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Research Area: Machine Learning, Econ and Social Sys |
Profile
Jake is a member of the Human Social Dynamics group in New York. His work involves data-driven modeling of complex systems, focusing on applications of machine learning and statistical inference to large-scale network data. He holds a B.S. in Electrical Engineering from Boston University and a Ph.D. in Physics from Columbia University.
Recent Publications, Projects and News
- Characterizing Individual Communication Patterns Dean Malmgren; Jake Hofman; Luís Amaral; Duncan Watts, KDD 2009, 2009
- Inferring the structure and scale of modular networks Jake M. Hofman; Chris H. Wiggins, 6th International Conference on Mining and Learning with Graphs, 2008 [view abstract]
- A Bayesian approach to network modularity Jake M. Hofman; Chris H. Wiggins, Physical Review Letters, 2008 [view abstract]