Rate My Professor Lisa Kusch

Lisa Kusch is an Assistant Professor in the Department of Mathematics and Computer Science at Eindhoven University of Technology, where she is affiliated with the Computational Illumination Optics group and the Eindhoven Artificial Intelligence Systems Institute (EAISI). She earned her Dr. rer. nat. in Mathematics from Technische Universität Kaiserslautern in 2020, with a doctoral thesis titled 'Robustness Measures and Optimization Strategies for Multi-Objective Robust Design,' supervised by Dr. Nicolas R. Gauger and Prof. Dr. Andrea Walther. Prior to joining TU/e, Kusch completed her studies in Computational Engineering Science at RWTH Aachen University and served as a Postdoctoral Researcher in the Scientific Computing group at the University of Kaiserslautern. Her academic trajectory has centered on applied mathematics and computational methods for engineering challenges.

Kusch's research specializes in advanced optimization techniques for engineering design, emphasizing optimization under uncertainty, partial differential equation-constrained problems, multi-objective optimization, and one-shot methods. Her work bridges rigorous mathematical formulations with practical applications, including the design of imaging systems that balance optical performance, efficiency, and manufacturability, as well as aerodynamic shape optimization and internal flow design. Key publications include 'Design of a three-dimensional parallel-to-point imaging system using inverse methods' (2026, Journal of the Optical Society of America A), co-authored with Sanjana Verma and others; 'Adjoint-based multi-point optimization framework for mixing processes applied to a venturi mixer' (2025, Applied Thermal Engineering); 'A neural network approach for solving the Monge–Ampère equation with transport boundary condition' (2025, Journal of Computational Mathematics and Data Science); 'Neural network methods for two-dimensional finite-source reflector design' (2026, arXiv preprint); and 'Data-driven aerodynamic shape design with distributionally robust optimization approaches' (2024, Computer Methods in Applied Mechanics and Engineering). With over 16 journal articles, conference contributions, and book chapters, her contributions have garnered approximately 54 citations on the TU/e research portal. At TU/e, she teaches courses such as Calculus and Professional Portfolio, contributing to education in mathematics and computer science.