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George Mohler, Associate Professor, Computer Science


B.S. Mathematics, Indiana University

Ph.D. Mathematics, University of California Santa Barbara

Courses Taught / Teaching

CSCI 52000 Computational Methods in Analysis (Fall 2017)

CSCI 49000 Intro to Data Science (Spring 2018)

Publications & Professional Activities

G. Mohler, J. Carter, R. Raje.  Improving social harm indices with a modulated Hawkes process.  submitted.

Y. Cheng, M. Dundar, G. Mohler.  A coupled ETAS-I2GMM point process with applications to fault detection.  submitted.

G. Mohler, E. McGrath, C. Buntain, and G. LaFree.  Hawkes binomial topic model with applications to coupled conflict-Twitter data.  submitted.

G. Mohler.  Learning to rank spatio-temporal event hotspots.  submitted.

G. Mohler, M. Short, P.J. Brantingham.  The concentration-dynamics tradeoff in crime hot spotting.  To appear in Unravelling the Crime-Place Connection.

C. Ramaiah, A. Tran, E. Cox, and G. Mohler.  Deep learning for driving detection from mobile phones.  KDD Workshop on Machine learning for large scale transportation systems.  2016.

G. Mohler, M. Short, S. Malinowski, M. Johnson, G. Tita, A. Bertozzi, P.J. Brantingham. Randomized controlled field trials of predictive policing.  JASA.  2015.

G. Mohler.  Learning convolution filters for inverse covariance estimation of neural network connectivity.  NIPS.  2014.

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