Surya Dheeshjith is a Senior Data Scientist based in New York with seven years of experience building scalable ML systems and research-grade deep learning models. He currently works on Core LLM and Agentic AI at Capital One, bringing research expertise from NYU where he led a 5-member team to develop ocean emulators that achieved 120× speedups and >90% correlation on key physical variables. His background spans end-to-end ML engineering—from preprocessing ~10TB of simulation data and orchestrating multi-node, multi-GPU training to experiment tracking and production-ready pipelines. Prior work includes applied research in climate emulation, self-supervised representation learning for images and videos, and building agent-based epidemic simulators and semantic segmentation models during internships. Comfortable at the intersection of research and engineering, he has a knack for turning high-dimensional scientific problems into efficient generative models and production workflows. He holds a Master's in Computer Science from NYU and a BE from RV College of Engineering.
7 years of coding experience
3 years of employment as a software developer
Master's degree Computer Science, Master's degree Computer Science at New York University
Bachelor of Engineering - BE Computer Science and Engineering, Bachelor of Engineering - BE Computer Science and Engineering at RV College Of Engineering
Episimmer is an Epidemic Simulation Framework for Decision Support. It is a highly flexible system that can be easily configured to help take decisions during an epidemic in closed communities like university campuses and gated communities.
Contributions:10 releases, 16 reviews, 506 commits in 1 year
Contributions:97 pushes, 1 branch in 3 years 3 months
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