G. Mohler, E. McGrath, C. Buntain, and G. LaFree.  Hawkes binomial topic model with applications to coupled conflict-Twitter data.  Annals of Applied Statistics.  In press.

X. Liu, J. Carter, B. Ray, and G. Mohler.  Point process modeling of drug overdoses with heterogeneous and missing data.  Annals of Applied Statistics.  In press.

Andrea L Bertozzi, Elisa Franco, George Mohler, Martin B Short, Daniel Sledge. The challenges of modeling and forecasting the spread of COVID-19, Proceedings of the National Academy of Sciences, 117 (29), 16732-16738.

H. Sha, M. Al Hasan, P.J. Brantingham, and G. Mohler.  (2020).  Dynamic topic modeling of the COVID-19 Twitter narrative among U.S. governors and cabinet executives.  5th International Workshop on Social Sensing (SocialSens 2020).

Mohler, G., Bertozzi, A., Carter, J.G., Short, M.B., Sledge, D., Tita, G., Uchida, C. and Brantingham, P.J.  (2020).  Impact of social distancing during COVID-19 pandemic on crime in Los Angeles and Indianapolis.  Journal of Criminal Justice.  68, 2020.

K. Gray, D. Smolyak, S. Badirli, and G. Mohler.  Coupled IGMM-GANs for deep multimodal anomaly detection in human mobility data.  ACM Transactions on Spatial Algorithms and Systems.  6 (4), 1-14.

G. Mohler, M. Porter, J.G. Carter and G. LaFree.  Learning to rank spatio-temporal hotspots (journal version).  Crime Science. 9 (1), 1-12.


W. Chiang, B. Yuan, H. Li, B. Wang, A. Bertozzi, J. Carter, B. Ray, and G. Mohler.  System for Overdose Spike Early Warning using Drug Mover’s Distance-based Hawkes Processes.  ECML-PKDD Workshop on Data Science for Social Good.  2019.

G. Mohler, P.J. Brantingham, J. Carter and M.B. Short.  Reducing bias in estimates for the law of crime concentration.  Journal of Quantitative Criminology (2019), DOI: 10.1007/s10940-019-09404-1.

Stanhope, A., Sha, H., Barman, D., Al Hasan, M., & Mohler, G.  Group Link Prediction. In 2019 IEEE International Conference on Big Data (Big Data) (pp. 3045-3052). IEEE.

A. Morehead, L. Ogden, G. Magee, R. Hosler, B. White, and G. Mohler.  Low cost gunshot detection using deep learning on the Raspberry Pi.  2019 IEEE International Conference on Big Data (Big Data). IEEE, 2019.

J. Lu, S. Sridhar, R. Pandey, M. Al Hasan, and G. Mohler,  Investigate Transitions into Drug Addiction through Text Mining of Reddit Data.  Proceedings of 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, (KDD 2019).


G. Mohler and M. Porter.  Rotational grid, PAI-maximizing crime forecasts.  Statistical Analysis and Data Mining: The ASA Data Science Journal 11.5 (2018): 227-236.

Y. Cheng, M. Dundar, G. Mohler.  A coupled ETAS-I2GMM point process with applications to fault detection.  Annals of Applied Statistics 12(3), DOI: 10.1214/18-AOAS1134.​

R. Hosler, X. Liu, J. Carter, A. Ganci, J. Hill, R. Raje, G. Mohler and M. Saper.  RaspBary: Hawkes point process Wasserstein barycenters as a service. 

R. Vijayan and G. Mohler.  Forecasting retweet count during elections using graph convolution neural networks.  IEEE International Conference on Data Science and Advanced Analytics (DSAA 2018).

S. Pandey, N. Chowdhury, M. Patil, R. Raje, G. Mohler, and J. Carter.  CDASH: Community data analytics for social harm.  IEEE International Smart Cities Conference (ISC2 2018).   

G. Mohler and P.J. Brantingham.  Privacy preserving, crowd sourced crime Hawkes processes.  International Workshop on Social Sensing (SocialSens).  IEEE 2018.

Brantingham, P.J., M. Valasik, G. Mohler.  Does Predictive Policing Lead to Biased Arrests? Results from a Randomized Controlled Trial.  Statistics and Public Policy. 5(1), 2018.

G. Mohler, J. Carter, R. Raje.  Improving social harm indices with a modulated Hawkes process.  International Journal of Forecasting, 34 (3), 2018.

G. Mohler, M. Porter, J. Carter, and G. LaFree.  Learning to rank spatio-temporal event hotspots.  7th International Workshop on Urban Computing.  2018.

G. Mohler, R. Raje, J. Carter,  M Valasik, and P.J. Brantingham.  A penalized likelihood method for balancing accuracy and fairness in predictive policing.  IEEE International Conference on Systems, Man, and Cybernetics (SMC2018). 

S. Khorshidi, M. Al Hasan, G. Mohler, and M. Short.  The role of graphlets in viral processes on networks.  Journal of Nonlinear Science, 2018.

J. Carter, G. Mohler and B. Ray.  Spatial Concentration of Opioid Overdose Deaths in Indianapolis: An Application of the Law of Crime Concentration at Place to a Public Health Epidemic.  Journal of Contemporary Criminal Justice, 35 (2), 2018.


G. Mohler, M. Short, P.J. Brantingham.  The concentration-dynamics tradeoff in crime hot spotting.  In Unraveling the Crime-Place Connection: New Directions in Theory and Policy, edited by David Weisburd and John Eck.  2017.

2016 (On leave to industry)

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.

2015 (On leave to industry)

G. Mohler, M. Short, S. Malinowski, M. Johnson, G. Tita, A. Bertozzi, P.J. Brantingham. Randomized controlled field trials of predictive policing.  Journal of the American Statistical Association.  110 (512).  2015.


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

J. T. Woodworth, G. Mohler, A. L. Bertozzi and P. J. Brantingham, Nonlocal crime density estimation incorporating housing information, Phil. Trans. Roy. Soc. A, 2014.


G. Mohler, Marked point process hotspots maps for homicide and gun crime prediction in Chicago, International Journal of Forecasting, 30, 491, 2014.


M. Short, G. Mohler, P. J. Brantingham, and G. Tita, Gang rivalry dynamics via coupled point process networks, Discrete and Continuous Dynamical Systems B, 34, 1459, 2014.



G. Mohler, Discussion of: Estimating the historical and future probabilities of large terrorist events, Annals of Applied Statistics, 7 (4), 1866, 2013.


G. Mohler, Modeling and estimation of multi-source clustering in crime and security data, Annals of Applied Statistics, 7 (3), 1525, 2013


E. Lewis and G. Mohler, A nonparametric EM algorithm for multiscale Hawkes processes, preprint.


D. Sledge and G. Mohler, Eliminating malaria in the American South:  An analysis of the decline of malaria in 1930s Alabama, American Journal of Public Health, 103 (8), 1381, 2013.



G. Mohler and M. Short, Geographic profiling from kinetic models of criminal behavior, SIAM J. on Applied Math, 72 (1), 163, 2012.


E. Lewis, G. Mohler, P. J. Brantingham, and A. Bertozzi, Self-exciting point process models of civilian deaths in Iraq, Security Journal, 25 (3), 244, 2012.



M. G. Ascenzi, C. Blanco, I Drayer, H. Kim, R. Wilson, K. Retting, K. Lyons, and G. Mohler, Effect of localization, length and orientation of chondrocytic primary cilium on murine growth plate organization, Journal of Theoretical Biology, 285 (1), 147, 2011.


G. Mohler, M. Short, P. Brantingham, F. Schoenberg, and G. Tita, Self-exciting point process modeling of crime, Journal of the American Statistical Association, 106 (493), 100, 2011.


G. Mohler, A. Bertozzi, T. Goldstein and S. Osher, Fast TV Regularization for 2D Maximum Penalized Likelihood Estimation, Journal of Computational and Graphical Statistics, 20 (2), 479, 2011.



L. Smith, M. Keegan, T. Wittman, G. Mohler, and A Bertozzi,  Improving Density Estimation By Incorporating Spatial Information, EURASIP J. on Advances in Signal Processing, Volume 2010, 12 pages.



H. D. Ceniceros, G. H. Fredrickson, and G. O. Mohler, Coupled flow-polymer dynamics via statistical field theory: modeling and computation,  Journal of Computational Physics, 228 (5), 1624, 2009.



E. M. Lennon, G. O. Mohler, H. D. Ceniceros, C. J. Garcia-Cervera, and G. H. Fredrickson,  Numerical solutions of the complex Langevin equations in polymer field theory, Multiscale Modeling and Simulation, 6 (4), 1347, 2008.  



H. D. Ceniceros and G. O. Mohler, A practical splitting method for stiff SDEs with applications  to problems with small noise, Multiscale Modeling and Simulation, 6 (1), 212, 2007.


Manuscripts from REU projects mentored


Statistical and Stochastic Modeling of Gang Rivalries in Los Angeles,  SIURO Vol. 3, Mike Egesdal (UCLA now at Harvard), Chris Fathauer (Harvey Mudd), Kym Louie (Harvey Mudd), and Jeremy Neuman (UCLA now at Chicago). 


Effect of localization, length and orientation of chondrocytic primary cilium on murine growth plate organization, Journal of Theoretical Biology, 285 (1), 147, 2011, Cristian Blanco (UCLA now at CMU), Ian Drayer (UCLA), Hannah Kim (UCLA now at Sony), Ryan Wilson (UCLA now at Stanford).


Geographic profiling through six dimensional nonparametric density estimation, SIURO Vol. 5, Austin Alleman (SCU).