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Dr. Yu Zhang Assistant Professor Affiliations: CITRIS and the Banatao Institute Office: E2-547B
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Short Bio
Dr. Yu Zhang is an Assistant Professor in the ECE Department of the University of California, Santa Cruz. He received the Ph.D. degree from the University of Minnesota and was a postdoc at UC Berkeley & Lawrence Berkeley National Laboratory. His research interests span the spectrum from theory to practice, which include
Monitoring, learning, and management for smart power grids
Optimal resource allocation for cyber-physical systems
Robust, stochastic, and online optimization
Deep learning and AI.
News
04/2024: New paper Addressing Heterogeneity in Federated Load Forecasting via Personalization Layers is accepted by the Institute of Industrial and Systems Engineers (IISE) Annual Conference.
03/2024: New paper Greening Service Capacity in Telecom Supply Chain under Environmental Regulation is accepted by Sustainability.
03/2024: New paper Adaptive Fault Detection for Grid-Forming Inverters is accepted by IEEE Access.
02/2024: New paper A Novel Observer-Centric Approach for Detecting Faults in Islanded AC Microgrids with Uncertainties is accepted by IEEE Systems Journal.
02/2024: Privacy-Preserving Load Forecasting via Personalized Model Obfuscation is accepted by 2024 IEEE PES General Meeting
12/2023: IEEE Spectrum News on our work of Reinforcement Learning based Load Restoration; see more Media Coverage.
12/2023: New preprint Learning to Optimize: Accelerating Optimal Power Flow via Data-driven Constraint Screening.
12/2023: Jing Xiong successfully defended her PhD Thesis “Deep Learning Based Load Forecasting and Monitoring for Electric Power Systems.” Congratulations!
11/2023: New preprint Privacy-Preserving Load Forecasting via Personalized Model Obfuscation.
09/2023: Our team won the L2RPN Delft 2023 competition.
09/2023: Our paper Load Restoration in Islanded Microgrids: Formulation and Solution Strategies is accepted by IEEE Transactions on Control of Network Systems.
08/2023: Our paper Physics-guided Residual Learning for Probabilistic Power Flow Analysis is accepted by IEEE Access.
07/2023: Our paper MATNilm: Multi-appliance-task Non-intrusive Load Monitoring with Limited Labeled Data is accepted by IEEE Transactions on Industrial Informatics.
07/2023: Our paper “Power System Quasi-Steady State Estimation: An Echo State Network Approach” is accepted by the 55th Annual North American Power Symposium.
06/2023: Shourya Bose is awarded the IEEE-IES Student and Young Professionals Paper Assistances (IES-SYPA).
05/2023: Our paper A Unifying Framework of Attention-based Neural Load Forecasting is accepted by IEEE Access.
04/2023: Our paper “On LinDistFlow Model Congestion Pricing: Bounding the Changes in Power Tariffs” is accepted by International Symposium on Industrial Electronics (ISIE)
03/2023: Our paper “Frequency Cyber-Attack Detection in Droop-Controlled Grid Forming Inverters” is accepted by PES General Meeting.
02/2023: Our paper Real-Time Power System Event Detection: A Novel Instance Selection Approach is accepted by IEEE Access.