Pritish Uplavikar is a Senior Research Engineer with nine years of experience building production-ready ML and simulation systems across industry leaders like Apple, Meta, and NIO. He has delivered end-to-end pipelines that translate 2D floorplans into realistic 3D environments, drove a ~3x IoU improvement in multimodal segmentation that saved $500k+ in outsourcing, and scaled synthetic data generation for perception and RL through controllable scenario and texture-generation frameworks. His background spans computer vision, deep learning, sensor fusion and trajectory prediction, with hands-on expertise deploying models and data pipelines in production at scale. A Texas A&M CS graduate and former AI Scientist Intern, he combines rigorous research with practical engineering—often tackling data scarcity by designing annotation specs and probabilistic spawning models that enable realistic validation before real-world tests.
[CVPRW 2019] All-In-One Underwater Image Enhancement using Domain-Adversarial Learning
Contributions:7 commits, 8 pushes, 1 branch in 29 days
adversarial-learningimage-enhancement
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