PeopleofSuperintelligence

Researcher

Akshay Subramaniam

Akshay Subramaniam is an AI researcher at NVIDIA whose work applies machine learning and GPU computing to scientific simulation and weather prediction. He earned a bachelor's degree in aerospace engineering at IIT Madras in 2012 and an MS in aeronautics and astronautics at Stanford in 2014 before completing a PhD focused on turbulent flows, computational physics, numerical algorithms, high-performance computing and deep learning. He coauthored NVIDIA's GPU-accelerated Wide & Deep recommender implementation, SimNet and ClimSim; ClimSim won a 2023 NeurIPS Outstanding Paper award. His later work added hydrostatic constraints and generative AI to weather forecasting; since March 2026, he is a Principal AI Research Engineer, DevTech, at NVIDIA.

Now at
NVIDIA
Works
42
Citations
603
h-index
11
Badges

Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

  1. 2016

    Shock-induced turbulent mixing

    At Stanford, he presents a numerical study of shock-induced turbulent mixing in an inclined-interface Richtmyer–Meshkov instability in 2016.

  2. 2017

    Plastic flow at interfaces

    At Stanford's Thermal and Fluid Sciences Affiliates Program, he presents research on shock-driven plastic flow at solid-solid interfaces in 2017.

  3. 2012–2018

    Degrees before NVIDIA

    He earns a bachelor's degree in aerospace engineering at IIT Madras in 2012 and an MS in aeronautics and astronautics at Stanford in 2014. By November 2018, he completes a Stanford PhD focused on turbulent flows, computational physics, numerical algorithms, high-performance computing and deep learning, then joins NVIDIA as a senior AI developer technology engineer.

  4. 2019

    Wide & Deep on GPUs

    In 2019, he coauthors NVIDIA's GPU-accelerated Wide & Deep recommender implementation, which reduces inference latency by up to 13x or improves throughput by up to 11x against CPU baselines.

  5. 2021

    NVIDIA SimNet

    In 2021, he coauthors NVIDIA SimNet, an AI-accelerated multi-physics simulation framework.

  6. 2023

    ClimSim earns a NeurIPS award

    In 2023, he coauthors ClimSim, a large multi-scale dataset for hybrid physics-ML climate emulation. NeurIPS gives the paper its Outstanding Paper award.

  7. June 2025–November 2025

    Weather prediction at NVIDIA

    In June 2025, he coauthors a global machine-learning weather prediction study that imposes hydrostatic-balance constraints; its soft constraint improves the RMSE of many forecast fields, especially beyond 7–10 days. By November 2025, he is a senior AI developer technology engineer at NVIDIA, focused on AI-powered climate modeling and petascale data workflows. In November 2025, he coauthors NVIDIA's article 'Gen AI Super-Resolution Accelerates Weather Prediction with Scalable, Low-Compute Models.'

  8. Since March 2026

    Principal AI Research Engineer

    Since March 2026, he is a Principal AI Research Engineer, DevTech, at NVIDIA. In June 2026, he coauthors STRATA, an autoregressive AI emulator for global storm-resolving atmospheric dynamics trained on 17 days of SCREAM physics-model output at 4.9-km resolution sampled every 10 minutes.

Career

  1. Since 2026NVIDIASenior AI Developer Technology Engineer

Education

  1. 2012IIT MadrasBachelor’s degree in aerospace engineering
  2. Stanford UniversityPhD

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

  1. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes Akshay Subramaniam. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.
  2. Google has the highest combined h-index among AI organizationsIncludes NVIDIA. We estimate that Google holds the highest combined h-index at 8,016, while universities account for 73% of the deduplicated total across AI organizations.
  3. 20% of people at companies who shape AI also hold a university role, led by Google and Stanford UniversityIncludes NVIDIA. We estimate that 539 of the 6,766 people with a known current organization (8%) hold both a university role and a company role, including 20% of people at companies and 13% of people at universities.
  4. Google alumni have founded or led 133 other organizations, more than any other AI labIncludes NVIDIA. We estimate that alumni of 17 major AI labs went on to found or lead 350 other organizations, including 226 they founded, and we trace 472 career moves directly between 23 labs since 2010.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Akshay Subramaniam yet. Send us a free-licensed photo.

  1. 2016 Posters | Aeronautics and Astronautics aa.stanford.edu. Checked 22 October 2026.
  2. Presentations - 2017 | Thermal & Fluid Sciences Affiliates Program tfsa.stanford.edu. Checked 22 October 2026.
  3. A High Resolution Compact Scheme for Compressible Flows Involving Shocks and Turbulence nas.nasa.gov. Checked 22 October 2026.
  4. Presenter – SC25 Schedule sc25.conference-program.com. Checked 22 October 2026.
  5. Find Akshay Subramaniam's email & phone number - Principal AI Research Engineer, DevTech at NVIDIA, Stanford | SignalHire signalhire.com. Checked 22 October 2026.
  6. Accelerating Wide & Deep Recommender Inference on GPUs | NVIDIA Technical Blog developer.nvidia.com. Checked 22 October 2026.
  7. NVIDIA SimNet: An AI-accelerated multi-physics simulation framework | NVIDIA Learning and Perception Research research.nvidia.com. Checked 22 October 2026.
  8. ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation | NVIDIA Climate research.nvidia.com. Checked 22 October 2026.
  9. NeurIPS 2023 Awards neurips.cc. Checked 22 October 2026.
  10. Imposing the Fundamental Dynamical Constraint of Hydrostatic Balance to Improve Global ML Weather Prediction arxiv.org. Checked 22 October 2026.
  11. Gen AI Super-Resolution Accelerates Weather Prediction with Scalable, Low-Compute Models | NVIDIA Technical Blog developer.nvidia.com. Checked 22 October 2026.
  12. Scaling Storm-Resolving Atmospheric AI Simulation to the Entire Planet arxiv.org. Checked 22 October 2026.