Applied AI Researcher | Frontier AI & World Models | Scalable Vision Systems
Welcome, I’m Gajesh, an applied AI researcher with 4+ years of hands-on experience in computer vision and large-scale visual systems.
My work sits at the intersection of frontier vision research, representation learning, and real-world spatial intelligence.
I focus on building, training, and evaluating foundation-style vision models, with a strong emphasis on self-supervised learning, world models, and scalable inference — often grounded in high-resolution, large-scale visual data.
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Frontier Vision Research
Self-Supervised Learning, Representation Learning, World Models, Foundation Vision Backbones -
Applied Computer Vision
Segmentation, Detection, Dense Prediction, Super-Resolution, Vision-Language & Generative Models -
Large-Scale Spatial Systems
Earth Observation, Geospatial Intelligence, Route Optimization, Building & Infrastructure Mapping -
Scalable ML Systems
PyTorch, Dask, Xarray, Distributed Training & Inference, Cloud-native AI (AWS / GCP)
I care deeply about signal over noise, open research, and shipping real systems — from training large models to releasing datasets, weights, and reproducible code.