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Final Program


    Shrey Sukhadia, MS, PhD (he/him/his)

    Assistant Director of Genome Informatics and Clinical Genomics and Advanced Technology, and Instructor at Pathology and Laboratory Medicine
    Dartmouth Health
    Lebanon, New Hampshire, United States

    I am an Assistant Director of Genome Informatics at Dartmouth Health, and an Instructor at Pathology and Laboratory Medicine at the Geisel School of Medicine at Dartmouth College. I am a Biomedical Informaticist and a Machine Learning Scientist. My training is in biotechnology, bioinformatics, pathomics, radiomics, machine learning, software engineering, and cloud-based operations with more than a decade of experience working in clinical laboratories analyzing omics data for cancer patients. I received a Bachelor of Engineering degree in Biotechnology from Visvesvaraya Technological University in India, and a Masters degree in Bioinformatics from the University of the Sciences in Philadephia. My PhD-training is from Queensland University of Technology in Brisbane (Australia) in collaboration with Stanford University (Stanford, USA) and was focused on conducting machine learning experiments that connect radiological, pathological and omic (i.e., genomic/proteomic-based) data together to predict treatment-response and tumor-recurrence in Breast, Head and Neck, and Lung cancers.
    I have developed and validated clinical grade infromatics solutions at various clinical laboratories in United States. I have conducted informatics evaluation and validation of whole exome sequencing and transcriptome assays for the reporting of somatic variants (such as SNVs, Indels, SVs/CNVs, Gene-fusions, TMB and MSI) in tumor specimens. My research interests include modelling radiomic, pathomic, clinicopathologic and molecular features of tumors to predict the risk of tumor-recurrence or metastases in cancer patients, using several Machine Learning and a broader set of Artificially Intelligent techniques in the most transparent and explanaible way possible, which will aid their translation in clinic, ultimately.

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    Presentation(s):