Nicholas H.Nelsen
- nnelsen@oden.utexas.edu
- POB 6.334
Uncertainty quantification; Statistics; Applied probability; Inverse problems; Scientific machine learning
About
Nicholas Nelsen joined The University of Texas at Austin as an assistant professor in Fall 2026. He holds a joint appointment in the Department of Aerospace Engineering and Engineering Mechanics and the Oden Institute for Computational Engineering and Sciences. Before UT, he was a Klarman Fellow in the Department of Mathematics at Cornell University (2025-2026) and a National Science Foundation Postdoctoral Fellow in the Department of Mathematics at MIT (2024-2025). Nelsen earned his Ph.D. from Caltech in 2024, where his doctoral dissertation on the data efficiency of scientific machine learning was awarded the W. P. Carey Co. Prize for Best Thesis in Applied Mathematics and the Centennial Prize for the Best Thesis in MCE.
Nelsen’s research centers on the interplay between machine learning and computational science, engineering, and mathematics. He develops artificial intelligence (AI) methods for high- or infinite-dimensional problems and establishes mathematical guarantees on the reliability of these methods. His fundamental work is instated in physical, engineering, and data science applications; these include weather forecasting, fusion energy, and intelligent systems. Some of Nelsen’s specific research interests include operator learning, amortized Bayesian inference and uncertainty quantification, statistical and stochastic inverse problems, optimal sampling and experimental design, data assimilation for dynamical systems, and generative AI.
Educational Qualifications
Ph.D., California Institute of Technology
B.S., Aerospace Engineering, Oklahoma State University
B.S., Mechanical Engineering, Oklahoma State University
B.Sc., Mathematics, Oklahoma State University