Asim Kadav

Research Interests: Content understanding and generation and efficient ML systems

News: Watch my lecture on Video understanding at Yale University, Topics in Deep Learning, Spring 2020.

Asim Kadav is an experienced technical leader with over 15 years in developing and deploying cloud and edge-based AI products and large-scale distributed systems. He has led multiple successful product launches and is a researcher with 8000+ research citations and 50+ patent filings. Most recently, Asim led teams at Samsung Research America, Freenome, and Tonal, where he focused on developing sub-1B parameter Vision-Language Models for video understanding and planning, ML models for early cancer detection and GenAI biomedical and clinical applications, and launched Tonal's first camera-based computer vision product. Before that, he led the eigen team at NEC Labs, advancing efficient image and video classification, retrieval, and pose tracking methods. With a strong background in multi-modal learning and distributed systems, he has developed and deployed several scalable video AI products. Asim's past work extends to building data center solutions, distributed file systems, and OS reliability tools, with publications in top conferences such as ICLR, CVPR, ECCV, SOSP, OSDI, and ASPLOS.

Email: firstlastname@gmail.com

Recent Publications | All, By area | Students

  • COMPOSER: Compositional Reasoning of Group Activity in Videos.
    Honglu Zhou, Asim Kadav, Aviv Shamsian, Shijie Geng, Farley Lai, Long Zhao, Ting Liu, Mubbasir Kapadia, Hans Peter Graf.
    In ECCV 2022. PDF.
  • Hopper: Multi-hop Transformer for Spatiotemporal Reasoning.
    Honglu Zhou, Asim Kadav, Farley Lai, Alexandru Niculescu-Mizil, Martin Renqiang Min, Mubbasir Kapadia, Hans Peter Graf.
    In ICLR 2021. PDF. Poster.
  • 15 Keypoints is All You Need. Michael Snower, Asim Kadav, Farley Lai, Hans Peter Graf. In CVPR 2020.PDF. Ranked #1 in PoseTrack.
  • S3VAE: Self-Supervised Sequential VAE for Representation Disentanglement and Data Generation. Yizhe Zhu, Martin Renqiang Min, Asim Kadav, Hans Peter Graf.
    In CVPR 2020. PDF.
  • Tripping Through Time: Efficient Localization of Activities in Videos. (Spotlight) Meera Hahn, Asim Kadav, James M. Rehg, Hans Peter Graf.
    In CVPR Workship on Language and Vision, 2019. Also, appears in BMVC'20. PDF.
  • Visual Entailment: A Novel Task for Fine-Grained Image Understanding. Ning Xie, Farley Lai, Derek Doran, Asim Kadav.
    In NeurIPS Workshop on Visually-Grounded Interaction and Language, 2018 (ViGIL’18). PDF.Dataset. Check out the leaderboard!
  • Teaching Syntax using Adverserial Distraction. Juho Kim, Christopher Malon, and Asim Kadav. In FEVER-EMNLP, 2018. PDF.
  • Attend and Interact: Higher-Order Object Interactions for Video Understanding. Chih-Yao Ma, Asim Kadav, Iain Melvin, Zsolt Kira, Ghassan AlRegib, and Hans Peter Graf. In CVPR, 2018. PDF. Video NEC Video. Live Demo.
  • DeepConfig: Automating Data Center Network Topologies Management with Machine Learning. Christopher Streiffer, Huan Chen, Theophilus Benson, Asim Kadav. SIGCOMM Net AI Workshop, 2018. PDF.
  • ASAP: Asynchronous Approximate Data-Parallel Computation.
    Asim Kadav and Erik Kruus. arXiv Preprint. Dec 2016. PDF. Code.

Open-source software/datasets

  • CATER-H: A more difficult CATER dataset with longer reasoning chains, ICLR 2021. Github.
  • SNLI-VE: A novel visual entailment task using image/text pairs. Github.
  • MALT-v2: A federated learning framework over RDMA and TCP. Github. Website. PDF.
  • Numerous patches to the Linux and android kernel to improve the software/hardware layer.[1][2][3][4].

Press

Service: (out of date)