Pradyumna Chari

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About Me

I am a third year PhD student at the Visual Machines Group, UCLA, advised by Prof. Achuta Kadambi. At VMG, we work on developing cutting-edge tools at the intersection of physics and artificial intelligence, to be applied to diverse problems in computer vision and computational imaging.

I completed my Bachelor's degree in Electrical Engineering from the Indian Institute of Technology, Madras, India, where I was the President's Gold Medal awardee for outstanding academic performance, for the year 2019. I worked on my undergraduate thesis with Prof. Kaushik Mitra at the Computational Imaging Lab in the domain of High Dynamic Range imaging.


  • August 2022: Paper accepted to UIST 2022. Details upcoming.

  • July 2022: Paper accepted to ECCV 2022.

  • May 2022: Paper accepted to SIGGRAPH 2022.

  • March 2022: Paper accepted to CVPR 2022.

  • October 2020: Our paper, Diverse RPPG: Camera-based Heart Rate Estimation for Diverse Subject Skin Tones and Scenes, is up on ArXiv.

  • Novemeber 2019: Our paper, Visual Physics: Discovering Physical Laws from Videos, is up on ArXiv.

  • October 2019: Awarded the President of India Prize, Bharat Ratna M Visvesvaraya Memorial Prize and the Siemens Prize for outstanding academic performance from IIT Madras.
    Media and Links: IIT Madras, UCLA, The Hindu, Jagranjosh

  • March 2019: Awarded the Graduate Dean's Scholars Award from the University of California, Los Angeles in 2019, in recognition of prior academic excellence.


My research interests lie at the intersection of applied deep learning and computer vision/computational imaging. My current work relates to developing novel sensing techniques for key vision tasks in healthcare and beyond. I am also interested in aspects of fairness in the era of learning-based vision systems.

In the past, I have worked on more traditional imaging projects. As part of my undergraduate thesis, I worked on developing novel regimes for HDR imaging with new camera setups. I have also worked on minor projects in lensless imaging and camera calibration regimes for large camera networks.

Selected Papers

* indicates equal contribution

MIME: Minority Inclusion for Majority Group Enhancement of AI Performance
Pradyumna Chari, Yunhao Ba, Shreeram Athreya, Achuta Kadambi
ECCV, 2022

Some inclusion of minority samples improves test error for the majority group.

Project Webpage
Blending Camera and 77 GHz Radar Sensing for Equitable, Robust Plethysmography
Alexander Vilesov*, Pradyumna Chari*, Adnan Armouti*, Anirudh B H, Kimaya Kulkarni, Ananya Deoghare, Laleh Jalilian, Achuta Kadambi
ACM Trans. Graph. (SIGGRAPH), 2022

A multimodal fusion approach between camera and radar to achieve more equitable and robust plethysmography.

Project Webpage
Synthetic Generation of Face Videos with Plethysmograph Physiology
Zhen Wang*, Yunhao Ba*, Pradyumna Chari, Oyku Deniz Bozkurt, Gianna Brown, Parth Patwa, Niranjan Vaddi, Laleh Jalilian, Achuta Kadambi
CVPR, 2022

A scalable biophysical neural rendering method to generate biorealistic synthetic rPPG videos given any reference image and target rPPG signal as input.

Project Webpage
Diverse RPPG: Camera-based Heart Rate Estimation for Diverse Subject Skin Tones and Scenes
Pradyumna Chari*, Krish Kabra*, Doruk Karinca, Soumyarup Lahiri, Diplav Srivastava, Kimaya Kulkarni, Tianyuan Chen, Maxime Cannesson, Laleh Jalilian, Achuta Kadambi
ArXiv, 2020

Identifying and solving underlying bias in remote heart rate monitoring using consumer camera systems based on noise analysis.

Project Webpage
Visual Physics: Discovering Physical Laws from Videos
Pradyumna Chari*, Chinmay Talegaonkar*, Yunhao Ba*, Achuta Kadambi
ArXiv, 2019

A novel pipeline that enables discovery of underlying parameters and equations from videos of physical phenomena.

Project Webpage

Template credits: Jon Barron