Shravan Venkatraman

I am an M.Sc. computer vision student at MBZUAI. I am fortunate to be a part of the Intellectual and Visual Analytics Lab, where I am advised by Dr. Fahad Khan and Dr. Salman Khan. I completed my undergrad in computer science at VIT University, advised by Dr. Joe Dhanith and Dr. Pandiyaraju.

My research focuses on developing self-evolving large multimodal models for generalizable multimodal intelligence, within the broader context of multimodal representation learning for reasoning. I also work on unified large-scale models for image understanding and generation, and controllable generation of extended, coherent video sequences.

Prior to this, I was a research intern at Nagasaki University advised by Dr. Muthu Subash Kavitha. In the summer of 2024, I interned at MedxAI under the mentorship of Dr. Susan Elias and Dr. Sheena Pravin. I also work on industry- and consultancy-funded projects through SPORIC at VIT.

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EvoLMM is a fully unsupervised self-evolving framework for large multimodal models (LMMs) that improves visual reasoning from raw images only by coupling a Proposer and a Solver trained via continuous self-consistency rewards.

@misc{thawakar2025evolmmselfevolvinglargemultimodal,
  title={EvoLMM: Self-Evolving Large Multimodal Models with Continuous Rewards}, 
  author={Omkar Thawakar and Shravan Venkatraman and Ritesh Thawkar and Abdelrahman Shaker and Hisham Cholakkal and Rao Muhammad Anwer and Salman Khan and Fahad Khan},
  year={2025},
  eprint={2511.16672},
  archivePrefix={arXiv},
  primaryClass={cs.CV},
  url={https://arxiv.org/abs/2511.16672}, 
}
      

Enforcing physical surface properties through PDE constraints yields geometrically accurate neural scene representations from sparse views.

Structuring attention through multi-scale graphs enable transformers to reason across visual hierarchies.

BCSE332P - Deep Learning Lab (Fall 2024)

Yep it's another Jon Barron and Ben Mildenhall website.
Last updated July 2025.