Yi Hu

Contact

yhu6@mtu.edu
906-487-3091
EERC 504

Assistant Professor, Electrical and Computer Engineering

Ph.D., Electrical Engineering, North Carolina State University, 2025
M.S., Electrical Engineering, Peking University, 2018
B.S., Electrical Engineering, Chongqing University of Posts and Telecommunications, 2014

Biography

Yi Hu joined Michigan Technological University in 2025 as an assistant professor in the Department of Electrical and Computer Engineering, after receiving his PhD in Electrical Engineering from North Carolina State University. His research combines power system knowledge with advanced computational methods to address challenges arising from the increasing complexity, uncertainty, and digitalization of the electric grid. His work has been published in leading journals, including IEEE Transactions on Smart Grid, IEEE Transactions on Industrial Informatics, Applied Energy. He has also gained industry research experience through internships at Eaton Research Lab and Danovo Energy, formerly Quanta Technology.

Links of Interest

Courses Taught

EE 4221 - Power System Analysis I
EE 4222 - Power System Analysis II

Research Interests

Power and Energy Systems
Artificial Intelligence
Data Science

Recent Publications

C. Ngwerume, L. Tong, C.-W. Ten, and Y. Hu, “A Configurable Thermal-Dynamic Model for AI Data Center Cooling Load Simulation,” arXiv preprint, arXiv:2607.28962, 2026.
Y. Hu and Z. Cheng, "Generative AI for Open-Set Event Detection and Classification in Power Systems Using Synchrophasor Data," in IEEE Transactions on Industrial Informatics, doi: 10.1109/TII.2026.3690931.
H. Kim, Y. Hu, K. Ye, and N. Lu. "Vit4lpa: A Vision Transformer for Advanced Smart Meter Load Profile Analysis", in Applied Energy, vol. 382, pp. 125243, Mar. 2025.
Y. Hu, H. Kim, K. Ye, and N. Lu, "Applying Fine-Tuned LLMs for Reducing Data Needs in Load Profile Analysis", in Applied Energy, vol. 377, pp. 124666, Jan. 2025.
Y. Hu, K. Ye, H. Kim and N. Lu, "BERT-PIN: A BERT-Based Framework for Recovering Missing Data Segments in Time-Series Load Profiles", in IEEE Transactions on Industrial Informatics, vol. 20, no. 10, pp. 12241-12251, Oct. 2024, doi: 10.1109/TII.2024.3417272.
Y. Hu, Y. Li, L. Song, H.P. Lee, PJ. Rehm, M. Makdad, E. Miller, and N. Lu, "MultiLoad-GAN: A GAN-Based Synthetic Load Group Generation Method Considering Spatial-Temporal Correlations", in IEEE Transactions on Smart Grid, vol. 15, no. 2, pp. 2309-2320, Mar. 2024, doi: 10.1109/TSG.2023.3302192.
Y. Li, L. Song, Y. Hu, H.P. Lee, D. Wu, PJ. Rehm, N. Lu, "Load Profile Inpainting for Missing Load Data Restoration and Baseline Estimation", in IEEE Transactions on Smart Grid, vol. 15, no. 2, pp. 2251-2260, Mar. 2024, doi: 10.1109/TSG.2023.3293188.