INSTRUCTORS

Dr. Andrew Ning is a professor in mechanical engineering at Brigham Young University with a joint appointment at the National Renewable Energy Laboratory. His research lab specializes in multidisciplinary optimization, deep learning, and aerodynamics as applied to wind energy and aircraft systems. He received a PhD in Aeronautics & Astronautics from Stanford University in 2011. He is co-author of the textbook Engineering Design Optimization and regularly teaches semester-length-graduate courses on optimization, deep learning, aerodynamics, and undergraduate courses on aircraft design and numerical methods.

Dr. Christopher Lupp is a Research Aerospace Engineer at the Air Force Research Laboratory (AFRL) in Dayton, Ohio. At AFRL Dr. Lupp leads several digital engineering and multi-disciplinary analysis and design optimization (MDO/MDAO/MADO) projects. His research interests include gradient-based and computationally distributed MDO, MDO including mission utility analyses, and geometrically nonlinear aeroelasticity. He received his Ph.D. from the Department of Aerospace Engineering at the University of Michigan, investigating the integration of nonlinear aeroelasticity into gradient-based MDO.

Dr. Ashwin Renganathan is an assistant professor in the department of aerospace engineering and the Institute of Computational and Data Sciences (ICDS) at Penn State. He directs the Computational complex engineered Systems Design Lab (CSDL) at Penn State, where his research focuses on developing scalable and theoretically sound mathematical and computational methods toward the design of complex engineered systems. He has designed and regularly teaches a graduate-level numerical optimization course every year at Penn State. He previously earned his Ph.D. in aerospace engineering at Georgia Tech and completed and postdoctoral appointment in applied mathematics from the Argonne National Laboratory.

Dr. Dan Berkenstock is a Science Fellow at The Hoover Institution and also a lecturer in the Department of Aeronautics and Astronautics at Stanford University. Dan's research focuses on the application of convex, quasiconvex, & polynomial optimization methods to the design of aerodynamic shapes. His research is primarily driven by an interest in extending the breadth of known problems that can be shown to conform to these techniques. Dan received his PhD from Stanford University in 2024, working in the Aerospace Design Laboratory with Juan Alonso. He previously received an M.S. in Aeronautics and Astronautics at Stanford University and a B.S.E in Aerospace Engineering at the University of Michigan, Ann Arbor.

Nathalie Bartoli is a research director at ONERA (French Aerospace Lab in Toulouse, France) in a team dedicated to multidisciplinary optimization and conceptual aircraft design She worked on optimization algorithms within the framework of national projects or Europeans with a joint supervision of several PhDs on these subjects. She is in charge of some courses at ISAE-SUPAERO in the field of optimization and machine learning techniques.

H Alicia Kim is a professor in the Department of Structural Engineering and the Materials Science and Engineering Program at UC San Diego. Her primary research area has been in topology optimization and computational mechanics since the 90s and has published over 250 publications. Her current research focuses on coupled multiscale and multiphysics topology optimization. She has been teaching structural and topology optimization for over 15 years, to undergraduate students at the University of Bath (UK) then to graduate students at UC San Diego (USA), as well as short courses to industry.