Rajeev Jain

Rajeev Jain

Principal Specialist, Research Software Engineering · AI Systems and Verification · HPC · Scientific Computing

The gap between prototype and production is where I work — ML training pipelines that scale on new accelerator hardware, I/O that doesn’t bottleneck at exascale, Python platforms research teams can actually maintain across institutions and years. Lately most of that is AI systems: giving agents typed, scoped, provenance-tracked tools instead of a chat box, and checking what comes back against a measurement rather than a plausible story. Writing numerical code since 2009 makes me skeptical of a plausible-looking number. Principal Specialist at Argonne National Laboratory, with a joint appointment at the University of Chicago.

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Rajeev Jain

Work

  • UXarrayLead developer · open-source climate analysis
    Python library for unstructured climate grid analysis, used at DOE labs, NCAR, and universities working with MPAS, ICON, SAM, and next-generation meshes. Conservative zonal averaging via Gauss-Legendre quadrature; grid I/O for ESMF, MPAS, SCRIP, and HEALPix; MCP server for AI-agent dataset exploration across local and HPC execution. Also the correctness and performance work underneath it: error-free-transformation arithmetic in the spherical-geometry kernels, after catastrophic cancellation inside a cross product — a difference of nearly equal products, not a running sum — drifted 0.68 m on a real Earth mesh; and a 1.67× speedup in a Numba hot path once hidden heap allocation turned out to be the cost rather than the math. Both are merged upstream (PR #1513, PR #1577); the point-in-face and face-bounds split is still in review (PR #1627). Docs · GitHub · MCP article
  • ncvisMaintainer · DOE SEATS
    NetCDF visualizer for structured and unstructured grids, C++/wxWidgets. Took over maintenance in August 2026: reviewed and merged the community pull-request backlog (1D line plots, color-scale centering, macOS XQuartz refresh, CMake link order), testing each branch on both build paths against generated netCDF fixtures. Diagnosed a macOS link failure caused by target_link_options de-duplicating repeated -framework arguments and replaced the wx-config parsing with find_package results; restored CMake 4 compatibility. GitHub
  • SFNO on AuroraIntel XPU port · Argonne Leadership Computing Facility
    PyTorch climate emulator on the Spherical Fourier Neural Operator, ported to Aurora’s Intel XPU stack for DOE exascale Earth system modeling. First stable portable DDP baseline: PMIX/PALS environment mapping, XPU/CUDA device branching, device-aware mixed precision with gradient scaling on CUDA and bf16 on Intel XPU. Measured baseline is one node, 12 XPU ranks, ~12 s steady-state epochs; full-dataset scale-up is still ahead. Article
  • FLASH-XI/O and compression lead · R&D 100 Award 2022
    Checkpoint and restart redesign for a million-line multiphysics engine. Async HDF5 with Argobots plus SZ3/ZFP compression: 40–70% checkpoint overhead reduction and 50%+ storage savings on Summit. Cross-checkpoint restart between AMReX and Paramesh — removing a hard constraint that forced full restarts when switching solvers. SC24 paper
  • CANDLE / IMPROVECore contributor · R&D 100 Award 2023
    HPO and benchmarking infrastructure for cancer drug response models, built with collaborators at Argonne, LLNL, and ORNL. 10,000+ training experiments across Summit, Theta, and Cori using Swift/T. Published in Briefings in Bioinformatics, 2026.
  • MeshKitPI and software lead · DOE NEAMS · 2009–2016
    Open-source C++ toolkit for automated nuclear reactor core mesh generation. Parallel CoreGen: 712 processors, 101 million hexahedral elements, 14 GB MONJU reactor mesh in about 7 minutes — a job the serial path couldn’t run at all. Blog post · Source

Selected papers

Full list on Google Scholar

Recent talks

Recognition

  • R&D 100, 2023 CANDLE — cancer AI infrastructure across Argonne, LLNL, and ORNL
  • R&D 100, 2022 FLASH-X — multiphysics simulation engine
  • IMR 2010 Best Paper — reactor core mesh generation with lattice hierarchy encoding
  • ATPESC 2015 Scholar — Argonne training program on extreme-scale computing

Service

  • 2026 Program committee — AgenticAI4HPC, 1st International Workshop on Agentic AI for HPC, SC26
  • 2026 Program committee — AGENT4SC, 1st Workshop on Agentic AI for Large-scale Science, IEEE eScience 2026
  • Ongoing SBIR/STTR proposal reviewer, U.S. Department of Energy · reviewer, Journal of Open Research Software

Funding

  • Active DOE SEATS — Software Ecosystem for Advancing Climate Tools and Services
  • Active NSF Raijin — collaborative research in climate model analysis
  • 2017–2023 DOE ECP CANDLE — core contributor
  • 2009–2016 DOE NEAMS — principal investigator, MeshKit

Roles

  • 2009–present Argonne National Laboratory — Principal Specialist in Research Software Engineering
  • 2023–present University of Chicago, Consortium for Advanced Science and Engineering (CASE) — Staff At-Large, cancer pharmacogenomics and Earth system science
  • 2007–2009 Arizona State University — Research and teaching assistant, structural and computational mechanics

Education

  • 2020 M.S. Computer Science — University of Chicago
  • 2009 M.S. Structural Engineering — Arizona State University
  • 2006 B.Tech. Mechanical Engineering — IIT ISM Dhanbad