Information Processing Systems, 2024
  4. NeurIPS
    Space: Single-round participant amalgamation for contribution evaluation in federated learning
    Yi-Chung Chen, Hsi-Wen Chen, Shun-Gui Wang, and 1 more author
    Advances in Neural Information Processing Systems, 2023
  5. ICCV
    Size does matter: Size-aware virtual try-on via clothing-oriented transformation try-on network
    Chieh-Yun Chen*, Yi-Chung Chen*, Hong-Han Shuai, and 1 more author
    In Proceedings of the IEEE/CVF international conference on computer vision, 2023