Vidrovr develops end-to-end video search and understanding solutions that help companies index and manage their live stream and archival video content. Vidrovr provides a solution that can be customized to match a companies business goals and needs. Machine Learning solutions are not the same as traditional SaaS solutions, and therefore should not be implemented or utilized in the same way. Vidrovr works directly with customers to understand the problems that they are trying to solve, and then implements with the customer a "managed" service that leverages Vidrovr's proprietary video understanding and search solution to meet those business needs. Our team has deep expertise in machine learning, video understanding, and multimedia retrieval from our time working at the world's leading machine learning companies and academic research labs.
Vidrovr is selected as one of the recipients of the National Science Foundation (NSF) Small Business Innovation Research (SBIR) grant for video understanding. The title of the proposal being: Automatically Generating Domain Speciﬁc Structured Ontologies for Video.NSF Medium
Vidrovr is selected as one of the top 12 teams out of 3500+ world applicants to receive funding from Publicis Groupe in their Publicis 90 Startup Competition.TechCrunch
Joe is the CEO and Co-Founder of Vidrovr, an enterprise video search company making video as searchable as the web. While a PhD candidate at Columbia University he published research in the areas of multimodal information processing, computer vision and machine learning, and has received a patent in the field of video search. Previously, he worked at Google, IBM Research, and MITRE.
Dan is a former PhD candidate at Columbia University who worked on machine learning applied to neuroscience. He has published research in computational physics, computer multimedia. Previously, he worked at NASA, and HHMI Janelia.
Connor holds a Bachelor's of Science in Business Administration from the University of Richmond. Previously, he worked at Fortress Investment Group, CRT Capital Group LLC, and JP Morgan.
Gianni researches machine learning algorithms for video representation and classification. He has a MA in psychology from NYU and a BA in chemistry from Brown University. Previously, he developed behavioral experiments and computational models to study human decision-making in strategy games.
Chong holds MS degree in Digital Media from Georgia Tech, BA in filmmaking from Tongji University. Previously, he worked at GoPro.
Oren Weingrod is a full-stack engineer and former Philosophy student. Previously, he worked at Siberia as an Engineering Associate.
Mihir holds MS degree in Electrical Engineering from NYU, Bachelor of Engineering degree from Pune University. Previously, he worked at EyeLock.