Anirudh Bindiganavale Harish

Graduate Student@Rice.

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I’m a 2nd year PhD student in the Department of Electrical and Computer Engineering at Rice University. My interests span the areas of digital health and vital sign sensing, particularly applied to driver state sensing and patient monitoring. Additional topics I find interesting are implicit representations and self-supervised learning focused on healthcare technologies.

I graduated from UCLA with a M.S degree in 2023, where I was a part of the Visual Machines Group, advised by Prof. Achuta Kadambi. Prior to coming to UCLA, I was a Research Intern with the EdgeML team at Microsoft Research India, advised by Harsha Vardhan Simhadri and Prateek Jain. I worked on audio processing algorithms for resource constrained devices.

I also received a B.Tech degree from NITK Surathkal in 2020. During the same time, I completed my Undergraduate Thesis on Structured Light Profilometry and 3-D Registration under the supervision of Prof. Chandra Sekhar Seelamantula at the Indian Institute of Science (IISc), Bangalore.


Research Interests

I am interested in developing jointly-optimized novel hardware-software stacks to better model physical phenomena and efficiently leverage this information for downstream perception tasks. Currently, I am working on implementing the same for health-care technologies such as vital sign sensing.

In the past, as a part of my internships and undergraduate thesis, I have had the opportunity to work on a diverse set of problems ranging from depth estimation from Profilometry and 3-D reconstruction to keyword recognition, optimization and implementation of neural networks for low-resource devices and multimodal sentiment analysis.


Selected Publications

  1. Implicit neural models to extract heart rate from video
    Pradyumna Chari, Anirudh Bindiganavale Harish, Adnan Armouti, Alexander Vilesov, Sanjit Sarda, Laleh Jalilian, and Achuta Kadambi
    In European conference on computer vision 2024
  2. Blending camera and 77 GHz radar sensing for equitable, robust plethysmography
    Alexander Vilesov, Pradyumna Chari, Adnan Armouti, Anirudh Bindiganavale Harish, Kimaya Kulkarni, Ananya Deoghare, Laleh Jalilian, and Achuta Kadambi
    ACM Transactions on Graphics (TOG) 2022
    Bib