Dirk Lauinger

MIT Energy Initiative and the Sloan School of Management

Friday, December 19, 2025, 11:00 - 11:59

Room 02-012, Georges-Köhler Allee 102, Freiburg 79110, Germany

 As energy systems shift from fuels to metals, the supply of which is geographically more concentrated than the supply of oil and gas, reliability and resource-efficiency become increasingly important. This talk will present how mathematical optimization methods can be used to reduce primary material needs and increase reliability by using existing resources more efficiently, for example, through vehicle-to-grid, and by reusing and recycling materials. Given the complexity of modern energy systems, these methods typically employ optimization under uncertainty and large-scale optimization for identifying efficiency gains, and material and energy flow analysis for analyzing reuse and recycling opportunities. As system complexity increases, more advanced optimization methods and models become necessary. The talk will describe such methods for (i) continuous-time constraints with functional uncertainties, which are used to model energy transport through time (storage); and (ii) mixed-integer nonlinear problems, which are used to model energy transport through space (transmission and distribution). Since energy systems are heavily regulated, sometimes with unintended consequences, we will explore how legal requirements can be modeled as mathematical constraints for policy and market design and analysis.

Dirk Lauinger is a postdoc at the MIT Energy Initiative and the Sloan School of Management researching mathematical optimization for reliable, resource-efficient energy systems with a focus on electricity storage and transportation and on translating law into math for decision-making problems. He holds a PhD in Operations Research, a M.Sc. in Energy Management and Sustainability, and a B.Sc. in Electrical Engineering, all from EPFL.