Pranav Jeevan

Pranav Jeevan

PhD candidate

About Me

I am Pranav Jeevan P, working as a Research Scientist at sync. where I design generative models to control and edit human attributes in video. I completed my doctoral thesis from the Department of Electrical Engineering at Indian Institute of Technology, Bombay. My research focused on building resource-efficient neural architectures that can perform multiple computer vision tasks. I have been associated with MeDAL (Medical Imaging, Deep Learning and Artificial Intelligence Lab) and working under the supervision of Prof. Amit Sethi. I did my Masters in Robotics from the Department of Mechanical Engineering at Indian Institute of Technology, Kanpur. I was working in the Center for Mechatronics under the supervision of Prof. Ashish Dutta, where I developed a lower-extremity exoskeleton, for rehabilitation. I have been serving as a reviewer for top international conferences such as CVPR, AAAI, ICCV, ECCV, ICLR and WACV.

After completing my Masters degree, I worked as Post-graduate Engineering Trainee at Engineering Research Centre, Tata Motors Limited. I have worked on vehicle evaluation and thermal analysis of brakes in Consumer Vehicle Business Unit. After working in industry for sometime, I moved back to academic research at the Department of Physics, Indian Institute of Technology, Madras. I did coursework in theoretical physics with special focus on Quantum Computing and Quantum Information. I did a 6 month Internship with the AI Camera Team, Camera Solutions Group, Visual Intelligence Division at Samsung R&D Institute India, Bangalore (SRI-B) from July 2023 to January 2024. I worked on developing various models for tasks such a classification, detection and generation. These models have been commercialized and deployed in Samsung's flagship Galaxy S24 series.

Recent Updates

  1. Our paper “Which Backbone to Use: A Resource-efficient Domain Specific Comparison for Computer Vision” has been accepted in the TMLR Journal.
  2. Our paper “Evaluation Metric for Quality Control and Generative Models in Histopathology Images” has been accepted in ISBI 2025.
  3. Our paper “WaveMixSR-V2: Enhancing Super-resolution with Higher Efficiency” has been accepted for the AAAI 2025 Student Abstract and Poster Program (oral presentation).
  4. Our paper “FLeNS: Federated Learning with Enhanced Nesterov-Newton Sketch” has been accepted for the Special Session on Federated Learning at IEEE BigData 2024.
  5. Our paper “Adversarial Transport Terms for Unsupervised Domain Adaptation” has been accepted in ICPR 2024.
  6. My work during internship at Samsung Research was published as “PawFACS: Leveraging Semi-Supervised Learning for Pet Facial Action Recognition” at BMVC 2024. A patent has also been filed.
  7. Our paper “A Comparative Study of Deep Neural Network Architectures in Magnification Invariant Breast Cancer Histopathology Image Analysis” has been accpeted in CCIS.
  8. Our paper “Magnification Invariant Medical Image Analysis: A Comparison of Convolutional Networks, Vision Transformers, and Token Mixers” has been accepted in Bioimaging 2024 and won the Best Student Paper Award.
  9. Our paper “WaveMixSR: Resource-efficient Neural Network for Image Super-resolution” has been accepted in WACV 2024.
  10. Our paper “Heterogeneous Graphs Model Spatial Relationships Between Biological Entities for Breast Cancer Diagnosis” has been accepted in the 5th MICCAI Workshop on GRaphs in biomedicAl Image anaLysis (GRAIL) 2023.
  11. Our tiny paper “Resource-efficient Image Inpainting” has been accepted in ICLR 2023.
  12. Our paper “Resource-efficient Hybrid X-Formers for Vision” has been accepted in WACV 2022.
  13. Our paper “So You Think You’re Funny?”: Rating the Humour Quotient in Standup Comedy” has been accepted in EMNLP 2021.