- Gund Fellow
BIO
Mads Almassalkhi (IEEE M'06; SM'19) is Associate Professor in the Department of Electrical and Biomedical Engineering at ¶¶Òõ̽̽ and co-founder of startup company Packetized Energy. His research interests lie at the intersection of power systems, mathematical optimization, and control systems and focuses on developing scalable algorithms that improve responsiveness and resilience of power systems. He was awarded the Outstanding Junior Faculty award by ¶¶Òõ̽̽ CEMS in 2016. Prior to joining ¶¶Òõ̽̽, he was lead systems engineer at Root3 Technologies, which developed software for set-point optimization of multi-energy systems. Before that, he received his PhD from the University of Michigan in Electrical Engineering: Systems (EE:S) in 2013 and a dual major in Electrical Engineering and Applied Mathematics at the University of Cincinnati, in Ohio, in 2008. He also serves as Chair of the IEEE SBLC Loads Subcommittee.
Area(s) of expertise
Power and Energy Systems, Control Systems, Mathematical Optimization, Renewable Energy Integration
Bio
Mads Almassalkhi (IEEE M'06; SM'19) is Associate Professor in the Department of Electrical and Biomedical Engineering at ¶¶Òõ̽̽ and co-founder of startup company Packetized Energy. His research interests lie at the intersection of power systems, mathematical optimization, and control systems and focuses on developing scalable algorithms that improve responsiveness and resilience of power systems. He was awarded the Outstanding Junior Faculty award by ¶¶Òõ̽̽ CEMS in 2016. Prior to joining ¶¶Òõ̽̽, he was lead systems engineer at Root3 Technologies, which developed software for set-point optimization of multi-energy systems. Before that, he received his PhD from the University of Michigan in Electrical Engineering: Systems (EE:S) in 2013 and a dual major in Electrical Engineering and Applied Mathematics at the University of Cincinnati, in Ohio, in 2008. He also serves as Chair of the IEEE SBLC Loads Subcommittee.
Areas of Expertise
Power and Energy Systems, Control Systems, Mathematical Optimization, Renewable Energy Integration