Wiggins is an applied mathematician with a PhD in theoretical physics working on computational biology. His research interests includes applied mathematics, mathematical biology, biopolymer dynamics, soft condensed matter, genetic networks and network inference, and machine learning.
Wiggins received a B.A. in Physics with a minor in Math from Columbia College in 1993 and a PhD in Theoretical Physics from Princeton University in 1998. He is currently an Associate Professor in the Department of Applied Physics and Applied Mathematics at Columbia and is affiliated with Columbia's Data Science Institute, Department of Systems Biology, and Department of Statistics.
As of January 2014, he is also the Chief Data Scientist at the New York Times. He co-founded hackNY.org, an experiential learning program pairing computational and quantitative students with NYC startups via a 10-week structured internship program and twice-annual student `hackathons' (24-hour coding events).
Associate Professor, Department of Applied Physics and Applied Mathematics, and Center for Computational Biology and Bioinformatics (C2B2), Columbia University 2006-
Assistant Professor, Department of Applied Physics and Applied Mathematics, and Center for Computational Biology and Bioinformatics (C2B2), Columbia University, 2001-2006
Assistant Professor/Courant Instructor, Courant Institute, NYU, 1998-2001
Learning probabilistic phenotypes from heterogeneous EHR data, R Pivovarov, AJ Perotte, E Grave, J Angiolillo, CH Wiggins, N Elhadad, Journal of biomedical informatics 58, 156-165, 2015
Noise expands the response range of the Bacillus subtilis competence circuit, A Mugler, M Kittisopikul, L Hayden, J Liu, CH Wiggins, GM Suel, ...arXiv preprint arXiv:1508.07571, 2015
Statistical Inference for Nanopore Sequencing with a Biased Random Walk Model, KJ Emmett, JK Rosenstein, JW van de Meent, KL Shepard, CH Wiggins, Biophysical journal 108 (8), 1852-1855, 2015
Integrative analysis of T cell motility from multi-channel microscopy data using TIAM, V Mayya, W Neiswanger, R Medina, CH Wiggins, ML Dustin, Journal of immunological methods 416, 84-93, 2015
Single-molecule dataset (SMD): a generalized storage format for raw and processed single-molecule data, M Greenfeld, JW van de Meent, DS Pavlichin, H Mabuchi, CH Wiggins, …, BMC bioinformatics 16 (1), 1, 2015
Pegasus: a comprehensive annotation and prediction tool for detection of driver gene fusions in cancer, F Abate, S Zairis, E Ficarra, A Acquaviva, CH Wiggins, V Frattini, ..., BMC systems biology 8 (1), 97, 2014
Multiple LacI-mediated loops revealed by Bayesian statistics and tethered particle motion, S Johnson, JW van de Meent, R Phillips, CH Wiggins, M Lindén, Nucleic acids research, gku563, 2014
Bias in synapse stability leads to suppression of naive CD8 T cell activation by memory CD8 T cells during secondary responses (IRC9P. 709), V Mayya, E Judokusumo, R Medina, S Zairis, C Wiggins, L Kam, M Dustin, The Journal of Immunology 192 (1 Supplement), 191.10-191.10, 2014
Stylistic clusters and the Syrian/South Syrian tradition of first-millennium BCE Levantine ivory carving: a machine learning approach, AR Gansell, JW van de Meent, S Zairis, CH Wiggins, Journal of Archaeological Science 44, 194-205, 2014
Empirical Bayes methods enable advanced population-level analyses of single-molecule FRET experiments, JW van de Meent, JE Bronson, CH Wiggins, RL Gonzalez Jr, Biophysical journal 106 (6), 1327-1337, 2014
Multiple Lac-Mediated Loops Revealed by Bayesian Statistics and Tethered Particle Motion M Lindén, S Johnson, JW van de Meent, R Phillips, C Wiggins, Biophysical Journal 106 (2), 22a, 2014