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Nicholas Nelsen is a Klarman Fellow in the Department of Mathematics at Cornell University. His research interests lie in applied mathematics with a focus on statistical machine learning methods, probability, and statistics. He employs techniques from operator learning, inverse problems, and generative modeling to tackle high-dimensional challenges in computational mathematics. Nelsen's current research predominantly involves working with space probability measures and developing statistical methodologies for various applications in scientific computing. He has contributed significantly to the field with publications including works on operator learning and convergence rates in learning linear operators from noisy data, demonstrating his commitment to advancing research in applied mathematics and its intersection with data science.
Cornell University • Ithaca, NY
Conducting research in applied mathematics focusing on statistical machine learning.
Department of Architecture