Vidrovr is an enterprise video search platform that’s reimagining content discovery for videos.
Historically video search relied on high-level metadata that made it hard to deliver quality results. We built Vidrovr to change that. Leveraging computer vision and machine learning, the platform creates a granular, searchable index of every clip in a video library. Through front and backend search solutions, we help editors and consumers alike find exactly what they’re looking for--and what they didn’t even know existed. We also provide search tools to help content creators better monetize their video libraries and drive significant incremental ad revenue on O&O properties and in social.
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.
Haley holds a Bachelor’s of Art from Ohio University, where she studied Psychology and Sales. Previously, she worked at CloserIQ.
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.