Nicholas Giangreco

Independent and collaborative precision medicine scientist

Github | Linkedin | ORCID | nickg.bio | nick.giangreco@gmail.com | Date of preparation: October 12th 2021

Topic areas: Pediatric drug safety, Explainable machine learning, Fairness and equity in digital health, Cardiovascular biomarker development, Clinical and biomedical data management/integration/ analysis
Technical expertise: Differential expression analysis, Interpretable machine learning, Statistical simulation, Data cleaning and engineering, dashboard development, AWS/Google cloud computing, Data-driven hypothesis generation and hypothesis testing
Programming Languages: Python, R, bash
Pending patents: CU18316 Prediction of post-heart transplant primary graft dysfunction using exosome proteins
Team projects/Hackathons: 1 R package, 1 python package, 1 R Shiny App, 1 Dash/Plotly app, 6 analysis workflows in python, R, bash
Leadership roles: 3 club president, 2 treasurer, 1 501(c)(3) nonprofit secretary

WORK EXPERIENCE

2016 - Present

Systems biologist (Columbia University); New York, NY

Thesis work includes predictive analysis and detecting risk factors of adverse clinical and biomedical outcomes

February 2021 - August 2021

Bioinformatics intern (DNAnexus); San Francisco, CA

Product management

Initiating internal and external projects such as interpretable machine learning and genomic/phenomic data integration/analysis

June 2019 - August 2019

Clinical informatics intern (Regeneron Genetics Center)); Tarrytown, NY

Developed database of multivariate clinical associations using incremental learning on amazon web services.

July 2018 - September 2018

Computational biology intern (Genetic Intelligence Inc.); New York, NY

Conducted independent and collaborative genomics research using NCBI APIs and amazon web services.

2014-2019

Cancer bioinformatician (National Human Genome Research Institute); Bethesda, MD

Post-baccalaureate trainee 2014-2016; Special volunteer 2016-2019

Investigated ovarian endometrioid tumorigenesis by integrating and analyzing RNASeq and DNA methylation sequencing (MBD-Seq).

EDUCATION

2016 - Present

PhD Candidate, Systems Biology; Columbia University, New York City, NY

PhD advisor: Dr. Nicholas Tatonetti

Masters of Arts (2018) and Masters of Philosophy (2019)

2010 - 2014
BS, Biochemistry; University of Rochester, Rochester, NY

PUBLICATIONS

Peer-reviewed publications on pubmed

Google scholar profile

FELLOWSHIPS AND AWARDS

POSTERS AND SOFTWARE

Leadership and Management Experience

MENTORING, TUTORING, and WRITING

CONFERENCES AND HACKATHONS

TALKS AND PANELS

PROFESSIONAL MEMBERSHIPS