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• Abstract

  Our life and survival depend on energy. Energy is fundamental for meeting society’s need for heating and cooling, communications, health care, transportation, agriculture, manufacturing, and almost every other realm of human endeavour. There are dramatic economic, health and safety consequences when supply fails, as evidenced for example by the April 2025 blackout in the Iberian peninsula. At the same time, energy acquisition and use impact our natural environment. In particular, air pollution is the cause of millions of deaths each year, and the main culprit is the emission of small particles from power plants, factories, vehicle exhausts, and burning coal and wood. Another well-known concern are the global energy-related CO2 emissions. Increasing the use of electricity to meet our various needs is key to achieving major reductions of these emissions. Electric energy thus plays a fundamental role in our contemporary energy systems. As we aim to reduce the environmental impact of human activity, a historical energy transition is under way. Two simultaneous trends in this transition are: 1. more and more electricity is sourced from renewable sources and 2. the demand for electricity increases as it replaces the use of fossil fuels. This transition raises several major challenges for electric power systems. We will provide an overview of energy systems, highlight successful uses of OR in practice for system operations and policy-making, and review some of the main challenges currently being addressed by OR researchers
• Biography

   

  Miguel F. Anjos holds the Chair of Operational Research at the School of Mathematics, University of Edinburgh, U.K. He previously held faculty positions at Polytechnique Montreal, the University of Waterloo, and the University of Southampton. He is the Founding Academic Director of the Trottier Institute for Energy at Polytechnique Montreal. His accolades include an Inria International Chair, a Canada Research Chair, the NSERC-Hydro-Quebec-Schneider Electric Industrial Research Chair, a Humboldt Research Fellowship, INFORMS and IEEE Senior Memberships, and the Queen Elizabeth II Diamond Jubilee Medal. He is a Fellow of EUROPT and of the Canadian Academy of Engineering.

  The research interests of Professor Anjos are in mathematical optimization and its industrial applications. He has published four books and more than 100 scientific journal articles, and has led research collaborations with companies such as EDF, Hydro-Quebec, National Grid ESO (now NESO), Rio Tinto, and Schneider Electric. He was the Editor-in-Chief of Optimization and Engineering, is currently Area Editor for the Journal of Optimization Theory and Applications and for RAIRO-OR, and is a member of several other editorial boards. Professor Anjos currently serves as Chair of the Mathematical Optimization Society, INFORMS Vice-President for International Activities, and member of the Managing Boards of the EURO Working Groups on Continuous Optimization and on Stochastic Optimization. He previously served as President of the INFORMS Section on Energy, Natural Resources, and the Environment, on the Council of the Mathematical Optimization Society, as Program Director for the SIAM Activity Group on Optimization, and as Vice-Chair of the INFORMS Optimization Society

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• Abstract

  Continuous optimization is a mature field, which has recently undergone major expansion and change. One of the key new directions is the development of methods that do not require exact information about the objective function. Nevertheless, the majority of these methods, from stochastic gradient descent to "zero-th order" methods use some kind of approximate first order information. We will overview different methods of obtaining this information, including simple stochastic gradient via sampling, robust gradient estimation in adversarial settings, traditional and randomized finite difference methods and more. We will discuss what key properties of these inexact, stochastic first order oracles are useful for convergence analysis of optimization methods that use them.
• Biography

  Katya Scheinberg is a Coca-Cola Foundation Chair and Professor at the H. Milton Stewart School of Industrial and Systems Engineering   Georgia Institute of Technology.   Prior to joining Georgia Tech she held  positions at Cornell and Lehigh Universities and at IBM T.J. Watson Research Center. She attended Moscow University for her undergraduate studies and received her PhD degree from Columbia University. 

  Katya’s main research areas are related to developing practical algorithms (and their theoretical analysis) for various problems in continuous optimization, such as convex optimization, derivative free optimization, machine learning, quadratic programming, etc.

  She is an Informs Fellow, a recipient of the Lagrange Prize from  SIAM and MOS, the Farkas Prize from Informs Optimization Society and the Outstanding Simulation Publication award from Informs Simulation Society.   Katya is currently the editor-in-chief of Mathematics of Operations Research, and co-editor of Mathematical Programming. She is a Chair-Elect of the Mathematical Optimization Society.

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• Abstract

  TBD
• Biography

   

  Dr. Karen Smilowitz is the James N. and Margie M. Krebs Professor in Industrial Engineering and Management Science at Northwestern University, with a joint appointment in the Operations group at the Kellogg School of Management.

  Dr. Smilowitz is an expert in modeling and solution approaches for logistics and transportation systems in both commercial and nonprofit applications. She has been instrumental in promoting the use of operations research within the humanitarian and nonprofit sectors through the Woodrow Wilson International Center for Scholars, the American Association for the Advancement of Science, and the National Academy of Engineering, as well as various media outlets.

  Dr. Smilowitz is the Editor-in-Chief of Transportation Science and a Fellow of the INFORMS society.