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George Mohler

Daniel J. Fitzgerald Professor

Department of Computer Science

Boston College

Contact: mohlerg [AT] bc [DOT] edu

My research focuses on statistical and deep learning approaches to solving problems in spatial, urban and network data science.  Several current projects include modeling and causal inference for overdose and social harm event data, fairness and interpretability in criminal justice forecasting, and modeling viral processes and link formation on social networks.  For Postdoctoral Fellowship opportunities in my lab see here.   


Ph.D. in Mathematics

University of California Santa Barbara



M.A. in Mathematics

University of California Santa Barbara


B.S. in Mathematics (Highest Distinction)

Indiana University Bloomington



Academic Employment

Daniel J. Fitzgerald Professor

Boston College

Department of Computer Science 



Indiana University - Purdue University Indianapolis

Department of Computer and Information Science 



Indiana University - Purdue University Indianapolis​

Institute for Mathematical Modeling and Computational Science


Associate Professor

Indiana University - Purdue University Indianapolis

Department of Computer and Information Science 



Assistant Professor

Santa Clara University

Department of Mathematics and Computer Science 



CAM Assistant Adjunct Professor

University of California, Los Angeles 

Department of Mathematics


Graduate Students

Ritika Pandey (PhD, expected 2023)

Xueying Liu, PhD IUPUI 2022 (Postdoc at St Jude)

Wen-Hao Chiang, PhD IUPUI 2022 (Amazon)

Samira Khorshidi, PhD IUPUI 2022 (Apple)

Hao Sha, PhD IUPUI 2021 (Career Builder)

Bo Peng, MS IUPUI 2019 (PhD student at Ohio State)

Raghavendran Vijayan, MS IUPUI 2018 (Palo Alto Networks)

Editorial Activities

Associate Editor, Journal of Quantitative Criminology, 2022-present

Associate Editor, International Journal of Forecasting, 2020-present



G. Mohler and J. Mateu.  Second order preserving point process permutations.

X. Miscouridou, S. Bhatt, G. Mohler, S. Flaxman, and S. Mishra.  Cox-Hawkes: doubly stochastic spatiotemporal Poisson processes.

Recent Criminal Justice Publications 

D. Sledge, H. F. Thomas, B. L. Hoang, and G. Mohler. Impact of Medicaid, Race/Ethnicity, and Criminal Justice Referral on Opioid Use Disorder Treatment.  Journal of the American Academy of Psychiatry and the Law.  (2022).  DOI: 10.29158/JAAPL.210137-21

Brantingham, P. Jeffrey, George Mohler, and John MacDonald. Changes in Public-Police Cooperation Following the Murder of George Floyd. PNAS Nexus (2022).

G. Mohler, S. Mishra, B. Ray, L. Magee, P. Huynh, M. Canada, D. O'Donnell, and S. Flaxman.  A modified two-process Knox test for investigating the relationship between law enforcement opioid seizures and overdoses.  Proceedings of the Royal Society A 477.2250 (2021): 20210195.


P. J. Brantingham, J. Carter, J. MacDonald, C. Melde, and G. Mohler.  Is the recent surge in violence in American cities due to contagion?  Journal of Criminal Justice 76 (2021): 101848.

J. Carter, G. Mohler, R. Raje, N. Chowdhury, and S. Pandey.  The Indianapolis Harmspot Policing Experiment.  Journal of Criminal Justice 74 (2021): 101814.

Khorshidi, S., Carter, J., Mohler, G., and Tita, G.  Explaining crime diversity with Google street view.  Journal of Quantitative Criminology, 37.2: 2021: 361-391.

R. Pandey, P.J. Brantingham, C. Uchida, and G. Mohler. Building knowledge graphs of homicide investigation chronologies.  In 2020 International Conference on Data Mining Workshops (ICDMW) (pp. 790-798). IEEE.

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 35.4 (2019): 747-765.

Carter, J. G., Mohler, G., and Ray, B.  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 (2019): 161-185.

Recent COVID-19 Publications 

MacDonald, J., Mohler, G. and Brantingham, P.J.  Association between race, shooting hot spots, and the surge in gun violence during the COVID-19 pandemic in Philadelphia, New York and Los Angeles.  Preventive Medicine (2022).

B. Chen, P. Shrestha, A. L. Bertozzi, G. Mohler, and F. Schoenberg,

A Novel Point Process Model for COVID-19: Multivariate Recursive Hawkes Process, to appear as Chapter 5 in Predicting Pandemics in a Globally Connected World, Birkhauser-Springer, eds. Nicola Bellomo and Mark A.J. Chaplain (2022).

Wen-Hao Chiang, X. Liu, and G. Mohler.  Hawkes process modeling of COVID-19 with mobility leading indicators and spatial covariates.  International Journal of Forecasting (2022).

P. J. Brantingham, G. Tita, and G. Mohler.  Gang-related crime in Los Angeles remained stable following COVID-19 social distancing orders.  Criminology and Public Policy (2021).

G. Mohler, M.B. Short, F. Schoenberg and D. Sledge. Analyzing the Impacts of Public Policy on COVID-19 Transmission: A Case Study of the Role of Model and Dataset Selection Using Data from Indiana.  Statistics and Public Policy 8.1 (2021): 1-8.

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 (2020): 16732-16738.

N. Glober, G. Mohler, P. Huynh, T. Arkins, D. O'Donnell, J. Carter and B. Ray.  Impact of COVID-19 Pandemic on Drug Overdoses in Indianapolis.  Journal of Urban Health 97.6 (2020): 802-807.

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): 101692.

Grants and Awards

AFOSR MURI grant FA9550-22-1-0380, Learning Dynamics and Detecting Causal Pathways in Coupled Online-Offline Systems, $1,212,914 (Boston College portion). Joint w/ J. Brantingham, E. Hartman, H. Lu, F. Mortstatter, and N. Rodriguez.

NSF grant SCC-2125319, SCC-IRG Track 2: Independent Real-Time Sensing Data to Support Community Well-Being,

$1,422,463.  2021-2024.  Joint w/ J. Brantingham (PI), E. Hartman and J. Hill.

CDC grant R01CE003362, Examining the iatrogenic effect of law enforcement disruptions to the illicit drug market on overdose in the surrounding community, $1,087,500.  9/2021-8/2024. Joint w/ Brad Ray (PI), Jennifer Carroll, Erin Comartin, Steven Korzeniewski, Grant Victor and Brandon del Pozo.

NSF grant ATD-2124313, ATD: Collaborative Research: Multi-task, Multi-Scale Point Processes for Modeling Infectious Disease Threats, $149,992. 2021-2024.

NIJ Recidivism forecasting challenge, 1st, 3rd and 2nd place in three reducing bias categories of the competition.  Joint w/ M. Porter (team PASDA), $30,000.  2021.

IUPUI AI Institute Seed Grant, Leveraging Artificial Intelligence and Machine Learning to Reduce Disparities in Suicide Trajectories: A BioPsychosocial Approach to Identify Modifiable Risk and Protective Processes.  Joint w/ Y. Xiao, J. Carlson, and S. Fang, $25,000.  2021-2022.

IU Racial Justice Research Fund, High-stakes pairing systems for mitigating police bias and misconduct.  Joint w/ J. Carter and J. Hill.  $14,915. 2020-2021.  

NIJ grant 2019-R2-CX-0004,  The Impact of Gunshot Detection Technology on Gun Violence in Kansas City and Chicago: A Multi-Pronged Synthetic Control Evaluation.  Joint w/ E. Piza (PI) and J. Carter, $503,305.  2020-2021.

NSF grant SCC-1737585, SCC-IRG Track 2: Real-Time Algorithms and Software Systems for Heterogeneous Data Driven Policing of Social Harm, joint with J. Carter and R. Raje, $791,513. 9/2017- 8/2020.


NSF grant ATD-1737996, ATD: Collaborative Research: Point Process Algorithms for Threat Detection from Heterogeneous Human Mobility and Activity Data, $100,000.  9/2017- 8/2020.


NSF grant REU-1659488, REU Site: Data Science of Risk and Human Activity, joint with co-PI M. al Hasan, $287,377.  3/2017- 2/2020.

NIJ Real-time crime forecasting challenge.  First place in nine categories of large business division.  Joint w/ M. Porter, $135,000.  2017.


NSF grant SES-1343123, INSPIRE: Computational modeling of grievances and political instability through global media, joint with LaFree (PI), Cunningham, Golbeck, and Torrens, $2,594,533.  9/2014- 8/2017.


NSF grant DMS-0968309, FRG: Collaborative Research: Mathematics of large scale urban crime, joint with A. Bertozzi (PI), G. Tita, J. Brantingham, M. Short, L. Chayes, and F. Schoenberg, $1,008,105.  9/2010-8/2013.


Recent Data Science Publications 

W. Chiang and G. Mohler.  Hawkes process multi-armed bandits for search and rescue.  IEEE International Conference on Machine Learning and Applications, ICMLA 2022.

S. Khorshidi, B. Wang, and G. Mohler.  Adversarial attacks on deep temporal point processes.  IEEE International Conference on Machine Learning and Applications, ICMLA 2022.

S. Badirli, Z. Akata, G. Mohler, C. Picard, M. Dundar.  Fine-Grained Zero-Shot Learning with DNA as Side Information.  Conference on Neural Information Processing Systems, NeurIPS 2021. 

H. Sha, M. Al Hasan, and G. Mohler.   Group link prediction Using Convolutional Variational Autoencoder.  AAAI Conference on Weblogs and Social Media, ICWSM 2021.

H. Sha, M. Al Hasan, and G. Mohler.  Source detection on networks using spatial temporal graph convolutional networks.  IEEE International Conference on Data Science and Advanced Analytics, DSAA 2021.

H. Sha, M. Al Hasan, G. Mohler.  Learning Network Event Sequences Using Long Short-term Memory and Second-order Statistic Loss.  Statistical Analysis and Data Mining 14.1 (2021): 61-73.

G. Mohler, E. McGrath, C. Buntain, and G. LaFree.  Hawkes binomial topic model with applications to coupled conflict-Twitter data.  Annals of Applied Statistics 14.4 (2020): 1984-2002.

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 (2020): 1-14.

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.

Morehead, A., Ogden, L., Magee, G., Hosler, R., White, B., and Mohler, G.  Low Cost Gunshot Detection using Deep Learning on the Raspberry Pi.  2019 IEEE International Conference on Big Data.

Chiang, W., B.Yuan, H. Li, B. Wang, A. Bertozzi, J. Carter, B. Ray, and G. Mohler. SOS-EW: System for overdose spike early warning using drug mover’s distance-based Hawkes processes.  Joint European conference on machine learning and knowledge discovery in databases, pp. 538-554. Springer, Cham, 2019.

Papers on Fairness-Aware and Interpretable Forecasting

M. B. Short and G. Mohler.  A fully Bayesian, logistic regression tracking algorithm for mitigating disparate misclassfication.  International Journal of Forecasting (2022).

G. Mohler and M. Porter.  A note on the multiplicative fairness score in the NIJ recidivism forecasting challenge.  Crime Science 10.1 (2021): 1-5.

S. Khorshidi, J. Carter, and G. Mohler.  Repurposing recidivism models for forecasting police officer use of force.  2020 IEEE International Conference on Big Data.

H. Sha, M. Al Hasan, J. Carter and G. Mohler.  Interpretable Hawkes Process Spatial Crime Forecasting with TV-Regularization.  2020 IEEE International Conference on Big Data.

G. Mohler, R. Raje, J. Carter,  M Valasik, and P.J. Brantingham.  A penalized likelihood method for balancing accuracy and fairness in predictive policing.  2019 IEEE International Conference on Systems, Man, and Cybernetics.

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): 1-6.

Full List of Publications Available at Google Scholar  

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