Vidrovr develops multimodal computer vision and machine learning systems to index, tag and understand video. We leverage patented supervised and unsupervised techniques to process videos with specific domain constraints, such as in sports, government and media verticals. We believe true value is generated by building systems that leverage various modalities present in video (pixels, audio and text). Currently, we are working with large media corporations to process their video collections.

The Technology

Index & search multimedia

Search an indexed video corpus and retrieve content inside videos and link it to other media: photos and text.

Extract real entities

Pull out real entities, such as people and organizations out of video streams, articles and images. This is not your old fashioned text search.

Link to real events

Link multimedia content to real news events. See how your and your friends lives are part of the world.

Social integration

Integrating social media, in order to enable direct interactions between multimedia content. Know when the news affects you and your friends.

Connect your APIs

Have a great idea how to use our system-- feel free to connect to our APIs. Use our system's capabilities to solve your problems.

Near realtime

Stream broadcast news in near realtime. We get interactive content to you as quickly as possible, so that you act on the news.

The Team

Joe Ellis


Joe is a PhD candidate at Columbia University working on video searching and indexing. He has published research in the areas of multimodal information processing, computer vision and machine learning. He has worked at Google, IBM Research, and MITRE.

Dan Morozoff


Dan is a PhD candidate at Columbia University working on machine learning applied to neuroscience. He has published research in computational physics, computer multimedia. He has worked at NASA, and HHMI Janelia.

Connor O'Day

Head of Business Development

Connor holds a Bachelor’s of Science in Business Administration from the University of Richmond. He has previously worked at Fortress Investment Group, CRT Capital Group LLC, and JP Morgan.

Prof. Shih-Fu Chang

Technical Advisor

Shih-Fu Chang is a professor School of Engineering and at Columbia University. His research focuses on multimedia information retrieval, computer vision, and machine learning with a goal to develop intelligent systems that harness information from massive visual data.

Shikha Singh


Shikha is a masters candidate at Parsons School of Design studying Design and Technology. Her primary area of focus is User Exeprience Design and Interface Design. She has previously interned with Google as a UX Designer.

Ethan Grant


Ethan is a Computer Science and Economics-Statistics double major at Columbia University specializing in artificial intelligence. During his free time he likes to read, cook, and participate in the Columbia Debate Society.


Vidrovr Wins Gold at Publicis 90

July. 2016

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.
Publicis || TechCrunch || Campaign

Vidrovr presents at NY Meetup

June. 2016

We were invited back to give a short demo of Vidrovr and our tech at the NY Tech Meetup.
NYTM || NYTM-Video

Vidrovr receives followup funding from NYC Media Lab

June. 2016

Following up on 3 months of being part of the Combine. Vidrovr is selected to receive followup funding for the incubation program.

NewsRover Team Won Two Major Challenges in Media Technologies

Feb. 2016

The NewsRover team won two major challenges sponsored by New York City Media Lab. In the Combine program sponsored by NYC Economical Development Commission, the team was selected with major funding to identify products and develop business plans impacting the media industry.

News Rover @ 2014 NYC Media Lab Annual Summit

Sep 19, 2014

The News Rover system was presented at the 2014 NYC Media Lab Annual Summit and won the second place demo prize. Click here to check the article from NYC Media Lab.

NYC Media Lab

The News Rover team presented the News Rover system @ newsKDD

Aug 24, 2014

The News Rover team presented the News Rover system at newsKDD, a KDD workshop at Bloomberg in New York City.

News Rover @ November 2013 NY Tech Meetup

Nov 4, 2013

The News Rover system was presented at the November 2013 New York Tech Meetup alongside several other projects out from the academic sector at the beautiful NYU Skirball Center For The Performing Arts. It was exciting to present our revolutionary new way of getting context for your news!

Awarded ACM Multimedia 2013 Grand Challenge 1st Place Award

Oct 25, 2013

Work on News Rover presented in part at ACM Multimedia (MM) 2013 won the Multimedia Grand Challenge 1st Place Award in Barcelona, Spain. The work was entitled “Structured Exploration of Who, What, When, and Where in Heterogeneous Multimedia News Sources”.
ACM MM 2013