Nai-Chieh Huang

About me

I am an incoming Ph.D. student in the Machine Learning Department at Carnegie Mellon University, where I am fortunate to be advised by Prof. Max Simchowitz. My research interests lie broadly in reinforcement learning, control, generative modeling, and optimization. Specifically, I am interested in the mathematical and algorithmic foundations of generative modeling for reinforcement learning and control.

Previously, I received my B.S. in Computer Science from National Yang Ming Chiao Tung University in Taiwan. As an undergraduate, I conducted research under the supervision of Prof. Ping-Chun Hsieh, focusing on convergence guarantees in reinforcement learning.

News

Jul 11, 2025	Excited to join CMU MLD as a PhD student! Can’t wait to visit Pittsburgh and meet everyone soon!

Selected Publications

Accelerated Policy Gradient: On the Convergence Rates of the Nesterov Momentum for Reinforcement Learning

Yen-Ju Chen^*, Nai-Chieh Huang^*, Ching-pei Lee, and Ping-Chun Hsieh

In International Conference on Machine Learning (ICML), 2024

arXiv Bib PDF

@inproceedings{chen2024accelerated,
  title = {Accelerated Policy Gradient: On the Convergence Rates of the Nesterov Momentum for Reinforcement Learning},
  author = {Chen, Yen-Ju and Huang, Nai-Chieh and Lee, Ching-pei and Hsieh, Ping-Chun},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
}

PPO-Clip Attains Global Optimality: Towards Deeper Understandings of Clipping

Nai-Chieh Huang, Ping-Chun Hsieh, Kuo-Hao Ho, and I-Chen Wu

In Proceedings of the AAAI Conference on Artificial Intelligence, 2024

arXiv Bib PDF

@inproceedings{huang2024ppo,
  title = {PPO-Clip Attains Global Optimality: Towards Deeper Understandings of Clipping},
  author = {Huang, Nai-Chieh and Hsieh, Ping-Chun and Ho, Kuo-Hao and Wu, I-Chen},
  booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
  volume = {38},
  number = {11},
  pages = {12600--12607},
  year = {2024},
}