Chris Wiggins
Associate Professor at Columbia; Adviser to the Dean for AI Strategy, Columbia College; co-founder hackNY; author, “How Data Happened” and “Data Science in Context”
- Role
- Journal of Machine Learning Research, Action Editors at Journal Of Machine Learning Research Inc
- Location
- New York, NY, US
- LinkedIn followers
- 500 followers
About Chris Wiggins
Chris Wiggins is an associate professor of applied mathematics at Columbia University and the Chief Data Scientist at the New York Times. At Columbia he is a founding member of the Department of Systems Biology, the executive committee of the Data Science Institute (http://datascience.columbia.edu/), and the Institute\'s education and entrepreneurship committees. He is also an affiliate of Columbia\'s Department of Statistics and a founding member of Columbia\'s Center for Computational Biology and Bioinformatics (C2B2). He is a co-founder and co-organizer of hackNY (http://hackNY.org), a nonprofit which since 2010 has organized once a semester student hackathons and the hackNY Fellows Program, a structured summer internship at NYC startups. Prior to joining the faculty at Columbia he was a Courant Instructor at NYU (19••••01) and earned his PhD at Princeton University (19••••98) in theoretical physics. In 2014 he was elected Fellow of the American Physical Society and is a recipient of Columbia\'s Avanessians Diversity Award.
Experience
Journal of Machine Learning Research, Action Editors
Journal Of Machine Learning Research Inc
Jan 2021 — Present · New York, NY, US
Education
Princeton University
PhD, Physics
1993 — 1998
Columbia University
BA, Physics
1989 — 1993
Skills
- Modeling
- Monte Carlo Simulation
- Data Mining
- Condensed Matter Physics
- Data Visualization
- Social Network Analysis
- Numerical Analysis
- Entrepreneurship
- Optimization
- Numerical Simulation
- Data Analysis
- Probability Theory
- Mathematics
- Recommender Systems
- Mathematical Modeling
- Bayesian Statistics
- Unix Shell Scripting
- Probability
- Statistical Inference
- Systems Biology
- Predictive Modeling
- Decision Trees
- Applied Mathematics
- Algorithms
- Physics
- Information Theory
- Data Science
- Hidden Markov Models
- Python
- R
- Latex
- Linear Algebra
- Statistical Modeling
- Time Series Analysis
- Matlab
- Computational Modeling
- Graph Theory
- Machine Learning
- Scientific Computing
- Stochastic Processes
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