Supriya Patil is a machine learning and computer vision researcher with eight years of experience spanning industry and academia, currently a graduate student at Simon Fraser University. Her work focuses on understanding indoor 3D scenes, single-view scene reconstruction, and applying deep learning to temporal and networked data, with internships at Huawei, Max Planck Institute, and Adobe complementing longer research roles at IIT Hyderabad and SFU. She has published and contributed to research on trajectory representation in temporal graphs and community-based outlier detection, bringing strong theoretical grounding from an M.Tech at IIT Hyderabad and an MS thesis track at SFU. Supriya combines practical engineering—full-stack Java development and production ML prototyping—with advanced research in computer graphics and reinforcement learning. Notably, her projects bridge retrieval-and-alignment of 3D CAD models and marked temporal point processes, showing a knack for translating complex models into applied systems. Based in Vancouver and originally from India, she blends rigorous academic results with hands-on industry deliveries across diverse domains.
8 years of coding experience
8 years of employment as a software developer
Master of Technology (M.Tech.), Deep Learning, Machine Learning, Computer Vision, CGPA 9.50/10, Master of Technology (M.Tech.), Deep Learning, Machine Learning, Computer Vision, CGPA 9.50/10 at Indian Institute of Technology, Hyderabad
Bachelor’s Degree, Computer Engineering, CGPA 9.02/10, Bachelor’s Degree, Computer Engineering, CGPA 9.02/10 at Vishwakarma Institute Of Technology
M.S.-Thesis, Computer Science, 3.75/4.0, M.S.-Thesis, Computer Science, 3.75/4.0 at Simon Fraser University
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