Arin Gopakumar

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I'm a Computer Science student at UC Berkeley, specializing in artificial intelligence and machine learning. I'm currently a Software Engineer Intern at the California Department of Industrial Relations, and I spent this past summer as a Software Engineer Intern at Solugenix, where I ran systematic benchmarks of open-source speech-to-text and text-to-speech models to determine which ones were reliable enough to ship in production-grade voice agents. My research focuses on long-range graph representation learning, state-space sequence models, and applying those methods to problems in environmental forecasting and clinical prediction.

Publications

  1. 2026
    WildfireSpreadBench: The Metric Decides the Model in Wildfire Spread PredictionArin Gopakumar, Marco PannozzoNeurIPS 2026 | Tackling Climate Change with ML Workshop
  2. 2026
    HOPPER: Learnable Hop Extraction for Linearized Graph Sequence ModelsIsuru Herath, Arin Gopakumar, Sharan SahuarXiv preprint, August 2026
  3. 2026
    Predicting Vasoplegia at Bypass Separation with Three VariablesArin Gopakumar, Makenzie Higgins, Brittney WilliamsPoster, July 2026
  4. 2025
    A CNN-Based Framework for Forecasting Valley Fever Risk via Dust Detection in Arizona: A Proof of ConceptArin GopakumarICML 2025 | NewInML Affinity Event