Levi Waldron

Assistant Professor of Biostatistics

Ph.D Wood Science
University of Toronto

M.S Physics
University of Waterloo

B.S Physics
University of British Columbia


Dr. Waldron is active in public health data science, combining statistics and computation to address data-intensive public health problems, particularly in the field of translational cancer research. He is a technical advisor to the Bioconductor project for computational biology and the author of multiple software and data packages for genomic analysis and analysis of the human microbiome.

Prior to his work at CUNY ISPH, Dr. Waldron completed a post-doctoral fellowship at the University Health Network in Toronto, and at the Harvard School of Public Health and Dana Farber Cancer Institute.

Dr. Waldron’s implementation science expertise focuses on assessing the effectiveness of novel HIV patient care, and the clinical translation of molecular subtypes of cancer.

Key Projects:

Recent Publications: 

Raimann JG, Waldron L, Koh E, Miller GA, Sor MH, Gray RJ, Kotanko P. Meta-analysis and commentary: Preemptive correction of arteriovenous access stenosis. Hemodial. Int. 2017.

Ramos M, Schiffer L, Re A, Azhar R, Basunia A, Rodriguez C, Chan T, Chapman P, Davis SR, Gomez-Cabrero D, Culhane AC, Haibe-Kains B, Hansen KD, Kodali H, Louis MS, Mer AS, Riester M, Morgan M, Carey V, Waldron L. Software for the Integration of Multiomics Experiments in Bioconductor. Cancer Res. 2017, 77:e39–e42.

Pasolli E, Schiffer L, Manghi P, Renson A, Obenchain V, Truong DT, Beghini F, Malik F, Ramos M, Dowd JB, Huttenhower C, Morgan M, Segata N, Waldron L. Accessible, curated metagenomic data through ExperimentHub. Nat. Methods 2017, 14:1023–1024.

Re A, Waldron L, Quattrone A. Control of Gene Expression by RNA Binding Protein Action on Alternative Translation Initiation Sites. PLoS Comput Biol. 2016 Dec 6;12(12): e1005198. doi: 10.1371/journal.pcbi.1005198. E-collection 2016.

Vathipadiekal V, Wang V, Wei W, Waldron L, Drapkin R, Gillette M, Skates S, Birrer M. Creation of a Human Secretome: A Novel Composite Library of Human Secreted Proteins: Validation Using Ovarian Cancer Gene Expression Data and a Virtual Secretome Array. Clinical cancer research : an official journal of the American Association for Cancer Research. 2015; 21(21):4960-9.