Data Science and Smart Grid Applications
This webinar will provide an overview of data science, including machine learning and optimization, and present a few applications in the context of Smart Grid. Professor El Ghaoui will describe work done in collaboration with different units at EDF. Some of the topics reviewed include: a)text analytics for business intelligence on smart grid applications, b) advanced machine learning and optimization for co-generation intra-day plant management, and c) optimal design of complex smart grid systems using surrogate models.
Instructors
Prof. Laurent El Ghaoui
Laurent El Ghaoui graduated from Ecole Polytechnique (Palaiseau, France) in 1985, and obtained his Ph.D. in Aeronautics and Astronautics at Stanford University in March 1990. Professor El Ghaoui taught in several institutions in France (Ecole Polytechnique, ENSTA and U. Paris La Sorbonne), then joined the UC Berkeley faculty in April 1999 as an Acting Associate Professor, and obtained tenure in May 2001. He was on leave from UC from July 2003 to 2006 to work for the hedge fund SAC Capital Management.
Dr. Stephanie Jumel
Stephanie Jumel joined EDF innovation Lab in 2013, to support EDF Business Units in North America on new energy services for Commercial, industrial, and MUSH markets. In previous positions Stephanie has been leadiing a research team on simulation tools for industrial energy efficiency, and contributed to the development of ElfeER )EDF R&D, Germany) by setting up research group on urban energy planning. Passionate about modeling and simulation, she started her career in developiing a multi-scale simulation toll to study irradiation-induced embrittlement of PWR vessels. Stephanie earned a PhD in Materials Science. She is also teaching material science at University Pierre & Marie Curie (Paris) and co-founder of Global-Vision, a French start-up supporting innovation in SMEs.
Publication Year: 2016
Earn 1 Professional Development Hour (PDH) for completing the webinar