Fellow, Association for Computing Machinery (ACM), 2024
Test of Time Award, RECOMB Conference, 2023
Test of Time, Runner Up, RECOMB Conference, 2022
Innovator Award, International Society for Computational Biology (ISCB), 2021
Best Paper, Runner Up, RECOMB Conference, 2021
Fellow, International Society for Computational Biology (ISCB), 2020
AACR Team Science Award, 2020
Best Paper, RECOMB Conference, 2013
NSF CAREER Award, 2011
Sloan Research Fellowship in Computational & Evolutionary Molecular Biology, 2010–2012
Research Experience
Joined Princeton University as Professor of Computer Science in 2016
Previously served on the faculty at Brown University in the Department of Computer Science and the Center for Computational Molecular Biology (CCMB) for a decade (approx. 2006–2016)
Directed the CCMB at Brown University from 2013 to 2016
Associated Faculty at Princeton’s Lewis-Sigler Institute for Integrative Genomics, Omenn-Darling Bioengineering Institute, and Center for Statistics and Machine Learning
Affiliate Faculty at Rutgers Cancer Institute of New Jersey, Irving Institute for Cancer Dynamics (Columbia University), and New York Genome Center
Background
Research focuses on the design and application of computational methods to analyze large-scale biological data
His group employs diverse computational approaches including combinatorial optimization, graph algorithms, machine learning, and statistical methods
Recent research emphases include cancer evolution, network/pathway analysis of genetic variants, and structural variation in human and cancer genomes
His algorithms have been used in multiple projects from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC)
Co-led the TCGA Pancreatic Adenocarcinoma project and the network analysis in the ICGC Pan-Cancer Analysis of Whole Genomes (PCAWG)
Professor of Computer Science at Princeton University, with affiliated faculty appointments across multiple interdisciplinary institutes