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Curriculum vitae. Full publication list is on the publications page.

General Information

Full Name Yasir Suhail, PhD
Position Assistant Professor, University of Connecticut Health Center
Email yasir.suhail@uconn.edu
Research Interests Computational modeling at cellular and tissue levels; AI over interaction networks for prognostics and -omics data; statistical models for heterotypic datasets
Funding NIH K99-R00 Pathway to Independence Award; total extramural funding $1,057,876

Education

  • 2017
    PhD, Biomedical Engineering
    Johns Hopkins University, Baltimore, MD
    • Built statistical mathematical models of biological systems at the protein interaction and paracrine communication levels.
    • Developed a quantitative model to reconstruct cell secretion dynamics on a microfabricated device, with information-theoretic bounds on the variance.
    • Developed graph theoretical models to predict novel interactions in protein interaction networks.
  • 2005
    MS, Electrical Engineering
    Michigan State University, East Lansing, MI
    • Developed and quantitatively validated signal processing algorithms to record and compress neuronal electrical spike signals in implantable neural electrode arrays.
  • 2003
    B.Tech, Electrical Engineering
    Indian Institute of Technology Delhi, New Delhi, India

Experience

  • 2025 - present
    Assistant Professor
    University of Connecticut Health Center, Farmington, CT
    • Developing prognostic models for maternal-fetal disease such as pre-eclampsia using stromal transcriptomics, with semi-supervised learning on large single cell RNAseq and graph neural networks.
    • Developing a class of -omics based cellular transcriptional-phenotypic fibroblast cell models that relate fibroblast transcriptional states to systemic disease states.
  • 2024 - 2025
    Postdoctoral Associate
    University of Connecticut Health Center, Farmington, CT
    • Investigated maternal-fetal disorders using spatial single cell transcriptomics from patient samples from the UConn Health biorepository.
    • Developed graph convolution deep learning models integrating transcriptional profiles, genetic perturbations and cellular phenotype assays.
  • 2018 - 2024
    Postdoctoral Associate
    University of Connecticut, Storrs, CT
    • Investigated comparative transcriptomics and gene regulatory mechanisms underlying the evolved resistance to invasion in stroma, with applications to placental disorders such as placenta accreta and preeclampsia.
    • Bioinformatics investigations of the effect of oscillatory hypoxic dynamics in cancer and fibroblast cells.
  • 2018
    Postdoctoral Associate
    Yale University, New Haven, CT
    • Identified the signaling niches necessary for lung development using single cell transcriptomics.
  • 2017
    Postdoctoral Associate
    Johns Hopkins University, Baltimore, MD
    • Studied the role of E-cadherin in the metastasis of breast cancer using transcriptomic analysis.

Grants Awarded

  • 2025 - 2028
    R00HD105973, NICHD (sole PI): $747,000
    • Development of a variational autoencoder generative AI model for prognosticating maternal-fetal disorders of pre-eclampsia and fetal growth disorders.
  • 2025 - 2026
    Connecticut Lion's Eye Research Foundation (co-investigator): $35,520
    • Spatial transcriptomic analysis of Proteoglycan 4 (PRG4) deficient mouse retina, towards recombinant human PRG4 as a treatment for dry AMD.
  • 2022 - 2025
    K99HD105973, NICHD (sole PI): $237,840
    • Mapping inter-cellular trophoblast-decidual signaling to its effects on invasion related maternal-fetal diseases.
  • 2024
    K99HD105973S21, NICHD (sole PI): $73,036
    • Spatial transcriptomics and investigation of primary placenta accreta patient tissue samples.

Invited Talks

  • 2020
    Prioritizing gene regulatory mechanisms for a complex phenotype using multiple species
    Center for Cell Analysis and Modeling, UConn Health
  • 2020
    Variance Estimates for an Unbiased Random Sample Strategy Based Fatality Rate for COVID-19
    Office of Biostatistics and Epidemiology, CBER, FDA
  • 2020
    Panel discussion, Workshop on Cancer and Embryo Development
    Arizona State University
  • 2018
    Deconvolution of paracrine signaling dynamics using a microprinted antibody arrays
    Center for Cell Analysis and Modeling, UConn Health
  • 2014
    De-novo Brassica napus transcriptome assembly
    Colorado State University

Peer Reviewing

  • Journal of Neuroscience Methods
  • International Journal of Molecular Sciences
  • Biotechniques
  • PLoS One
  • The Yale Journal of Biology and Medicine
  • Network Modeling Analysis in Health Informatics and Bioinformatics
  • Genes