Emiliano Dall'Anese

Emiliano Dall'Anese is an Assistant Professor in the Department of Electrical, Computer, and Energy Engineering at the University of Colorado Boulder, and an affiliate Faculty with the Department of Applied Mathematics. He received the Ph.D. in Information Engineering from the Department of Information Engineering, University of Padova, Italy, in 2011. From January 2011 to November 2014, he was a Postdoctoral Associate at the Department of Electrical and Computer Engineering of the University of Minnesota, and from December 2014 to July 2018 he was a Senior Researcher at the National Renewable Energy Laboratory. He received the National Science Foundation CAREER Award in 2020, and the IEEE PES Prize Paper Award in 2021.

Gianluca Bianchin

Gianluca is an Assistant Professor at the ICTEAM Institute and Department of Mathematical Engineering at the Université Catholique de Louvain, Belgium. He received the Doctor of Philosophy degree in Mechanical Engineering from the University of California Riverside in 2020, the Laurea degree in Information Engineering, and the Laurea Magistrale degree (Summa Cum Laude) in Controls Engineering from the University of Padova, Italy, in 2012 and 2014, respectively. He was a Postdoctoral Scholar in the ECEE Department at the University of Colorado Boulder from 2020 to 2022. Prof. Bianchin is the recipient of the Dissertation Year Award and the Dean's Distinguished Fellowship Award from the University of California Riverside; his work on secure navigation was the Elsevier Journal of Automatica Editor's choice of the month in February 2020. His research interests include dynamical systems and control theory and their applications in traffic control and complex network control.

Karan Singh

Karan Singh is an Assistant Professor of Operations Research in the Tepper School of Business at Carnegie Mellon University. Drawing from the toolkits of optimization and learning theory, his research addresses algorithmic challenges in feedback-driven interactive learning, spanning both prediction and control. He completed his PhD in Computer Science at Princeton University, where he was awarded the Porter Ogden Jacobus Fellowship. Before joining CMU, he spent an year at Microsoft Research in Redmond as a postdoctoral researcher.

Na Li

Frank Allgöwer

Frank Allgöwer is professor in mechanical engineering and director of the Institute for Systems Theory and Automatic Control at the University of Stuttgart in Germany. His current research interests are to develop new methods for data-based control, optimization-based control and networked control. Frank has served the community in a number of roles, received several recognitions for his work, and has published over 500 scientific articles.

Sarah Dean

Sarah is an Assistant Professor in the Computer Science Department at Cornell. She is interested in the interplay between optimization, machine learning, and dynamics, and her research focuses on understanding the fundamentals of data-driven control and decision-making. This work is grounded in and inspired by applications ranging from robotics to recommendation systems. Sarah has a PhD in EECS from UC Berkeley and did a postdoc at the University of Washington.

Ján Drgoňa

Jan is a senior data scientist and principal investigator in the Physics and Computational Sciences Division at Pacific Northwest National Laboratory (PNNL). Jan has a PhD in Control Engineering from the Slovak University of Technology in Bratislava, and before joining PNNL, he was a postdoc at the mechanical engineering department at Katholieke Universiteit (KU) Leuven in Belgium. His current research is focused on differentiable programming for scientific machine learning, constrained optimization, and model-based optimal control with applications in the energy sector.

John W. Simpson-Porco

John W. Simpson-Porco is an Assistant Professor in the Edward S. Rogers Sr. Department Electrical and Computer Engineering at the University of Toronto. His research focuses on feedback control theory and applications of control and optimization in power and energy systems. John received his B.Sc. degree in Engineering Physics from Queen's University in 2010, and his PhD in Mechanical Engineering from the University of California, Santa Barbara in 2015. He was previously an Assistant Professor of Electrical and Computer Engineering at the University of Waterloo, Waterloo, Canada. Prof. Simpson-Porco is a recipient of the Automatica Paper Prize and the IEEE PES Technical Committee Working Group Recognition Award for Outstanding Technical Report. He is currently an Associate Editor for IEEE Transactions on Smart Grid.

Enrique Mallada

Enrique Mallada is an Associate Professor of Electrical and Computer Engineering at Johns Hopkins University. His technical research interests lie in control and dynamical systems, network and graph theory, mathematical optimization, machine learning, and their applications to engineering systems. He completed his Ph.D. in Electrical and Computer Engineering at Cornell. Before joining Johns Hopkins, he was a CMI Fellow at Caltech.