Students
Mayank Agarwal
Webpage | Linkedin | Github
Mayank is a Masters in Computer Vision student at the Robotics Institute, Carnegie Mellon University. Before joining CMU, he worked as a Deep Learning Engineer at Flixstock, primarily working on Generative Adversarial Networks for photorealistic image editing solving problems in the fashion industry. Previously, he has also developed quant tools to analyze financial datasets at D.E. Shaw. Previously, he was a research intern at Video Analytics Lab, Indian Institute of Science, advised by Prof. Venkatesh Babu, where he primarily worked on single-view 3D point cloud reconstruction.
Naveen Venkat
Webpage | Google Scholar
Naveen is a MS Computer Vision student at the Robotics Institute, Carnegie Mellon University. Prior to joining CMU, he worked as a Data Scientist at Couture AI, deploying AI solutions at scale for image, audio and video domains. Even before, he contributed to the research at Video Analytics Lab, IISc Bangalore as a Research Assistant advised by Prof. Venkatesh Babu. His past works span the areas of Unsupervised Domain Adaptation, and, Adversarial Training methods.
Advisors
Shubham Tulsiani
Webpage | Google Scholar
Shubham is an Assistant Professor at Carnegie Mellon University in the Robotics Institute, where he is a part of the Computer Vision group. He is interested in building perception systems that can infer the spatial and physical structure of the world they observe. Please see these recent talks for an overview. Prior to joining CMU, he was a Research Scientist at FAIR, Pittsburgh working with Abhinav Gupta. He previously graduated from UC, Berkeley where he was advised by Jitendra Malik, and also frequently collaborated with Alyosha Efros.
Maneesh Singh
Google Scholar
Maneesh is a Principal Scientific Advisor at Motive Technologies. Previously, he was the head of Verisk Innovative Analytics (VIA), Global Research. He has over 25 years of R&D experience with 15 years of customer-focused industrial R&D experience in statistical computer vision, pattern recognition, machine learning, and reasoning frameworks, image and video analytics in the areas of multi-camera security and surveillance, aerial surveillance, advanced driver assistance and intelligent traffic control, industrial inspection, medical image processing and patient diagnostics.