Dr. Boyu Wang holds a Ph.D. in Electrical Engineering from Louisiana State University, Baton Rouge, LA, USA, which he completed from August 2014 to August 2018. Prior to his doctoral studies, he earned a Master of Science in Electrical Engineering from the same institution, Louisiana State University, during the period from August 2012 to August 2014. In addition to his background in electrical engineering, Dr. Wang expanded his expertise by obtaining a Master of Science in Computer Science from the Georgia Institute of Technology, where he studied from January 2020 to May 2022. His multidisciplinary academic training provides a solid foundation for his research and contributions in energy systems, machine learning, and data science.
Experience
Dr. Boyu Wang currently serves as a Principal Data Scientist at Tacoma Public Utilities in Washington, USA, where he leads the annual energy and peak forecasting for resource planning, financial modeling, and power operations. His responsibilities include supporting various teams with data collection, cleaning, and manipulation, as well as developing risk models and automation tools to improve reporting efficiency. Dr. Wang has played a key role in assisting with project management strategies and energy stability efforts. Prior to this, he worked as a Power Engineer Intern at Entergy, where he conducted analysis on renewable energy integration into distribution systems. Throughout his career, Dr. Wang has leveraged his expertise in deep learning, blockchain, and data science to contribute to various innovative research projects, particularly in energy management and grid stability.
Research Interests
Dr. Boyu Wang’s research interests lie at the intersection of energy systems, machine learning, and advanced technologies. His work primarily focuses on applying deep learning techniques, such as convolutional neural networks (CNN) and long short-term memory (LSTM) models, to predict power flow and optimize grid stability in real-time. Additionally, Dr. Wang has explored blockchain-based energy management for decentralized micro-grids, developing dynamic pricing strategies and decision-making algorithms to enhance energy distribution and trading. He is also passionate about developing novel methods for power grid stability, including multi-layer constrained spectral clustering for post-contingency problems and dynamic programming-based control systems for micro-grids. His research aims to advance the resilience and efficiency of energy systems through the integration of cutting-edge computational techniques.
Skills
Dr. Boyu Wang possesses a robust skill set in programming, data analysis, and energy systems optimization. He is proficient in Python, R, and SQL, which he utilizes for data manipulation, analysis, and model development. Dr. Wang is also experienced with platforms and software such as Tableau, DBeaver, Snowflake, and Databricks, enabling him to work efficiently with large datasets and develop impactful visualizations and analytics solutions. His technical expertise extends to deep learning, where he has applied convolutional neural networks (CNN) and long short-term memory (LSTM) models for power flow prediction, as well as blockchain technology for decentralized energy management in micro-grids. These skills, combined with his background in electrical and computer engineering, allow him to tackle complex challenges in energy systems and grid stability.
Publication
Cybersecurity Enhancement of Power Trading within the Networked Microgrids Based on Blockchain and Directed Acyclic Graph Approach
- Authors: B. Wang, M. Dabbaghjamanesh, A. Kavousi-Fard, S. Mehraeen
- Journal: IEEE Transactions on Industry Applications
- Volume: 55, Issue 6, Pages 7300-7309
- Publication Year: 2019
- Cited by: 188
A Novel Two-Stage Multi-Layer Constrained Spectral Clustering Strategy for Intentional Islanding of Power Grids
- Authors: M. Dabbaghjamanesh, B. Wang, A. Kavousi-Fard, S. Mehraeen, …
- Journal: IEEE Transactions on Power Delivery
- Volume: 35, Issue 2, Pages 560-570
- Publication Year: 2019
- Cited by: 70
Blockchain-Based Stochastic Energy Management of Interconnected Microgrids Considering Incentive Price
- Authors: M. Dabbaghjamanesh, B. Wang, A. Kavousi-Fard, N.D. Hatziargyriou, …
- Journal: IEEE Transactions on Control of Network Systems
- Volume: 8, Issue 3, Pages 1201-1211
- Publication Year: 2021
- Cited by: 43
Networked Microgrid Security and Privacy Enhancement by the Blockchain-Enabled Internet of Things Approach
- Authors: M. Dabbaghjamanesh, B. Wang, S. Mehraeen, J. Zhang, A. Kavousi-Fard
- Conference: 2019 IEEE Green Technologies Conference (GreenTech)
- Pages: 1-5
- Publication Year: 2019
- Cited by: 37
Superconducting Fault Current Limiter Allocation in Reconfigurable Smart Grids
- Authors: A.S. Abdollah Kavousi-Fard, Boyu Wang, Omid Avatefipour, Morteza …
- Conference: IEEE, Berkley University Conference on Smart City and Smart Grid
- Publication Year: 2019
- Cited by: 28
Stability Improvement of Microgrids Using a Novel Reduced UPFC Structure via Nonlinear Optimal Control
- Authors: H. Saberi, S. Mehraeen, B. Wang
- Conference: 2018 IEEE Applied Power Electronics Conference and Exposition (APEC)
- Pages: 3294-3300
- Publication Year: 2018
- Cited by: 17
Conclusion
Dr. Boyu Wang’s extensive work in energy systems, innovative applications of deep learning and blockchain technologies, and his leadership in power grid optimization make him an excellent candidate for the Research for Best Researcher Award. His research not only advances theoretical knowledge but also provides practical solutions for improving energy efficiency, grid stability, and resilience, aligning with the award’s recognition of impactful, cutting-edge research.