{"id":8,"date":"2022-04-26T21:57:04","date_gmt":"2022-04-26T21:57:04","guid":{"rendered":"https:\/\/mscvprojects.ri.cmu.edu\/2022team16\/?page_id=8"},"modified":"2022-12-21T04:20:58","modified_gmt":"2022-12-21T04:20:58","slug":"team","status":"publish","type":"page","link":"https:\/\/mscvprojects.ri.cmu.edu\/2022team16\/team\/","title":{"rendered":"Team"},"content":{"rendered":"\n

Students<\/h2>\n\n\n\n

<\/p>\n\n\n\n

\"\"<\/figure><\/div>\n\n\n\n

Mayank Agarwal<\/strong>
Webpage<\/a> | Linkedin<\/a> | Github<\/a><\/p>\n\n\n\n

Mayank is a Masters in Computer Vision student at the\u00a0Robotics Institute<\/a>,\u00a0Carnegie Mellon University<\/a>. Before joining CMU, he worked as a Deep Learning Engineer at\u00a0Flixstock<\/a>, 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\u00a0D.E. Shaw<\/a>. Previously, he was a research intern at Video Analytics Lab<\/a>,\u00a0Indian Institute of Science<\/a>, advised by\u00a0Prof. Venkatesh Babu<\/a>, where he primarily worked on single-view 3D point cloud reconstruction.
<\/p><\/p>\n\n\n\n

\n\n\n\n
\"\"<\/figure><\/div>\n\n\n\n

Naveen Venkat<\/strong>
Webpage<\/a> | Google Scholar<\/a><\/p>\n\n\n\n

Naveen is a MS Computer Vision student at the Robotics Institute<\/a>, Carnegie Mellon University<\/a>. Prior to joining CMU, he worked as a Data Scientist at Couture AI<\/a>, deploying AI solutions at scale for image, audio and video domains. Even before, he contributed to the research at Video Analytics Lab, IISc Bangalore<\/a> as a Research Assistant advised by Prof. Venkatesh Babu<\/a>. His past works span the areas of Unsupervised Domain Adaptation, and, Adversarial Training methods. <\/p><\/p>\n\n\n\n

Advisors<\/h2>\n\n\n\n
\"\"<\/figure><\/div>\n\n\n\n

Shubham Tulsiani<\/strong>
Webpage<\/a> | Google Scholar<\/a><\/p>\n\n\n\n

Shubham is an Assistant Professor at Carnegie Mellon University in the Robotics Institute<\/a>, where he is a part of the Computer Vision group<\/a>. He is interested in building perception systems that can infer the spatial and physical structure of the world they observe. Please see these recent<\/a> talks<\/a> for an overview. Prior to joining CMU, he was a Research Scientist at FAIR<\/a>, Pittsburgh working with Abhinav Gupta<\/a>. He previously graduated from UC, Berkeley where he was advised by Jitendra Malik<\/a>, and also frequently collaborated with Alyosha Efros.<\/a><\/p><\/p>\n\n\n\n

<\/p>\n\n\n\n

\"maneesh-pic.png<\/figure><\/div>\n\n\n\n

Maneesh Singh<\/strong>
Google Scholar<\/a><\/p>\n\n\n\n

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.<\/p><\/p>\n","protected":false},"excerpt":{"rendered":"

Students Mayank Agarwal Webpage | Linkedin | Github Mayank is a Masters in Computer Vision student at the\u00a0Robotics Institute,\u00a0Carnegie Mellon University. Before joining CMU, he worked as a Deep Learning Engineer at\u00a0Flixstock, primarily working on Generative Adversarial Networks for photorealistic image editing solving problems in the fashion industry. Previously, he has also developed quant tools … <\/p>\n

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