معرفی
Yi Hu is an Assistant Professor in the Department of Electrical and Computer Engineering at Michigan Technological University, appointed in August 2025 following his Ph.D. completion at North Carolina State University. His work bridges artificial intelligence and power systems engineering to advance grid digitalization and renewable energy integration.
His academic credentials include:
- Ph.D. in Electrical Engineering, North Carolina State University (2025)
- M.S. in Electrical Engineering, Peking University (2018)
- B.S. in Electrical Engineering, Chongqing University of Posts and Telecommunications (2014)
Dr. Hu's research specializes in generative AI applications for power systems, with emphasis on synthetic data generation, missing data restoration, and load profile analysis. He pioneers techniques using LLMs and GANs to reduce data requirements for grid analytics while enhancing privacy preservation and situational awareness in renewable energy integration.
His publication portfolio reveals a cohesive trajectory applying cutting-edge AI to power system data challenges, particularly in load forecasting and grid resilience. The work spans computer science, electrical engineering, and data analytics, consistently targeting practical implementations for modern smart grids.
Award recognitions include:
- Exceptional Reviewer for IEEE Transactions on Sustainable Energy (2024)
- E-STAR Award from Eaton Research Lab for generative AI innovation (2024)
Dr. Hu actively recruits graduate researchers for industry-collaborative projects, leveraging his internship experiences at Eaton and Quanta Technology. His group emphasizes open-source development and top-tier publications in energy AI, with current funding supporting synthetic data frameworks and human-machine interfaces for grid operators.
Establishing his research lab at MTU, he focuses on real-world AI deployment for grid digitalization through partnerships with Harvard University, NC State, and energy industry leaders, advancing tools for next-generation power system management.
