Samarth Mishra

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Samarth Mishra,
PhD Student in Computer Science at Boston University,
Advisors : Prof. Venkatesh Saligrama & Prof. Kate Saenko

I am on the market for full-time industry positions starting fall 2024.
Feel free to reach out if you think I am a fit!


Master's Advised by Prof. James M. Rehg Georgia Institute of Technology 2017-2019
Bachelor's Advised by Prof. Suyash P. Awate IIT Bombay 2013-2017

Research Interests

Computer Vision, Machine Learning, Large Multimodal Models, Synthetic Data



  • H. Zhong, Samarth Mishra, D. Kim, S. Jin, R. Panda, H. Kuehne, L. Karlinsky, V. Saligrama, A. Oliva and R. Feris.
    Learning Human Action Recognition Representations Without Real Humans.
    NeurIPS 2023 D&B [openreview] [arxiv] [github]

  • Y. Kim, Samarth Mishra, S. Jin, R. Panda, H. Kuehne, L. Karlinsky, V. Saligrama, K.Saenko, A. Oliva, R.S. Feris.
    How Transferable are Video Representations Based on Synthetic Data?
    NeurIPS 2022 D&B [openreview] [github]

  • Samarth Mishra, R. Panda, C.P. Phoo, C.F. Chen, L. Karlinsky, K. Saenko, V. Saligrama, and R.S. Feris.
    Task2Sim: Towards effective pre-training and transfer from synthetic data.
    CVPR 2022 [arxiv] [project page]

  • D. Bashkirova, D. Hendrycks, D. Kim, Samarth Mishra, K. Saenko, K. Saito, P. Teterwak, and B. Usman.
    Visda-2021 competition : Universal domain adaptation to improve performance on out-of-distribution data.
    NeurIPS 2021 Competitions Track. [arxiv] [competition page]

  • Samarth Mishra, K. Saenko, and V. Saligrama.
    Surprisingly Simple Semi-Supervised Domain Adaptation with Pretraining and Consistency.
    BMVC 2021 [arxiv] [github]

  • Samarth Mishra, Z. Zhang, Y. Shen, R. Kumar, V. Saligrama, and B. Plummer.
    Effectively leveraging attributes for visual similarity.
    ICCV 2021 [arxiv] [github]

  • S. Stojanov, Samarth Mishra, N.A. Thai, N. Dhanda,
    A. Humayun, L.B. Smith, C. Yu, and J. M. Rehg.
    Incremental Object Learning from Contiguous Views.
    Oral, Best paper finalist CVPR 2019 [cvf] [project page]

  • K. Chatterjee, B. Kragl, Samarth Mishra, A. Pavlogiannis.
    Faster Algorithms for Weighted Recursive State Machines.
    ESOP 2017 [arxiv]


  • Samarth Mishra, P. Zhu, V. Saligrama.
    Learning Compositional Representations for Effective Low-Shot Generalization.
    IEEE Transactions on Pattern Analysis and Machine Intelligence. [arxiv]


  • D. Kim, K. Saito, Samarth Mishra, S. Sclaroff, K. Saenko, and B.Plummer.
    Self-supervised visual attribute learning for fashion compatibility.
    ICCV 2021 VIPriors Workshop [arxiv]

  • P. Zhu, R. Zhu, Samarth Mishra, and V. Saligrama.
    Low dimensional visual attributes: An interpretable image encoding.
    ICPR 2020 EDL/AI Workshop [springer]


  • Samarth Mishra, C. Castillo, H. Wang, K. Saenko, V. Saligrama.
    SynCDR : Training Cross Domain Retrieval Models with Synthetic Data.

Relevant Coursework

Boston University

  • Towards Universal Natural Language Understanding

  • Reinforcement Learning

  • Statistical Learning Theory

Georgia Tech

  • Machine Learning

  • Numerical Linear Algebra

  • Machine Learning Theory

IIT Bombay

  • Advanced Machine Learning (Probabilistic Graphical Models and Deep Learning)

  • Foundations of Intelligent and Learning Agents

  • Algorithms in Medical Image Processing

  • Digital Image Processing