Guiding Tomorrow's Energy Leaders: Introducing Professor Junbo Zhao

Junbo Zhao, the Todd M. Cook and Elizabeth Cook Associate Professor of Engineering and Irving Institute Faculty Affiliate. (Photo by Katie Lenhart)

Professor Zhao shared, "I'm very excited to teach this great cohort of students about today's and tomorrow's energy technologies, covering the entire energy value chain from generation to grid-edge systems. Students will explore a wide range of energy infrastructures, including traditional systems like fossil fuels and nuclear power, while also investigating the crucial shift towards low-carbon and decentralized energy solutions. This prepares them to tackle complex energy system challenges."

Zhao's course covers key topics, including the integration of renewable energies, such as solar, wind, hydro, and geothermal, as well as smart grids, energy storage solutions, and innovations related to electric vehicles. Through case studies, simulations, and project-based learning, students will assess the security and reliability of these technologies. This comprehensive approach equips students to contribute meaningfully to the development and implementation of efficient, sustainable energy systems.

Zhao is widely regarded as a leading thinker in his field, recognized by his numerous accolades. These include the prestigious NSF CAREER Award; the IEEE Power & Energy Society Outstanding Young Engineer award; Early-Career Research Fellowship of National Academies of Sciences, Engineering, and Medicine; IEEE PES Technical Committee Distinguished Individual Service Award; his role as editor-in-chief of the International Journal of Electrical Power & Energy Systems; and his leadership positions at various IEEE Power & Energy Society committees and subcommittees. Notably, he has also received eleven Best Paper Awards from IEEE between 2020 and 2025, reflecting his groundbreaking contributions to energy research.

One of his acclaimed papers, "A Review of Safe Reinforcement Learning Methods for Modern Power Systems," published in Proceedings of the IEEE, explores the intersection of AI and energy systems. By examining safe reinforcement learning (RL) methods, the paper demonstrates how advanced techniques can enhance the security and efficiency of energy operations. These innovations are critical for ensuring safety while optimizing performance in real-world power systems. Zhao's work emphasizes the use of proactive mechanisms in RL to ensure operational safety, paving the way for more reliable integration of AI in energy management.

"We are thrilled to have Professor Zhao launch the first term of our inaugural year of the MET program," shared Dartmouth Engineering Professor and Irving Faculty Director, Geoff Parker. "His scholarship and teaching will help to equip future leaders with the skills needed to innovate affordable and reliable energy solutions that foster sustainable growth."