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Faculty Affiliate: Georgia Perakis, William F. Pounds Professor of Management Professor

by Michael A. Mehling on Tuesday May 12, 2015

MIT’s Center for Energy and Environmental Policy Research is delighted to welcome a new faculty affiliate: Georgia Perakis, the William F. Pounds Professor of Management and a Professor of Operations Research and Operations Management at the MIT Sloan School of Management. Perakis is a leading authority in the theory and practice of optimization and equilibrium problems, and develops optimization models for complex systems such as energy, retail, and transportation.

Born on the Greek island of Crete, Perakis developed an early fascination with mathematics. After completing her undergraduate studies in Athens, she came to the United States with a fellowship for graduate studies and eventually obtained a Ph.D. in Applied Mathematics from Brown University. Her thesis advisor was Thomas Magnanti, who later would become Institute Professor and Dean of the School of Engineering at MIT.

She joined MIT in 1995, initially as a Postdoctoral Associate and since 1998 as a member of the faculty at the MIT Sloan School of Management. An impressive list of accolades and long roster of Ph.D. students testify to her passion for both research and teaching. “This is my home – there are so many opportunities here, with different programs and centers allowing for close collaboration with industry,” she says about working at MIT. “I would miss that anywhere else.”

In her work, Perakis has frequently helped optimize processes in energy and transportation systems, yielding valuable insights for policy design and improvement. She also uses analytics to build systems that give price recommendations in the retail space. Using predictive analytics techniques, she has helped energy companies understand where corrosion or extreme weather are most likely to disrupt transmission and distribution grids for gas and electricity, allowing more efficient scheduling of emergency maintenance work.1 “Utilities have only recently begun to harness data-driven optimization models to streamline their operations”, she says. “But they definitely see the potential benefits.”

More recently, Perakis and a team of current and former students have worked on a model to optimize subsidies for green technology. “Policy makers cannot easily predict the effect of subsidies on demand and supply of green technology”, she explains, “and that makes it important to understand how consumers and producers will respond to different types of incentives.” Her model offers policy makers a tool to design subsidies that achieve green technology adoption targets at the lowest possible cost.2 Two subsequent CEEPR Working Papers build on this research by assessing the effects of competition and uncertainty on green technology adoption.

“Many challenges in energy and environmental policy are optimization problems”, Perakis points out as she describes her work. With disruptive changes across the energy sector and growing pressure to address the threat of climate change, her work has arguably never been more important.

1Mallik Angulakati et al., (2014), “Business Analytics for Flexible Resource Allocation Under Random Emergencies”, Management Science, Vol. 60, Issue 6, 1552-1573.

2Maxime C. Cohen et al., (2015), “The Impact of Demand Uncertainty on Consumer Subsidies for Green Technology Adoption”, forthcoming in Management Science (published online September 14, 2015).