Michael Qizhe Shieh

Michael Qizhe Shieh is an Assistant Professor in the Department of Computer Science at the National University of Singapore (NUS), affiliated with the Tree and Rock AI Lab (TRAIL). He holds a PhD and Master's from Carnegie Mellon University (Machine Learning and Language Technologies) and a Bachelor's from Shanghai Jiao Tong University's ACM Class. His research focuses on Large Language Models, Deep Learning, and Natural Language Processing, with notable contributions to semi-supervised learning techniques like Noisy Student and UDA, and the RACE benchmark for reading comprehension.

• Education:
  • PhD in Machine Learning, Carnegie Mellon University (2020)
  • Master's in Language Technologies, Carnegie Mellon University (2018)
  • Bachelor's in Computer Science, Shanghai Jiao Tong University (2016)

His research explores robustness, safety, and scalability of AI systems. He has served as Area Chair for top conferences like NeurIPS, ICML, and ICLR. Current research directions include adversarial robustness, LLM self-evaluation, and alignment mechanisms. His lab, TRAIL, emphasizes foundational AI research.

Selected contributions include:

• Developing UDA and Noisy Student techniques for semi-supervised learning
• Creating the RACE benchmark for exam-based reading comprehension
• Advancing methods for LLM safety and adversarial defense

Prospective students are encouraged to apply to NUS's PhD program for collaborative research opportunities.