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Dr. Jin Zhao

Assistant Professor (Electronic & Elect. Engineering)
      
Profile Photo

Dr. Jin Zhao

Assistant Professor (Electronic & Elect. Engineering)

 zhaoj6@tcd.ie

 


Jin Zhao is an Assistant Professor at Trinity College Dublin. Her research interests include Resilient Energy System, Electricity, Operation of Highly Renewable Energy Integrated Systems, Microgrids and Machine Learning. She is the Alexander von Humboldt Fellow of Germany. She was a Research Scientist at The University of Tennessee (UTK). She received the B.E. and Ph.D. degrees from Shandong University, Jinan, China, all in the electrical engineering, in 2015 and 2020, respectively. She serves as a Subject Editor of IET Generation, Transmission & Distribution, a Editor of IEEE trans on Smart Grid, and a regular reviewer for several IEEE and Nature Portfolio journals. She is the chair of IEEE Task Force AISR and PES representative of IEEE DataPort. She was an outstanding reviewer of several IEEE Trans. journals. Please find our lab IResX here: https://jinzhaotcd.github.io/
Details Date
Secretary of IEEE load subcommittee
Secretary of IEEE EDPG GHG subcommittee
Associate Editor of IEEE trans. on Smart Grid
Senior Editor of IET Generation, Transmission & Distribution
Chair of IEEE TF AISR (https://cmte.ieee.org/pes-rsei/)
Steering Committee (PES rep) of IEEE DataPort (https://ieee-dataport.org/)
Language Skill Reading Skill Writing Skill Speaking
Chinese Fluent Fluent Fluent
English Fluent Fluent Fluent
Details Date From Date To
Alexander von Humboldt Fellow
IEEE Member, IEEE PES member.
X. Cui, J. Zhao, C. -K. Lee and Y. Hou, Robust Co-Planning of Dynamic Wireless Charging Lanes and Remote-Controlled Switches Under Exogenous and Endogenous Uncertainties, IEEE Transactions on Smart Grid, 2026, Journal Article, PUBLISHED
C. Li, F. Li, S. Jang, J. Zhao, S. Fan, and L. M. Tolbert, Resilience-Oriented DG Siting and Sizing Considering Energy Vulnerability Constraint, IEEE Transactions on Smart Grid, 2026, Journal Article, PUBLISHED
Fangxing Li, Qingxin Shi, Jin Zhao, Solutions, current issues, and future challenges, Elsevier eBooks, 2025, p19 - 39, p19-39 , Book Chapter, PUBLISHED  DOI
Fangxing Li, Qingxin Shi, Jin Zhao, Machine learning for postevent restoration, Elsevier eBooks, 2025, p193 - 214, p193-214 , Book Chapter, PUBLISHED  DOI
Fangxing Li, Qingxin Shi, Jin Zhao, Machine learning for preparation before events, Elsevier eBooks, 2025, p139 - 163, p139-163 , Book Chapter, PUBLISHED  DOI
Fangxing Li, Qingxin Shi, Jin Zhao, Machine learning for during-event mitigation, Elsevier eBooks, 2025, p165 - 191, p165-191 , Book Chapter, PUBLISHED  DOI
Fangxing Li, Qingxin Shi, Jin Zhao, Resilience-oriented short-term planning in urban-level power networks, Elsevier eBooks, 2025, p83 - 105, p83-105 , Book Chapter, PUBLISHED  DOI
Y Shen, J Zhao, P Chen, Q Zhou, Zero-trust Framework for Resilient Power System with Anomalous Data, 2025 IEEE Kiel PowerTech, 2025, Conference Paper, PUBLISHED
Y Shen, Q Zhou, J Zhao, Pioneering Climate Change Adaptation: Sustainable Power Systems Enhanced by Integrated Satellite"Terrestrial Networks, IEEE Energy Sustainability Magazine, 2025, p53 - 65, Journal Article, PUBLISHED  DOI
H. Zhao, S. Liao, B. Liu, Z. Fang, H. Wang, C. Cheng, J. Zhao, Multiagent optimization for short-term generation scheduling in hydropower-dominated hydro-wind-solar supply systems with spatiotemporal coupling constraints, Applied Energy, 382, 2025, Notes: [https://www.sciencedirect.com/science/article/pii/S0306261925000546], Journal Article, PUBLISHED
  

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Award Date
IEEE PES Technical Council Award Young Professional Award 2025
climate adaptive energy systems, power system resilience, high renewable energy integration, microgrids, low-carbon grids, machine learning.