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I am a Staff Research Scientist and Tech lead at Runway where I work on improving quality and safety of generative models. Previously, I was a Senior Research Scientist and Tech lead at Fundamental AI Research (FAIR) in Meta AI where I worked on a broad variety of topics in Computer Vision, Machine Learning, and Image and Video Processing. My interests spans several topics such as building image and video understanding models, fair and inclusive computer vision models, ML explainability, and perceptual image and video quality.

Prior to Meta AI, I obtained my PhD at the University of Texas at Austin in 2017 where I worked with Prof. Alan Bovik on perceptual image and video quality assessment for real-world content.

News

  • I am an Area chair at WACV’24!
  • I am one of the Technical Program Chair for the conference AIMLSystems 2023
  • I am a co-organizer of XAI4CV workshop at CVPR’23!
  • I am a session chair of the featured papers panel at NeurIPS’22.
  • I moderated a panel discussion on Responsible AI research and in practice at the workshop on Responsible CV at ECCV’22.
  • I am one of the main organizers of Responsible CV at ECCV’22.
  • 2 papers accepted at ECCV’22!
  • I am serving as a Program Chair for NeurIPS’22 Datasets and Benchmarks track
  • I am serving as an Area Chair for AAAI’22, WiML workshop @ NeurIPS’21
  • 1 paper accepted at ECCV’21!
  • I am the main organizer of a full-day workshop on Responsible Computer Vision at CVPR’21!
  • 2 papers accepted at CVPR’21!
  • [March 8th, 2021] Interviewed by IIIT-Hyderabad as part of Alumni Speak series on my journey from an undergraduate student to a successful researcher link
  • 1 paper accepted in the Sign Language Recognition, Translation & Production (SLRTP) Workshop ECCV’20.
  • 3 papers accepted to CVPR’20, 1 oral acceptance.
  • 3 papers accepted to CVPR’19.

Professional Service

Short Bio

Deepti is a Staff Research Scientist and a tech lead at Runway where she focuses on improving quality and safety of generative image and video models. Previously, she was a Senior Research Scientist and a tech lead at Fundamental AI Research (FAIR) in Meta AI focusing on a broad topics in Computer Vision, Machine Learning, and Image and Video Processing. Her research interests span several topics such as building image and video understanding models, fair and inclusive computer vision models, ML explainability, and perceptual image and video quality.

Deepti served as a program chair of Neural Information Processing Systems’22 datasets and benchmarks track and AIMLsystems’23 and an area chair for several conferences such as IEEE Conference on Computer Vision and Pattern Recognition (CVPR), IEEE Winter Conference on Applications of Computer Vision (WACV), Women in Machine Learning (WiML), and Association for the Advancement of Artificial Intelligence (AAAI). She organized several workshops on the topics of responsible and explainable computer vision at top-tier machine learning conferences.