PeopleofSuperintelligence

Researcher

Ganapathy Krishnamurthi

Ganapathy Krishnamurthi is an AI and medical-imaging researcher who is a Professor at IIT Madras's Wadhwani School of AI and Department of Engineering Design, and a founding core faculty member at its School of Data Science and Artificial Intelligence. He earned a PhD from Purdue University in 2008, completed postdoctoral fellowships at Case Western Reserve University and the Mayo Clinic, and joined IIT Madras as an assistant professor in October 2012, where his team won the 2015 ISBI Longitudinal MS Lesion Segmentation Challenge. His research has included stacked denoising autoencoders for brain-lesion segmentation in 2016, interpretability analysis of brain-tumor networks in 2019, pre-clinical X-ray cardiac imaging in February 2022, and the Liver Tumor Segmentation Benchmark in 2023. In January 2025, he coauthored KD SAM for knowledge distillation of medical-image segmentation models, and his current research focuses on generative AI and deep learning for medical-image analysis and reconstruction.

Timeline

  1. 2008

    PhD at Purdue and US postdocs

    He earns a PhD from Purdue University in 2008 and holds an MSc in Physics from IIT Madras. He also works as a postdoctoral research fellow at Case Western Reserve University and at the Mayo Clinic in the United States.

  2. 2012–2015

    Joining IIT Madras and ISBI win

    In October 2012, he joins IIT Madras's Department of Engineering Design as an assistant professor, serving in that role until July 2018. His IIT Madras team wins the 2015 ISBI Longitudinal MS Lesion Segmentation Challenge.

  3. 2016

    Brain lesion autoencoders

    In 2016, he coauthors research that uses stacked denoising autoencoders to detect and segment brain lesions. A single-layer denoising autoencoder acts as a novelty detector trained with a mean-squared-error loss function to reconstruct non-lesion patches and identify lesion regions through reconstruction error.

  4. 2019

    Interpreting tumor networks

    In 2019, he coauthors a study that visualizes internal concepts in brain-tumor segmentation networks and measures uncertainty in their predictions.

  5. February 2022

    Pre-clinical X-ray imaging

    In February 2022, he coauthors a pre-clinical X-ray imaging study on a CMOS sensor optically coupled to a CsI scintillator that supports high-resolution 3D and functional cardiac imaging. Having become an associate professor in July 2018, he works in IIT Madras's Medical Imaging and Reconstruction Lab in the Department of Engineering Design.

  6. 2023

    The LiTS benchmark

    In 2023, he coauthors The Liver Tumor Segmentation Benchmark (LiTS), which evaluates liver and tumor segmentation methods on CT scans. The study reports 75 submitted algorithms trained on 131 CT volumes and tested on 70 unseen images.

  7. January 2025

    Distilling Segment Anything

    In January 2025, he coauthors KD SAM, a knowledge-distillation method for medical-image segmentation. It pairs mean-squared-error and perceptual losses across the encoder and decoder to preserve accuracy with fewer parameters.

  8. As of October 2026

    Professor at IIT Madras

    As of October 2026, he is a Professor at IIT Madras's Wadhwani School of AI and in the Department of Engineering Design, as well as a founding core faculty member at the School of Data Science and Artificial Intelligence. His current research interests include generative AI and deep learning for medical-image analysis and reconstruction.

Career

  1. NowIIT MadrasProfessor
  2. Department of Engineering DesignAssociate Professor
  3. Case Western Reserve UniversityPostdoctoral Research Fellow
  4. Mayo ClinicPostdoctoral Research Fellow

Education

  1. 2008Purdue UniversityPhD
  2. IIT MadrasMSc in Physics

From the biography.

  1. The United States employs an estimated 48% of people shaping AIIncludes IIT Madras. We estimate where the people shaping AI work today, how universities, companies and research institutes split across countries, and how country shares have changed since the 1960s.
  2. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes IIT Madras. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.
  3. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes IIT Madras. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  4. Google has the highest combined h-index among AI organizationsIncludes IIT Madras. We estimate that Google holds the highest combined h-index at 8,016, while universities account for 73% of the deduplicated total across AI organizations.

Sources and credits

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  1. Course Page - IIT Madras Degree Program study.iitm.ac.in. Checked 22 October 2026.
  2. Agentic AI Course | AI Agent Workflows | IITM Pravartak futurense.com. Checked 22 October 2026.
  3. Vidwan | Profile vidwan.inflibnet.ac.in. Checked 22 October 2026.
  4. MiRL Lab ed.iitm.ac.in. Checked 22 October 2026.
  5. Semi-supervised Learning using Denoising Autoencoders for Brain Lesion Detection and Segmentation arxiv.org. Checked 22 October 2026.
  6. Demystifying Brain Tumour Segmentation Networks: Interpretability and Uncertainty Analysis arxiv.org. Checked 22 October 2026.
  7. X-ray scintillator lens-coupled with CMOS camera for pre-clinical cardiac vascular imaging—A feasibility study journals.plos.org. Checked 22 October 2026.
  8. The Liver Tumor Segmentation Benchmark (LiTS) pmc.ncbi.nlm.nih.gov. Checked 22 October 2026.
  9. Efficient Knowledge Distillation of SAM for Medical Image Segmentation arxiv.org. Checked 22 October 2026.