| 1. |
Endogenous and exogenous effects in self-exciting
process models of terrorist activity. Statistica Neerlandica,
79(1): e12347, 2025. (Ruggeri F., Porter M.D., and White G.)
[PDF] |
| 2. |
Guest editorial: Forecasting for social good.
International Journal of Forecasting, 41(1): 1-2, 2025.
(Rostami-Tabar B., Pinson P., and Porter M.D.)
[PDF] |
| 3. |
Contextual Embeddings in Sociological Research:
Expanding the Analysis of Sentiment and Social Dynamics.
Sociological Methodology, 55},: 25–58, 2025. (Mostafavi M.,
Porter M.D., and Robinson D.T.)
[PDF] |
| 4. |
Time of week intensity estimation from partly interval
censored data with applications to police patrol planning. Journal
of Applied Statistics, : 1–19, 2024. (Tian J. and Porter M.D.)
[PDF] |
| 5. |
Using Machine Learning to Assess the Predictive Power
of Donor Characteristics in Pediatric Heart Transplant Outcomes. The
Journal of Heart and Lung Transplantation, 43(4): S622, 2024.
(Porter M., Sharff J., Dixon R., Haregu F., and McCulloch M.)
[PDF] |
| 6. |
AI in Motion. Civil Engineering Magazine,
94(6): 60-69, 2024. (Pennetti C.A. and Porter M.D.)
[PDF] |
| 7. |
Pediatric donor heart acceptance practices in the
United States: What is really being considered?. Pediatric
Transplantation, 28(1): e14649, 2024. (McCulloch M., Alonzi L.,
White S., Haregu F., and Porter M.)
[PDF] |
| 8. |
Pediatric donor heart utilization variability among
organ procurement organizations. Pediatric Transplantation,
28(3): e14747, 2024. (Haregu F., Dixon R.J., Porter M., and McCulloch
M.)
[PDF] |
| 9. |
Machine Learning for Predicting Waitlist Survival in
Pediatric Patients Awaiting Heart Transplantation. The Journal of
Heart and Lung Transplantation, 43(4): S621–S622, 2024. (Haregu F.,
Dixon R., Porter M., Scharff J., and McCulloch M.)
[PDF] |
| 10. |
The Utility of Machine Learning Applied to Military
Assessment and Selection. Military Operations Research, 29(2):
53–94, 2024. (Deverill H., Scherer W., Porter M., and Stam A.)
[PDF] |
| 11. |
Deep-Learning Based Probabilistic Forecasting Framework
for Censored Data. 23rd IEEE International Conference on Machine
Learning and Applications (ICMLA), 2024. (Tian J. and Porter
M.D.) |
| 12. |
Forecasting Breakthroughs: Identifying Future Leaders
in the Semiconductor Industry. 2024 Systems and Information
Engineering Design Symposium (SIEDS), 425–430, 2024. (Rogers A.,
Dibsie C., Kuzneski E., Underwood D., Brozey R., Sullivan L., Robinson
D., and Porter M.D.)
[PDF] |
| 13. |
Sequential LLM Framework for Fashion Recommendation.
Proceedings of the 2024 Conference on Empirical Methods in Natural
Language Processing: Industry Track, 1276–1285, 2024. (Liu H., Tang
X., Chen T., Liu J., Indu I., Zou H.P., Dai P., Galan R.F., Porter M.D.,
Jia D., Zhang N., and Xiong L.)
[PDF] |
| 14. |
Reevaluating Data Partitioning for Emotion Detection in
EmoWOZ. arXiv preprint arXiv:2303.13364, : 2023. (Mostafavi M.
and Porter M.D.) [PDF] |
| 15. |
Quantifying the Influence of User Behaviors on the
Dissemination of Fake News on Twitter with Multivariate Hawkes
Processes. arXiv preprint arXiv:2308.13927, : 2023. (Jiang Y.
and Porter M.D.) [PDF] |
| 16. |
Effect of Practice Variation Amongst Organ Procurement
Organizations on Pediatric Donor Heart Utilization. The Journal of
Heart and Lung Transplantation, 42(4): S446–S447, 2023. (Haregu F.,
Porter M., Dixon J., and McCulloch M.)
[PDF] |
| 17. |
The intersection of video capsule endoscopy and
artificial intelligence: addressing unique challenges using machine
learning. arXiv preprint arXiv:2308.13035, : 2023. (Guleria S.,
Schwartz B., Sharma Y., Fernandes P., Jablonski J., Adewole S.,
Srivastava S., Rhoads F., Porter M., Yeghyayan M., and NA o.)
[PDF] |
| 18. |
Systems Analysis of Bias and Risk in AI-Enabled Medical
Diagnosis. 2023 IEEE Symposium Series on Computational Intelligence
(SSCI), 1800–1807, 2023. (Moghadasi N., Piran M., Baek S., Valdez
R.S., Porter M.D., Johnson D., and Lambert J.H.)
[PDF] |
| 19. |
Changing presidential approval: Detecting and
understanding change points in interval censored polling data.
Stat, 11(1): e463, 2022. (Tian J. and Porter M.D.)
[PDF] |
| 20. |
Guest Editorial: Forecasting for social good.
International Journal of Forecasting, 38(3): 1173–1174, 2022.
(Rostami-Tabar B., Hong T., and Porter M.D.) |
| 21. |
Forecasting for social good. International Journal
of Forecasting, 38(3): 1245–1257, 2022. (Rostami-Tabar B., Ali
M.M., Hong T., Hyndman R.J., Porter M.D., and Syntetos A.)
[PDF] |
| 22. |
Learning affective meanings that derives the social
behavior using Bidirectional Encoder Representations from Transformers.
arXiv preprint arXiv:2202.00065, : 2022. (Mostafavi M., Porter
M.D., and Robinson D.T.)
[PDF] |
| 23. |
Assessing the Relationship Between Pediatric Donors’
Terminal Hospitalizations and Heart Acceptance Practices. The
Journal of Heart and Lung Transplantation, 41(4): S508, 2022.
(McCulloch M., Liu I., Alonzi L., White S., and Porter M.) |
| 24. |
Building-Level Wastewater Surveillance for SARS-CoV-2
in Occupied University Dormitories as an Outbreak Forecasting Tool One
Year Case Study. ACS ES&T Water, 2(11): 2094–2104, 2022.
(Kotay S.M., Tanabe K.O., Colosi L.M., Poulter M.D., Barry K.E.,
Holstege C.P., Mathers A.J., and Porter M.D.)
[PDF] |
| 25. |
Simulating Fake News Dissemination on Twitter with
Multivariate Hawkes Processes. 2022 IEEE International Conference on
Big Data (Big Data), 3597–3606, 2022. (Jiang Y. and Porter M.D.)
[PDF] |
| 26. |
Multi-frame Abnormality Detection in Video Capsule
Endoscopy. Proceedings of the Future Technologies Conference,
177–186, 2022. (Jablonski J., Fernandes P., Adewole S., Syed S., Brown
D., and Porter M.)
[PDF] |
| 27. |
A note on the multiplicative fairness score in the NIJ
recidivism forecasting challenge. Crime Science, 10(17): 1–5,
2021. (Mohler G. and Porter M.D.)
[PDF] |
| 28. |
Development of Wastewater Pooled Surveillance of Severe
Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) from Congregate
Living Settings. Applied and Environmental Microbiology,
87(13): e00433-21, 2021. (Colosi L.M., Barry K.E., Kotay S.M., Porter
M.D., Poulter M.D., Ratliff C., Simmons W., Steinberg L.I., Wilson D.D.,
Morse R., Zmick P., and Mathers A.J.)
[PDF] |
| 29. |
Unsupervised shot boundary detection for temporal
segmentation of long capsule endoscopy videos. arXiv preprint
arXiv:2110.09067, : 2021. (Adewole S., Fernandes P., Jablonski J.,
Copland A., Porter M., Syed S., and Brown D.) |
| 30. |
A Tale of Two Metrics: Polling and Financial
Contributions as a Measure of Performance. IEEE International
Systems Conference (SysCon), 2021. (Mostafavi M., Porter M.D.,
Jiang Y., Phillips M., and Freedman P.)
[PDF] |
| 31. |
How emoji and word embedding helps to unveil emotional
transitions from social media interactions. IEEE International
Systems Conference (SysCon), 2021. (Mostafavi M. and Porter M.D.)
[PDF] |
| 32. |
Discovering Influence of Yelp Reviews Using Hawkes
Point Processes. Intelligent Systems Conference (IntelliSys),
2021. (Jiang Y. and Porter M.D.)
[PDF] |
| 33. |
An Application of the Partially Observed Markov Process
in the Analysis of Transmission Dynamics of COVID-19 via Wastewater.
Systems and Information Engineering Design Symposium (SIEDS),
2021. (Jiang S., Maggard K., Shakeri H., and Porter M.D.) |
| 34. |
Safe and Sustainable Fleet Management with Data
Analytics and Training. Systems and Information Engineering Design
Symposium (SIEDS), 1–3, 2021. (Gresham T.R., Kim J., McDonald J.,
Scoggins N., Mostafavi M., Park B.B., Porter M.D., Duffy M.E., and Smith
S.A.) |
| 35. |
Wastewater-Based Epidemiological Modeling for
Continuous Surveillance of COVID-19 Outbreak. 2021 IEEE
International Conference on Big Data (Big Data), 4342–4349, 2021.
(Fazli M., Sklar S., Porter M.D., French B.A., and Shakeri H.) |
| 36. |
Determining Factors of Heart Quality and Donor
Acceptance in Pediatric Heart Transplants. Systems and Information
Engineering Design Symposium (SIEDS), 2021. (Bullock J., Grieco M.,
Liu Y., Pedersen I., Roberson W., Wright G., Alonzi P., McCulloch M.A.,
and Porter M.D.) |
| 37. |
Lesion2Vec: Deep Meta Learning for Few-Shot Lesion
Recognition in Capsule Endoscopy Video. Proceedings of the Future
Technologies Conference, 762–774, 2021. (Adewole S., Fernandes P.,
Jablonski J., Copland A., Porter M., Syed S., and Brown D.) |
| 38. |
Graph Convolutional Neural Network For Weakly
Supervised Abnormality Localization In Long Capsule Endoscopy Videos.
2021 IEEE International Conference on Big Data (Big Data),
388–399, 2021. (Adewole S., Fernandes P., Jablonski J., Copland A.,
Porter M., Syed S., and Brown D.) |
| 39. |
Learning to rank spatio-temporal event hotspots.
Crime Science, 9(3): 1–12, 2020. (Mohler G., Porter M.D.,
Carter J., and LaFree G.)
[PDF] |
| 40. |
Is hydrothermal treatment coupled with carbon capture
and storage an energy-producing negative emissions technology?.
Energy Conversion and Management, 203(112252): 2020. (Cheng F.,
Porter M.D., and Colosi L.M.)
[PDF] |
| 41. |
Traveler Perception of Transportation System
Performance Using Kernel Density Estimation to Prioritize Infrastructure
Investments. International Conference on Transportation and
Development, 48-61, 2020. (Pennetti C.A., Andrews D., Porter M.D.,
and Lambert J.H.)
[PDF] |
| 42. |
Criminal Consistency and Distinctiveness. Systems
and Information Engineering Design Symposium (SIEDS), 1–3, 2020.
(Koch A., Tian J., and Porter M.D.)
[PDF] |
| 43. |
Optimization of VDOT Safety Service Patrols to Improve
VDOT Response to Incidents. Systems and Information Engineering
Design Symposium (SIEDS), 1–6, 2020. (Campbell E., Chamberlayne E.,
Gawrylowicz J., Hood C., Hudak A., Orlowsky M., Rivero E., and Porter
M.) [PDF] |
| 44. |
Detecting, identifying, and localizing radiological
material in urban environments using scan statistics. IEEE
International Symposium on Technologies for Homeland Security
(HST), 1–6, 2019. (Porter M.D. and Akakpo A.)
[PDF] |
| 45. |
Evaluation of VDOT’s Safety Service Patrols to Improve
Response to Incidents. Systems and Information Engineering Design
Symposium (SIEDS), 1–5, 2019. (Abrisqueta A., Bishop C.A., Perryman
S.P., Shoebotham L.M., Wang J., and Porter M.)
[PDF] |
| 46. |
Optimal Bayesian Clustering using Non-negative Matrix
Factorization. Computational Statistics and Data Analysis, 128:
395–411, 2018. (Wang K. and Porter M.D.)
[PDF] |
| 47. |
Rotational grid, PAI-maximizing crime forecasts.
Statistical Analysis and Data Mining, 11(5): 227–236, 2018.
(Mohler G. and Porter M.D.)
[PDF] |
| 48. |
Learning to rank spatio-temporal event hotspots.
URBCOMP2018, 2018. (Mohler G., Porter M.D., Carter J., and
LaFree G.)
[PDF] |
| 49. |
Predictive Crash Analytics. Technical Report,
2017. (Porter M.D., Das T., and R Z.) |
| 50. |
Understanding and Evaluating Predictive Crash Models.
SAMSI Summer Program on Transportation Statistics, 2017.
(Porter M.D.) |
| 51. |
How the Choice of Safety Performance Function Affects
the Identification of Important Crash Prediction Variables. Accident
Analysis and Prevention, 88(1): 1–8, 2016. (Wang K., Simandl J.K.,
Porter M.D., Graettinger A.J., and Smith R.K.)
[PDF] |
| 52. |
A Statistical Approach to Crime Linkage. The
American Statistician, 70(2): 152–165, 2016. (Porter M.D.)
[PDF] |
| 53. |
Consistency and specificity in burglars who commit
prolific residential burglary: Testing the core assumptions underpinning
behavioural crime linkage. Legal and Criminological Psychology,
21(1): 77–94, 2016. (Bouhana N., Johnson S.D., and Porter M.D.)
[PDF] |
| 54. |
Partially-supervised spatiotemporal clustering for
burglary crime series identification. Journal of the Royal
Statistical Society: Series A (Statistics in Society), 178(2):
465–780, 2015. (Reich B.J. and Porter M.D.)
[PDF] |
| 55. |
Modelling the effectiveness of counter-terrorism
interventions. Trends and Issues in Crime and Criminal Justice,
(457): 1–8, 2014. (White G., Mazerolle L., Porter M.D., and Chalk P.)
[PDF] |
| 56. |
GPU accelerated MCMC for modeling terrorist activity.
Computational Statistics and Data Analysis, 71: 643–651, 2014.
(White G. and Porter M.D.)
[PDF] |
| 57. |
Terrorism Risk, Resilience, and Volatility: A
Comparison of Terrorism in Three Southeast Asian Countries. Journal
of Quantitative Criminology, 29(2): 295–320, 2013. (White G.,
Porter M.D., and Mazerolle L.)
[PDF] |
| 58. |
Discussion of Estimating the historical and future
probabilities of large terrorist events. The Annals of Applied
Statistics, 7(4): 1871–1875, 2013. (Reich B.J. and Porter M.D.)
[PDF] |
| 59. |
Self-exciting hurdle models for terrorist activity.
The Annals of Applied Statistics, 6(1): 106–124, 2012. (Porter
M.D. and White G.)
[PDF] |
| 60. |
Evaluating temporally weighted kernel density methods
for predicting the next event location in a series. Annals of
GIS, 18(3): 225–240, 2012. (Porter M.D. and Reich B.J.)
[PDF] |
| 61. |
Innovative Methods for Terrorism and Counterterrorism
Data. In Evidence-Based Counterterrorism Policy, Springer New
York, 91–112, 2012. (Porter M.D., White G., and Mazerolle L.)
[PDF] |
| 62. |
Network Neighborhood Analysis. IEEE Int. Conf. on
Intelligence and Security Informatics (ISI), 31-36, 2010. (Porter
M.D. and Smith R.)
[PDF] |
| 63. |
Mixture Likelihood Ratio Scan Statistic for Disease
Surveillance. Advances in Disease Surveillance, 5: 1, 2008.
(Neimi J.B., Porter M.D., and Reich B.J.)
[PDF] |
| 64. |
Detecting local regions of change in high-dimensional
criminal or terrorist point processes. Computational Statistics
& Data Analysis, 51(5): 2753 – 2768, 2007. (Porter M.D. and
Brown D.E.) [PDF] |
