Rate My Professor David Bindel

Bindel's research lies at the interface of computational science and engineering, focusing on applied numerical linear algebra and scientific computing. His interests include stellarator optimization, verified numerics, kernel methods, parallel surrogate optimization, spectral network analysis, eigenvalue problems, and applications to fusion energy, networks, and MEMS. He is a 2024 SIAM Fellow for contributions in numerical linear algebra and its innovative use in broad areas of computational science. Notable awards also include the James and Mary Tien Excellence in Teaching Award (2020), KDD Best Research Paper Award (2019), ASPLOS Most Influential Paper Award (2018), SIAG/LA Prize (2015), Sloan Research Fellowship (2010), and Alston S. Householder Award (2008). Key publications feature "Understanding trade-offs in stellarator design with multi-objective optimization" (Journal of Plasma Physics, 2023, with Matt Landreman and Misha Padidar), "Direct optimization of fast-ion confinement in stellarators" (Plasma Physics and Controlled Fusion, 2023), "Global stochastic optimization of stellarator coil configurations" (Journal of Plasma Physics, 2022, with Silke Glas et al.), and "Bayesian transformed gaussian processes" (Transactions on Machine Learning Research, 2023). Bindel has held editorial positions such as Editor of NA Digest (2024-present), Associate Editor for SIAM Journal on Matrix Analysis and Applications (2025-2028), and SIAM Journal of Scientific Computing (2021-2023). He has contributed to numerous committees, including chairing the Scientific Committee for the Householder XXIII Meeting (2028) and serving on program committees for ICML, NeurIPS, and SIAM conferences. His publications have garnered over 9,600 citations on Google Scholar.