Dr. Jeremy Jay - PI

I earned my Ph.D. in Computer Science from the University of Maine in 2013, while studying computational methods for large-scale comparative functional genomics underlying addiction and behavior in the Chesler group at Jackson Laboratory. Prior to that, I earned a MS in Computer Science in 2010 from the University of Tennesse while studying graph search algorithms and computational approaches to gene clustering on the supercomputers at Oak Ridge National Laboratory. But my trajectory of research truly began while completing my Bachelors in Bioinformatics from Baylor University in 2006.

Before my appointment to the Research Faculty in Bioinformatics at UNC Charlotte, I worked as part of a core service for 5 years, providing expertise and results to academic and industry clients while gaining additional insights into the challenges of data integration, workflow management, and scientific reproducibility.

Current Lab Members

Science doesn't happen in a vacuum, many of my own successes have been a result of the people who have mentored and collaborated with me over my career. I've been privileged to share my experience, mentor, and learn from some amazing students over the years:

PhD Students
  • Aneeta Uppal
    Investigating the molecular mechanisms of essential oils on human health
    2020 (expected)
  • Aaron Trautman
    Knowledge based discovery of bilateral molecular underpinnings between diet and gut microbiota
    2020 (expected)

Undergraduates/Summer Interns
  • Jacob Ferrier
    Computational methods for dataset
    identification and discovery

    c/o 2020
  • Zeke Van Dehy
    Examining historical Gene Ontology annotations and connections to predict scientific progress
    c/o 2022
  • Andrew Wilson
    Examining historical Gene Ontology annotations and connections to predict scientific progress
    c/o 2021
MS Students
  • Anusha Reddy Ginni
    Statistics for measuring rigor and reproducibility of historical biomedical data sets
    c/o 2021
  • Brendan Kearney
    Computational approaches to identify and translate biomedical data for machine learning at scale
    c/o 2022

Staff
  • Steven Blanchard
    Scientific Software Engineer
  • Alexa Sanders
    Research Associate / Curator

Former students

These folks have contributed to the lab in the past, and have now graduated or moved onto other things.

PhD Students
  • Richard Linchangco, Ph.D.
    The semantics of diet and health: Knowledge based discovery through data integration, text mining, and network analysis
    2018
Undergraduates
  • Simran Bolla
    Nutrient reaction mining for health risk estimation
    c/o 2020
  • Robert Bennett
    Exploration of telomere response to nutrition
    c/o 2021
  • Natalie Kratts
    A voting model for crowdsourced data curation
    c/o 2018
  • Kevin Selles
    Web platform and user interface for data curation
    c/o 2019
MS Students
  • Kiera Patanella
    Data mining and curation for a Nutrient Knowledgebase
    c/o 2018
  • Tyler Robbins
    Chemical-Nutrient mapping and data integration
    c/o 2017
  • Brandon Burciaga
    Nutrition Knowledgebase data warehouse
    c/o 2016
  • Samantha Kaiser
    Chemical-Nutrient mapping and data integration
    c/o 2016