Sayan Ghosal bio photo

Sayan Ghosal

Computational Scientist
Broad Institute
Cambridge, U.S.A

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Publications & Patents

Patents

  1. Ghosal, S., Jacob, A. J., Sharma, P., & Gulsun, M. A. (2023). Subpopulation Based Patient Risk Prediction Using Graph Attention Networks. US Patent App. 17/647,613.

Journal Articles

  1. Sayan Ghosal, Michael C. Schatz, Archana Venkataraman, BEATRICE: Bayesian Fine-mapping from Summary Data using Deep Variational Inference.
    Under review for PLOS Genetics, 2023.

  2. Sayan Ghosal, Qiang Chen, Giulio Pergola, Aaron L. Goldman, William Ulrich, Karen F. Berman, Giuseppe Blasi, Leonardo Fazio, Antonio Rampino, Alessandro Bertolino, Daniel R. Weinberger, Venkata S. Mattay, Archana Venkataraman, A generative-discriminative framework that integrates imaging, genetic, and diagnosis into coupled low dimensional space, NeuroImage, Volume 238, 2021.

  3. Sayan Ghosal, Nilanjan Ray Deep deformable registration: Enhancing accuracy by fully convolutional neural net
    Pattern Recognition Letters, 2017.


Conference Publications

  1. Sarah Wu, Archana Venkataraman, Sayan Ghosal. GIRUS-net: A Multimodal Deep Learning Model Identifying Imaging and Genetic Biomarkers Linked to Alzheimer’s Disease Severity.
    EMBC, 2023.

  2. Sayan Ghosal, Giulio Pergola, Qiang Chen, Aaron Goldman, William Ulrich, Daniel R Weinberger, Archana Venkataraman
    A Biologically Interpretable Graph Convolutional Network to Link Genetic Risk Pathways and Neuroimaging Phenotypes of Disease
    Accepted at ICLR 2022

  3. Akos Varga-Szemes, Teodora Chitiboi, U. Joseph Schoepf, Athira J Jacob, Sayan Ghosal, Fei Xiong, Puneet Sharma, Jonathan Aldinger, and Tilman Emrich
    Cine Image Based Cardiac Disease Classification Using Random Forest Classifier and Graph Based Deep Learning Approach
    ISMRM 2022

  4. Sayan Ghosal, Qiang Chen, Giulio Pergola, Aaron L. Goldman, William Ulrich, Karen F. Berman, Giuseppe Blasi, Leonardo Fazio, Antonio Rampino, Alessandro Bertolino, Daniel R. Weinberger, Venkata S. Mattay, and Archana Venkataraman
    G-MIND: An End-to-End Multimodal Imaging-Genetics Framework for Biomarker Identification and Disease Classification
    Proc. SPIE, Medical Imaging 2021 [Selected for Special Oral Presentation, Deep Dive] - Best Paper Award.

  5. Sayan Ghosal, Qiang Chen, Aaron L. Goldman, William Ulrich, Karen F. Berman, Daniel R. Weinberger, Venkata S. Mattay, and Archana Venkataraman
    Bridging Imaging, Genetics, and Diagnosis in a Coupled Low- dimensional Framework
    MICCAI, 2019 [Acceptance Rate ≈ 30%] – Early Acceptance (Top 18% of Submissions)].

  6. Sayan Ghosal, Qiang Chen, Aaron L. Goldman, William Ulrich, Daniel R. Weinberger, Venkata S. Mattay, and Archana Venkataraman
    A Generative-Predictive Framework to Capture Altered Brain Activity in fMRI and its Association with Genetic Risk: Application to Schizophrenia.
    Proc. SPIE, Medical Imaging 2019.

  7. S. Ghosal, S. Banerjee, N. Tiso, E. Grisan and A. S. Chowdhury
    A novel non-rigid registration algorithm for zebrafish larval images
    EMBC, 2017.