Pushkar Shukla
पुष्कर शुक्ला

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I am a PhD student at the Toyota Technolgical Institute at Chicago working under the supervision of Dr. Matthew Turk. I work at the intersection of fairness, computer vision, and interpretability. My research broadly focuses on different aspects of Safe AI, including but not limited to bias detection and mitigation, counterfactual causal analysis, and safety evaluations. I am passionate about building solutions that bridge the gap between ethical AI development and practical applications.

Previously, I completed my Masters in Computer Science from University of California, Santa Barbara where I closely worked with Dr. William Wang on Goal-Oriented Visual Dialogue. Long back as an undergrad and then as a young reseacher I spent seven transformative years in the charming town of Roorkee, in Northern India. Those years were incredibly formative, leaving a lasting impact on my personal growth and shaping the person I am today.

When I’m not diving into research, you’ll probably find me trying out new recipes in the kitchen—experimenting with different flavors or enjoying a run/walk/hike outdoors.

You can find my curriculum vitae here.

news

Mar 12, 2025
Jan 29, 2025
  • Our work on detecting biases in AI image generators was featured in a podcast by Knowledge at Wharton —listen to the full discussion here.
Jan 14, 2025
  • I delivered a seminar talk on my research on evaluating and mitigating biases in Text-to-Image (TTI) generative models at the Infosys Center for AI at IIITD, India
Sep 30, 2024
  • I was featured on the TTIC website! Find the blog post here.
Jul 16, 2024

selected publications

  1. ECCV 2024
    TIBET: Identifying and evaluating biases in text-to-image generative models
    Aditya Chinchure*Pushkar Shukla*, Gaurav Bhatt, Kiri Salij, Kartik Hosanagar, and 2 more authors
    2024
  2. CVPR-W 2023
    CAVLI - Using Image Associations To Produce Local Concept-Based Explanations
    Pushkar Shukla, Sushil Bharati, and Matthew Turk
    In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, Jun 2023
  3. AAAI 2021
    Text-based rl agents with commonsense knowledge: New challenges, environments and baselines
    Keerthiram Murugesan, Mattia Atzeni, Pavan Kapanipathi, Pushkar Shukla, Sadhana Kumaravel, and 4 more authors
    In Proceedings of the AAAI Conference on Artificial Intelligence, Jun 2021
  4. ACL 2019
    What should I ask? using conversationally informative rewards for goal-oriented visual dialog
    Pushkar Shukla, Carlos Elmadjian, Richika Sharan, Vivek Kulkarni, Matthew Turk, and 1 more author
    ACL 2019, Jun 2019
  5. ETRA 2018
    3D gaze estimation in the scene volume with a head-mounted eye tracker
    Carlos Elmadjian, Pushkar Shukla, Antonio Diaz Tula, and Carlos H Morimoto
    In Proceedings of the Workshop on Communication by Gaze Interaction, Jun 2018
  6. CVPR-W 2018
    Automatic cricket highlight generation using event-driven and excitement-based features
    Pushkar Shukla, Hemant Sadana, Apaar Bansal, Deepak Verma, Carlos Elmadjian, and 2 more authors
    In Proceedings of the IEEE conference on computer vision and pattern recognition workshops, Jun 2018
  7. ICCV-W 2017
    A computer vision framework for detecting and preventing human-elephant collisions
    Pushkar Shukla, Isha Dua, Balasubramanian Raman, and Ankush Mittal
    In Proceedings of the IEEE international conference on computer vision workshops, Jun 2017
  8. WACV 2017
    A deep learning frame-work for recognizing developmental disorders
    Pushkar Shukla, Tanu Gupta, Aradhya Saini, Priyanka Singh, and Raman Balasubramanian
    In 2017 IEEE Winter Conference on Applications of Computer Vision (WACV), Jun 2017

patents

  1. US Patent
    Automated health condition scoring in telehealth encounters
    John O’donovan, Pushkar Shukla, Paul C McElroy, Sushil Bharati, and Marco Pinter
    In US Patent App. 16/949,370, 2021

preprints

  1. Preprint
    BiasConnect: Investigating Bias Interactions in Text-to-Image Models
    Pushkar Shukla, Aditya Chinchure, Emily Diana, Alexander Williams Tolbet, Vineeth N. Subramanian, and 3 more authors
    2025
  2. Preprint
    Utilizing Adversarial Examples for Bias Mitigation and Accuracy Enhancement
    Pushkar Shukla, Dhruv Srikanth, Lee Cohen, and Matthew Turk
    2024
  3. Preprint
    Enhancing text-based reinforcement learning agents with commonsense knowledge
    Keerthiram Murugesan, Mattia Atzeni, Pushkar Shukla, Mrinmaya Sachan, Pavan Kapanipathi, and 1 more author
    arXiv preprint arXiv:2005.00811, 2020