Di Wu, MIAE

Di Wu is an applied AI researcher working on Trustworthy and Data-Efficient Decision-Making for Complex Real-World Systems. He is currently an Associate Professor at Concordia University, an Associate Academic Member of Mila – Quebec AI Institute, and an Adjunct Professor at McGill University. Previously, he was a Senior Staff Research Scientist at Samsung AI Center Montreal, where he led the LLM Optimization and AI for Telecommunications teams and was recognized as an All-Star Researcher. Prior to Samsung, he conducted postdoctoral research at Mila and Stanford University. He received his Ph.D. from McGill University in 2018 and his M.Sc. from Peking University in 2013, and holds dual bachelor’s degrees in Microelectronics and Economics. 

His research focuses on developing data-efficient, safe, and trustworthy AI methods for decision-making under uncertainty, spanning three interconnected areas: 1) Predictive Intelligence, 2) Safe and Data-Efficient Reinforcement Learning, and 3) Trustworthy and Efficient Large Language Models. His work encompasses time-series forecasting, World Models / Digital Twins, safe and offline reinforcement learning, LLM reliability, efficient LLMs, reliable agentic AI, and self-improving intelligence. His research bridges fundamental AI methodologies with real-world applications in energy, telecommunications, transportation, and intelligent infrastructure, with demonstrated improvements in energy efficiency, reliability, and resource utilization. He has published over 200 papers, including work in NeurIPS, ICML, ICLR, AAAI, IJCAI, JMLR, TMLR, and leading IEEE journals. He has secured over CAD $3 million in research funding and holds more than 20 U.S. patents in AI and intelligent systems. His work has received three Best Paper Awards: IEEE GLOBECOM 2021, IEEE ITSC 2024, and IEEE EPEC 2025, along with multiple Best Paper Award nominations.

For potential students

We are recruiting motivated Ph.D. students (fully funded) to join our research group at Concordia University.

Interested candidates are encouraged to contact me at di.wu@concordia.ca if they:

1. Have published at least one research paper.

2. Have a strong background in AI, machine learning, and/or mathematics.

3. Have a genuine passion for conducting innovative, cutting-edge research.

Start Date: Fall 2027