Principal Engineer at Quanta Technology LLC, United States
Dr. Mengmeng Zhuang is a seasoned data scientist and engineer with 13 years of professional experience, including 8 years in AI applications within the energy sector. She holds a Ph.D. in Electrical Engineering from Illinois Institute of Technology. Dr. Zhuang has demonstrated exceptional skills in machine learning, data product development, and consulting, with a strong focus on energy systems and smart grid technologies. Her career includes significant contributions to both academia and industry, highlighted by her roles at Quanta Technology LLC and Aiknow Inc., where she led innovative projects and grew startups. Dr. Zhuang is recognized for her ability to transition research into practical applications, significantly impacting energy conservation and smart grid operations. Her expertise spans international collaborations, startup growth, and advanced data analysis, underscoring her role as a leading figure in AI-driven energy solutions.
Publication Profile
Education
Dr. Mengmeng Zhuang earned her Ph.D. in Electrical Engineering from Illinois Institute of Technology (2016-2019), where her thesis focused on scalable non-intrusive load monitoring using deep learning for load identification and management. Her coursework covered advanced topics such as power market operations, microgrid design, and cloud-based machine learning. Prior to this, she completed her M.S. in Testing Measurement Technology and Instruments at Zhejiang Sci-Tech University (2009-2012), where she researched PIV technology for measuring ionic wind air accelerators. Dr. Zhuang obtained her B.S. in Automation from Henan University of Science and Technology (2005-2009). Her educational background has provided a strong foundation in both theoretical and practical aspects of electrical engineering and data science, enabling her to excel in her subsequent research and professional endeavors.
Experience
Dr. Mengmeng Zhuang has accumulated extensive experience in both academic and industry settings. She currently serves as Principal Engineer at Quanta Technology LLC, where she leads the development of scalable ML models, optimal control algorithms, and data analysis products. At Illinois Institute of Technology, she worked as a Research Associate and Lab Manager, focusing on deep reinforcement learning for energy conservation and load disaggregation. As a Co-Founder of Aiknow Inc., Dr. Zhuang spearheaded the development of AI-driven energy management solutions and expanded the startup team to 30+ members. Her earlier roles included leading ESP scheme design at Teams Environment Protection Engineering Co. Ltd and software development at Tieto and Bosch. Dr. Zhuang’s diverse experience highlights her capability to drive innovation in energy systems and smart grid applications.
Awards and Honors
Dr. Mengmeng Zhuang has received several prestigious awards throughout her career. She earned the PhD-level Poster Competition Second Award from Illinois Institute of Technology in 2019 and the Innovative Award of Smart Energy Usage from the Department of Energy’s JUMP program in 2016. In recognition of her academic excellence, she was named an Excellent Graduate of Zhejiang Province in 2012, ranking top 1 of 1000. Additionally, Dr. Zhuang won 1st Prize in the Challenge Cup National College Student Extracurricular Science Work Competition of Zhejiang Province in 2011. These accolades reflect her outstanding contributions to research, innovation, and practical applications in the fields of energy and smart grid technologies.
Research Focus
Dr. Mengmeng Zhuang’s research focuses on the integration of artificial intelligence with energy systems to enhance efficiency and sustainability. Her work emphasizes deep reinforcement learning for non-intrusive load monitoring, aiming to improve load identification and management while minimizing computational complexity. She has developed robust algorithms for energy conservation and smart grid applications, including load disaggregation and optimal control. Her research also addresses energy efficiency and conservation through innovative machine learning approaches, impacting both residential and industrial sectors. Dr. Zhuang’s research is characterized by a strong emphasis on practical implementation, moving from theoretical frameworks to real-world applications. Her contributions have significantly advanced the understanding and application of AI in energy systems, supporting both environmental sustainability and operational efficiency.
Publications Top Notes
- Integrated Energy Cyber–Physical System Fusion Modeling and Operation State Analysis under the Cooperative Attack
- Authors: Fan, H., Sheng, Y., Lu, E., Zhuang, M., Zhou, B.
- Journal: Electric Power Systems Research
- Year: 2024
- Citations: 0 ⚡🔐
- Multi-Timescale Synergistic Planning for Flexible Regulation of Thermal Power to Support Wind-Photovoltaic-Storage
- Authors: Fan, H., Li, T., Jia, Q.-S., Zhuang, M.
- Journal: IET Renewable Power Generation
- Year: 2024
- Citations: 0 🌞⚡💨
- Collaborative Optimal Dispatch of Multi-Agent Distributed Integrated Energy System Based on Game Theory
- Authors: Fan, H., Liu, L., Ma, Y., Chen, S., Zhuang, M.
- Conference: 2023 IEEE 7th Conference on Energy Internet and Energy System Integration (EI2 2023)
- Year: 2023
- Citations: 0 🎮💡
