Oklahoma State University
10/15/2024 | Press release | Distributed by Public on 10/15/2024 08:16
Alumnus Nelsen making global impact in machine learning and computational science
Alumnus Nelsen making global impact in machine learning and computational science
Tuesday, October 15, 2024
Media Contact: Desa James | Communications Coordinator | 405-744-2669 | [email protected]
Dr. Nicholas H. Nelsen, a 2018 Oklahoma State University graduate, has quickly emerged as a notable figure in the fields of computational mathematics and machine learning.
His academic journey, which began with receiving three undergraduate degrees - mechanical engineering and aerospace engineering from the College of Engineering, Architecture and Technology, and mathematics from the College of Arts and Sciences- has led him on a path of success.
Currently an NSF Mathematical Sciences Postdoctoral Research Fellowat Massachusetts Institute of Technology, Nelsen's innovative work is contributing to advances in both physical sciences and engineering. Next, he is set to join Cornell University as a Klarman Fellow and the University of Texas-Austin as an assistant professor.
While in Stillwater, Nelsen developed a strong interest in applying mathematical principles to real-world problems.
"During my undergraduate studies at Oklahoma State University, I got really interested in the intersection of mathematics applied to the sciences, while still being grounded in real-world problems," Nelsen said.
"I wanted to understand these areas more deeply. A significant turning point for me was a summer I spent interning at Sandia National Laboratories, a government lab operated by the U.S. Department of Energy, in the Center for Computing Research. I began learning how to solve the underlying equations governing shallow water flows in the atmosphere, delving into numerical methods and computer simulation techniques that preserve physically important quantities."
Nicholas Nelsen | Photo by Lance HayashidaAfter completing his undergraduate studies, Nelsen pursued a master's degree at Caltech, where his focus deepened on the mathematical and statistical tools necessary for solving complex scientific challenges. In 2024, he earned his Ph.D. at Caltech under the supervision of professor Andrew Stuart.
Nelsen's doctoral work exploring the mathematical foundations of machine learning earned two "best thesis" awards - one from the applied mathematics department and another from the mechanical engineering department. His research centers on high-dimensional problems and how machine learning algorithms can be reliably applied to physical systems, such as optimizing airplane wing shapes or enhancing medical imaging techniques.
Nelsen has received multiple prestigious awards, including an NSF Graduate Research Fellowship, the Amazon AI4Science Fellowship and the SIAM Review SIGEST Award. His work has consistently been recognized for pushing the boundaries of how computational methods can solve real-world problems, from predicting weather patterns to improving the efficiency of quantum chemical calculations.
Looking ahead, Nelsen is set to start his Klarman Fellowship at Cornell University in 2025. There, he will develop a mathematical and statistical theory for scientific machine learning.In 2026, he will transition to a tenure-track assistant professor position at UT, with a joint appointment in the Oden Institute for Computational Engineering and Sciences and the Department of Aerospace Engineering and Engineering Mechanics. There, he plans to work with an interdisciplinary group of graduate students, including those from the Computational Science, Engineering, and Mathematics Ph.D. program, while also teaching both graduate-level appliedmathematics and undergraduate computational engineering courses.
As Nelsen continues to break new ground in computational mathematics and machine learning, his work promises to have a lasting impact on fields ranging from artificial intelligence to aerospace engineering. His career reflects a commitment not only to solving scientific problems but also to pushing the theoretical boundaries that underpin these solutions.
"Nicholas is an excellent example of a well-rounded education that spans college boundaries. His story underscores the importance of transdisciplinary perspectives and the imperative to work collaboratively to provide these opportunities for our students. Nicholas' significant accomplishments in machine learning and the way in which he has engaged across disciplinary boundaries and institutions speak to the incredible impact he is having on the field. We are very proud of him and his achievements as a joint product of two colleges."