Nate Veldt

 

My research focuses on combinatorial algorithms and computational methods for data analysis, especially data that can be modeled by a graph or network. This combines interests in CS theory, computational science, discrete mathematics, and various data science applications. I received the 2025 AFOSR Young Investigator Award to fund my research on hypergraph measures and algorithms, and in 2023 I received the SIAM Early Career Award in Applied and Computational Algorithms for my research on graph and hypergraph clustering and partitioning. My research is also funded by the Army Research Office, the Department of Energy, and by subcontracts from Lawrence Livermore National Laboratory. I received my PhD from Purdue University in 2019, and a Bachelor’s in Mathematics from Wheaton College in 2013. [third person bio]

I am currently looking for a postdoc to join my group starting in Fall 2026. The position will focus broadly on algorithms for analyzing large networked systems (graphs, hypergraphs, simplicial complexes), with a particular focus on randomized algorithms and techniques that better incorporate domain knowledge. Interested applicants can send application materials (CV, transcripts, and a research statement directly to me).

New and Events

• January 2026.Our paper Better Learning-Augmented Spanning Tree Algorithms via Metric Forest Completion was accepted for publication at ICLR 2026. Congrats to Tommy! Tommy will be traveling to Rio de Janeiro, Brazil, to present results at the conference in April 2026
• January 2026. Our paper An Improved Combinatorial Algorithm for Edge-Colored Clustering in Hypergraphs was accepted as a short paper at the ACM Web Conference. Congrats to lead author Seongjune!
• January 11-14, 2026. I had the pleasure of traveling to SIAM SODA/SOSA/ALENEX in Vancouver, Canada, where I served as PC co-chair of ALENEX, and also presented a paper at SOSA.
• December 15, 2025. I’m excited to be part of the recently funded SciDAC institute funded by the Department of Energy, on LEarning Accelerated Domain Science (LEADS). The new institute is led by Pacific Northwest National Laboratory, see a synopsis here. I will be part of a team focused on making combinatorial machine learning techniques more accessible to domain scientists.
• December 10, 2025. Vedangi Bengali successfully passed her preliminary exam. Congrats, Vedangi!
• November 3, 2025. I’m honored to receive a Montague Center for Teaching Excellence Scholar award for undergraduate teaching.

See here for earlier news.