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RaoUmer/README.md

Rao Muhammad Umer

My research focuses on developing next-generation foundation models for cancer diagnostics by integrating heterogeneous biomedical data and agentic AI systems. My goal is to advance translational healthcare by designing robust, scalable AI methods that improve diagnostic accuracy and support clinical decision-making. I have led and contributed to end-to-end AI projects, spanning model development, deployment, and interdisciplinary collaboration with clinical and research teams. I am particularly interested in building AI systems that bridge methodological innovation and real-world clinical impact, while fostering collaborative, open, and inclusive research environments.


News

  • The training and inference codes of LymphomaMIL (CVPR Workshops 2026) has been released!

  • The training and inference codes of CytoDiff (ICCV Workshops 2025) has been released!

  • The testing/inference codes of RBSRICNN (NeurIPS Workshops 2021) has been released!

  • For reproducibility, run inferences of SR models in the browser and docker image hosted on replicate.ai for the SRResCGAN, SRResCycGAN, and ISRResCNet!


🌱 My Repositories 🌱


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  1. SRResCGAN SRResCGAN Public

    Code repo for "Deep Generative Adversarial Residual Convolutional Networks for Real-World Super-Resolution" (CVPRW NTIRE2020).

    Python 98 17

  2. SRResCycGAN SRResCycGAN Public

    Code repo for "Deep Cyclic Generative Adversarial Residual Convolutional Networks for Real Image Super-Resolution" (ECCVW AIM2020).

    Python 47 10

  3. ISRResCNet ISRResCNet Public

    Code repo for "Deep Iterative Residual Convolutional Network for Single Image Super-Resolution" (ICPR 2020).

    Python 5 2

  4. RBSRICNN RBSRICNN Public

    Code repo for "RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network" (Machine Learning and the Physical Sciences workshop in NeurIPS 2021).

    Python 6 3

  5. dwx dwx Public

    Deep Web Extractor (DWX): Deep Web Extractor system is using statistical machine learning models for crawling and data discovery from the Deep Web (i.e., massive and quality portion of World Wide W…

    HTML 5 2