Agentic AI in Practice: Closing the Gap Between Theory and Deployment

Maria is a product and innovation expert with over 15 years of energy & utility industry experience. Maria started her career in the generation space working in nuclear, solar, and gas power plants before migrating to work on energy demand management and optimization. Over the years she has relished digging into the details of energy and her passion lies in the interconnection between supply and demand and creating solutions for a flexible energy future. At PADO Maria works closely with clients, stakeholders, and the internal team to create a vision and path to enable data centers to maximize compute per megawatt.

Na Li is a Winokur Family Professor of Electrical Engineering and Applied Mathematics at Harvard University. She received her Bachelor's degree in Mathematics from Zhejiang University in 2007 and Ph.D. degree in Control and Dynamical systems from California Institute of Technology in 2013. She was a postdoctoral associate at the Massachusetts Institute of Technology 2013-2014. She has held a variety of short-term visiting appointments including the Simons Institute for the Theory of Computing, MIT, Google Brain, and MERL. Her research lies in the control, learning, and optimization of networked systems, including theory development, algorithm design, and applications to real-world cyber-physical societal systems.

She is an IEEE fellow and a senior editor of IEEE Transactions on Control of Network Systems. She was an associate editor for IEEE Transactions on Automatic Control, Systems & Control Letters, IEEE Control Systems Letters and also served on the organizing committee for a few conferences and workshops such as IEEE CDC, AMC E-energy, and NSF workshop on Reinforcement Learning. She received the NSF career award, AFSOR Young Investigator Award, ONR Young Investigator Award, Donald P. Eckman Award, McDonald Mentoring Award, IEEE CSS Distinguished Lecturer, IFAC Distinguished Lecturer, IFAC Manfred Thoma Medal, Ruberti Young Researcher Prize, along with other awards.

With over 25 years of tech experience, Jun has helped create innovative solutions in biotech and energy. For Pado, Jun is building a proprietary data orchestration platform that will help the grid adapt to the growing demands of AI. Trained as a theoretical scientist, Jun is excited to bring his passion for AI/ML and high performance computing to Pado. Prior to joining Pado, Jun founded ThinkEco in 2008, an award-winning demand response company. ThinkEco's patented technology was the basis of commercial partnerships with leading companies, including Con Edison, GE Appliances, LG Electronics, and Rakuten. Jun has a BA, MA, and PhD (Chemical Physics) from Harvard, and a Professional Certificate in AI from Stanford.