Qiang Sun

Qiang Sun is an Associate Professor of Statistics and Computer Science at the University of Toronto (UofT), holding cross-appointments in the Department of Computer Science and the Department of Computer and Mathematical Sciences. He leads the StatsLE (Statistics, Learning, and Engineering) Lab, focusing on generative AI, trustworthy AI, and next-generation statistics. His research bridges statistical theory with applied challenges in industry, emphasizing ensemble learning, transfer learning, and reinforcement learning, with applications in tech, finance, and science.

Education:

• PhD from the University of North Carolina at Chapel Hill (UNC-CH)
• BS in SCGY from the University of Science and Technology of China (USTC)

Research Interests: Sun’s work spans foundational AI and statistical methods, including GenAI, robust algorithms, and interdisciplinary applications. His lab explores topics like resistant clustering, physical commonsense violation detection in gameplay, and microbiome analysis. Recent trends in his publications emphasize robustness (e.g., heavy-tailed errors), multimodal learning, and lifelong learning frameworks.

Scientific Awards:

• Connaught Award
• James E. Grizzle Distinguished Alumni
• Noah’s Ark Distinguished Lecture

Advising & Grants: While student names are not listed, his grants and collaborations reflect industrial and academic partnerships. He serves as an associate editor for the Electronic Journal of Statistics and as an area chair for conferences like AISTATS and COLT.

Labs & Teams: The StatsLE Lab at UofT drives his research, integrating statistical theory with cutting-edge AI applications.