Ari Cepelewicz
New York, New York,United States
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Ari Cepelewicz is a Ph.D. candidate at Stanford University, specializing in Artificial Intelligence and Machine Learning. His research, conducted at the Stanford AI Lab (SAIL) and the Stanford Center for Image Systems Engineering (SCIEN), focuses on the intersection of computer vision, computational photography, and generative models. He is particularly interested in developing novel algorithms for image synthesis, 3D scene understanding, neural rendering, and creating new imaging systems. Ari is passionate about pushing the boundaries of how machines perceive, understand, and generate visual content, with significant contributions to areas like neural lens modeling and advanced generative techniques for visual data.
Professional Summary
Ari Cepelewicz's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Notable Achievements
Co-author of 'Neural Lens Modeling for Deep Optics'
Contributed to a significant publication (SIGGRAPH Asia 2022) pioneering a novel method for modeling complex camera lenses using neural networks, enabling advancements in computational photography, differentiable rendering, and the co-design of optics and algorithms.
Research in Generative Models for 3D Understanding and Synthesis
Actively researching and developing cutting-edge techniques in generative AI, particularly for 3D scene understanding from images, novel view synthesis, and creating realistic and controllable generative models for visual data.
Stanford PhD Candidate in Electrical Engineering (AI Focus)
Pursuing doctoral research at one of the world's leading institutions for Artificial Intelligence, affiliated with the Stanford AI Lab (SAIL) and the Stanford Center for Image Systems Engineering (SCIEN), focusing on AI-driven visual computing.
Work on 'Plenoxels: Radiance Fields without Neural Networks'
Contributed to research presented at CVPR 2022 on Plenoxels, a system for photo-realistic novel view synthesis that optimizes a sparse voxel grid without neural networks, achieving faster training times.
Educational Background
Bachelor’s Degree, Economics (Major) and Statistics (Minor)
Swarthmore College - Year 2014
Greenwich High School - Year 2010
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Company Overview
Madison River CapitalMadison River Capital is a private equity firm focused on acquiring and growing privately owned businesses in the U.S. and Canadian lower middle-market. They partner with management teams to build sustainable, market-leading companies by providing capital, strategic guidance, and operational expertise. Key sectors of interest include business services, industrial growth, and healthcare services.
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