Arin Gopakumar

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 Machine Learning 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 interests center on long-range graph representation learning, state-space sequence models, and applying those methods to problems in environmental forecasting and clinical prediction.

HOPPER: Learnable Hop Extraction for Linearized Graph Sequence Models

Isuru Herath, Arin Gopakumar, Sharan Sahu

arXiv preprint, August 2026

A CNN-Based Framework for Forecasting Valley Fever Risk via Dust Detection in Arizona: A Proof of Concept

Arin Gopakumar

Poster, NewInML Affinity Event, ICML 2025

WildfireSpreadBench: The Metric Decides the Model in Wildfire Spread Prediction

Arin Gopakumar, Marco Pannozzo

In preparation

Three Routine Intraoperative Variables Predict Vasoplegia at Separation from Cardiopulmonary Bypass

Arin Gopakumar, Makenzie Higgins, Brittney Williams

In preparation