Collaborative Research: CS2: On-Demand Semantic Analysis via Program Synthesis
CS2 — Correctness for Scientific Computing Systems (joint NSF/DOE) · PI Ben Greenman; Co-PIs John Regehr, Varun Shankar
Appointments
- 2023 – presentAssistant Professor, Kahlert School of Computing, University of Utah
- 2023 – presentAssociate Chair, FinTech Center, University of Utah
- 2019 – presentAdjunct Graduate Faculty, Dept. of Mathematics, Boise State University
- 2026 – presentAdvisor, Light-Hope Diagnostics, Inc.
- 2022 – 2026Associate Director, Master of Software Development, University of Utah
- 2018 – 2023Assistant Professor (Lecturer), Kahlert School of Computing, University of Utah
- 2014 – 2018Postdoctoral Researcher, Dept. of Mathematics, University of Utah
Education
- 2014PhD in Computing (Scientific Computing), University of Utah
- 2009Visiting Scholar, UC Davis Global Study Program
- 2009B.Tech., Computer Science and Engineering, SRM University
Service
- Editor, Nature Scientific Reports (2026 – present)
- Member, University Technology Commercialization Advisory Committee (2026 – present)
- Faculty Coordinator for Web & Social Media Engagement, Kahlert School of Computing (2026 – present)
- Director, Scientific Computing Track, Kahlert School of Computing (2023 – present)
- Local Arrangements Chair, International Conference on Supercomputing (ICS 2025)
- Reviewer: NeurIPS, ICLR, SISC, JCP, IJNME, J. Sci. Comput., and others
Honors
- College of Engineering Dean's Teaching Recognition (2020–21, 2021–22, 2022–23)
- Nominated, School of Computing Outstanding Teacher Award (2022)
- NSF Travel Award, PNWNAS (2012)
Active research support
On the lab site →Collaborative Research: Unified Neural Operator (UNO): Towards Trustworthy Operator Learning for Scientific Applications
DMS / CISE — Computational & Data-Enabled Science (CDS&E) · PI Varun Shankar; Co-PI Akil Narayan
Collaborative Research: SHF: Medium: SCIOPT: Toward Certifiable Compression-Aware SciML Systems
CISE/CCF — Software & Hardware Foundations (SHF: Medium) · PI Ganesh Gopalakrishnan; Co-PIs Mary Hall, Varun Shankar
AFOSR
PI
FA9550-25-1-0042
Property-preserving and multiscale operator learning for surrogate modeling
Laboratory Research Initiation Request (LRIR)
AFRL
PI
Numerical methods and scientific machine learning for composite materials and structures
Air Force Research Laboratory (subcontracts via UES and ARCTOS)
Sandia
Co-PI
Scalable operator learning and surrogate modeling
Laboratory Directed Research & Development (LDRD)
Selected talks
- Sep 2026“Interpretable Multiscale Operator Learning with Multiscale Kernel Frames”
Banff Workshop on Kernel Approximation and Gaussian Processes · invited - Jul 2026“Multiscale Operator Learning with Multiscale Kernel Frames”
WCCM-ECCOMAS · invited - Jun 2026“Property-Preserving and Multiscale Operator Learning for Surrogate Modeling”
Air Force Research Laboratory · invited - Dec 2025“Property-Preserving and Multiscale Operator Learning for Surrogate Modeling”
AFOSR PI Meeting - Apr 2025“Kernels in Numerical Methods and Operator Learning”
Caltech CMX Seminar · invited - Mar 2025“Kernel Methods for Operator Learning”
SIAM CSE 2025 · invited - Dec 2024“Kernel Methods for Operator Learning”
Colorado School of Mines, Applied Math Seminar · invited - Feb 2023“Physics-informed neural networks (PINNs) and kernel methods”
SIAM CSE 2023 · invited - Dec 2022“Accelerated training of PINNs using meshless discretizations”
NeurIPS 2022 - Aug 2022“Accelerated training of PINNs using meshless discretizations”
CRUNCH Seminar, Brown University · invited - Sep 2021“A High-Order Meshless Semi-Lagrangian Method for PDEs on Surfaces”
Dolomites Workshop on Constructive Approximation · invited - Sep 2021“Stacked surface representations for Geometric Modeling and Node Generation”
SIAM Conference on Geometric and Physical Modeling · invited - Aug 2017“KernelPack: A C/C++ library for high-order RBF-FD methods and automatic node generation”
ICERM Workshop, Brown University · invited
Minisymposia & panels organized
- Meshless Numerical Methods and Scientific Machine Learning with Kernels and Gaussian Processes
ICOSAHOM 2027 · with Oleg Davydov - Automatic Differentiation for Scientific Computing
SIAM CSE 2027 · with Nathan Willis - Kernel Methods for PDEs and ML
SIAM MDS 2026 · with Grady B. Wright - Panel: Kernel approximation and GP software — libraries, workflows, best practices (Chair)
Banff Workshop, 2026 - Recent Advances in Kernel-based Meshless Methods
Approximation Theory 16, 2019 · with Grady B. Wright - Advances in RBF and Other Meshfree Methods
SIAM CSE 2015 · with Grady B. Wright
Advising
Current PhD students: Ramansh Sharma, Matthew Lowery, Branden Frieden, Alberto Cattaneo, Andrey Pluzhnik.
Graduated mentees: Dr. Madison Cooley, Milena Belianovich, Dr. Andrew Jones, Dr. Andrew Kassen, Dr. Hallie Elich, Dr. Vidhi Zala, Sage Shaw, Daniel Malmuth, M.S. Srivatsa, Harshitha Parnandi, Roman Amici, Zixuan Zhao, Hannah Bruns.