Faculty Profiles

Hasan, A. S., Jalayer, M., & Das, S. (n.d.). Investigation of Run-off the Road Crashes Involving Distracted Drivers in New Jersey: A Utilization of Machine Learning Models and SHAP Analysis. Transportation Research Record.

Das, S., & Chakraborty, R. (2026). A Dimensionality-Reduced XAI Framework for Roundabout Crash Severity Insights. In The 59th Hawaii International Conference on System Sciences (HICSS). Retrieved from https://arxiv.org/abs/2509.12524

Javed, S. A., Barua, S., Tusti, A. G., Polock, S. B. B., Chowdhury, T. I., & Das, S. (2026). Built environment and injury risk: Association rule-based exploration of e-scooter crashes in Texas cities. Cities, 171. https://doi.org/10.1016/j.cities.2025.106748

Rahman, M. A., Tolford, T., Junaed, S., Das, S., Hossain, A., Moomen, M., … Codjoe, J. (2026). Pedestrian fatalities on US interstates: a pattern mining approach to investigating pedestrian actions and policy implications. Case Studies on Transport Policy, 23. https://doi.org/10.1016/j.cstp.2025.101696

Tusti, A. G., Chakraborty, R., Chowdhury, T. I., Islam, M. M., Mimi, M. S., & Das, S. (2026). Uncovering latent structures of crash typology in narcotic-involved fatal crashes for safe system interventions. Accident Analysis & Prevention, 227. https://doi.org/10.1016/j.aap.2025.108382

Chukwu, M., Huang, X., Audu, K., Wang, H., & Das, S. (2026). Unequal Paths to Nature: Mobile-Phone Insights into Park Visits in Nine Major Cities in the United States. Urban Forestry & Urban Greening. https://doi.org/10.1016/j.ufug.2025.129196

Chakraborty, R., Polock, S. B. B., Pandey, B., Shuvo, S. A., Dey, K., & Das, S. (2026). Uncovering contextual risk patterns in cannabis-involved fatal crashes: A data-driven approach to public health-oriented road safety. Journal of Safety Research, 96. https://doi.org/10.1016/j.jsr.2025.12.005

Chhetri, G., Das, S., & Chowdhury, T. I. (n.d.). WISE: Web Information Satire and Fakeness Evaluation. In WEB&GRAPH 2026 Proceeding. Retrieved from https://arxiv.org/abs/2512.24000

Das, S., Chhetri, G., & Chowdhury, T. I. (n.d.). SPARK: Search Personalization via Agent-Driven Retrieval and Knowledge-sharing. In WEB&GRAPH 2026 Proceeding. Retrieved from https://arxiv.org/abs/2512.24008

Chettri, G., Dutta, A. K., & Das, S. (2026). CognitiveSky: Scalable Sentiment and Narrative Analysis for Decentralized Social Media. In The 59th Hawaii International Conference on System Sciences (HICSS). https://doi.org/https://hdl.handle.net/10125/111760

Sheykhfard, A., Azmoodeh, M., Das, S., Ye, X., & Koppel, S. (2026). Exploring factors influencing user Re-ride intentions in shared autonomous shuttle vehicles. Transport Policy. https://doi.org/10.1016/j.tranpol.2025.103894

Somvanshi, S., Liu, J., Chakraborty, R., Tamakloe, R., & Das, S. (2026). Predicting Crash Severity using Naturalistic Driving Data and Neural Networks. International Journal of Intelligent Transportation Systems Research. https://doi.org/10.1007/s13177-025-00624-3

P, S., Dutta, A. K., & Das, S. (n.d.). Characterizing and Predicting Wildfire Evacuation Behavior: A Dual-Stage ML Approach. In IEEE SouthEast Con 2026.

Somvanshi, S., Islam, Md. M., Rafe, A., Tusti, A. G., Chakraborty, A., Baitullah, A., … Das, S. (2026). Bridging the Black Box: A Survey on Mechanistic Interpretability in AI. ACM Computing Surveys. https://doi.org/https://doi.org/10.1145/3787104

Tamakloe, R., Adanu, E. K., Das, S., & Adoah, B. E. (2026). Fatal distracted driving pedestrian-involved crashes in Ghana: Exploring cluster-specific factor associations using cluster correspondence analysis. African Transport Studies, 4. https://doi.org/10.1016/j.aftran.2026.100081

Mimi, M. S., Das, S., & Dutta, A. K. (2026). Non-spatial AI Modeling to Estimate Traffic Volume Measures on Local Roadways. International Journal of Urban Sciences. https://doi.org/10.1080/12265934.2025.2612094

Somvanshi, S., Javed, S. A., Islam, M. M., Pandit, D., & Das, S. (2025). A survey on Kolmogorov-Arnold Network. ACM Computing Surveys, 58(2), 1–35. https://doi.org/10.1145/3743128

Liu, J., Antariksa, G., Somvanshi, S., & Das, S. (2025). Revealing equity gaps in pedestrian crash data through explainable artificial intelligence clustering. Transportation Research Part D: Transport and Environment, 139. https://doi.org/10.1016/j.trd.2024.104538

Antariksa, G., Tamakloe, R., Liu, J., & Das, S. (2025). Automated and Explainable Artificial Intelligence to Enhance Prediction of Pedestrian Injury Severity. IEEE Transactions on Intelligent Transportation Systems, 26(4). https://doi.org/10.1109/TITS.2025.3526217

Das, S., Dzinyela, R., Dadashova, B., Westfall, G., Silvestri-Dobrovolny, C., Adanu, E. K., & Lord, D. (2025). Analysis of Motorcyclists Crash Severity using Cluster Correspondence and Hierarchical Binary Logit Models. Multimodal Transportation, 4(1). https://doi.org/10.1016/j.multra.2025.100197

Kutela, B., Kinero, A., Shita, H., Das, S., Ruseruka, C., Chengula, T. J., & Novat, N. (2025). Understanding Spatial-temporal Attributes Influencing Electric Vehicle’s Charging Stations Utilization: A Multi-City Study. Green Energy and Intelligent Transportation, 4(5). https://doi.org/10.1016/j.geits.2025.100255

Mimi, M. S., Chakraborty, R., Barua, S., Das, S., Khan, M. N., & Dadashova, B. (2025). Demographic risk factors and injury severity scores in Substance-use behaviour related traffic crashes. Transportation Research Part F: Traffic Psychology and Behaviour, 108. https://doi.org/10.1016/j.trf.2024.11.018

Das, S., Sheykhfard, A., Azmoodeh, M., & Kutela, B. (2025). Analyzing purchase intentions of used electric vehicles through consumer experiences: A structural equation modeling approach. Transport Policy, 160. https://doi.org/10.1016/j.tranpol.2024.10.038

Mimi, M. S., Chakraborty, R., Liu, J., Barua, S., & Das, S. (2025). Exploring patterns in older pedestrian involved crashes during nighttime. Accident Analysis & Prevention, 209. https://doi.org/10.1016/j.aap.2024.107815

Rahman, M. A., Chakraborty, R., Das, S., Mohammed, N.-H., Hossain, M. M., & Junaed, S. (2025). Identifying attribute associations in fatal speeding crashes using latent class clustering and association rule mining. Journal of Transportation Safety & Security, 17(5). https://doi.org/10.1080/19439962.2024.2429095

Kinero, A., Kutela, B., Das, S., & Hossain, A. (2025). Who should be responsible for setting standards for how automated vehicles are used? Insights of the US perspective from a 2021 Nationwide Survey. Sustainable Futures, 9. https://doi.org/10.1016/j.sftr.2025.100718

Das, S., Dzinyela, R., Liu, J., Dadashova, B., & Silvestri-Dobrovolny, C. (2025). Understanding patterns of factor influences in motorcycle crashes with fixed objects. Journal of Transportation Safety & Security, 17(5), 483–509. https://doi.org/10.1080/19439962.2024.2429077

Jafari, M., Starewich, M., Hossain, A., Barua, S., Alnawmasi, N., Ye, X., & Das, S. (2025). Assessing motorcyclist injury severity on curved road segments with temporal dynamics and unobserved heterogeneity. Scientific Reports, 15(1). https://doi.org/10.1038/s41598-025-97972-7.

Das, S., & Chakraborty, R. (2025). Uncovering the role of restraint usage in driver ejection: a data mining investigation of fatal and injury crashes. Traffic Injury Prevention. https://doi.org/10.1080/15389588.2025.2491580

Das, S., Somvanshi, S., Chakraborty, R., & Dutta, A. K. (2025). Crash severity analysis of child bicyclists using arm-net and mambanet. IEEE. https://doi.org/10.1109/CAI64502.2025.00146

Antariksa, G., Chakraborty, R., Somvanshi, S., Das, S., Jalayer, M., Patel, D. R., & Mills, D. (2025). Comparative Analysis of Advanced AI-based Object Detection Models for Pavement Marking Quality Assessment during Daytime. IEEE. https://doi.org/10.1109/CAI64502.2025.00179

Somvanshi, S., Tusti, A. G., Chakraborty, R., & Das, S. (2025). Applying Tabular Deep Learning Models to Estimate Crash Injury Types of Young Motorcyclists. https://doi.org/10.1109/CAI64502.2025.00177

Ye, X., Newman, G., Zhai, W., Retchless, D., Das, S., Ham, Y., … Zhang, Z. (2025). Toward Coastal Infrastructure Resiliency: An AI-Enabled Decision Support Framework for Multiscale Comprehension and Stakeholder Empowerment. Transactions of the American Philosophical Society, 114(1), 65–97. https://doi.org/10.1353/tap.2025.a957549

Banihashemi, M., Das, S., Dadvar, S., & Liu, J. (2025). COVID-19 Era Crash Fatality/Severe Injury and Proven Speed-Crash Relations. Transportation Research Record. https://doi.org/10.1177/03611981251341322

Kutela, B., Das, S., kabir, N., & Vierkant, V. (2025). The Autopilot Paradox: Public Perception of Sleeping while Driving Semi-Automated Cars. Applied Mobilities, 10(4). https://doi.org/10.1080/23800127.2025.2516284

Dzinyela, R., Das, S., Jafari, M., & Khan, N. (2025). Applying Hybrid Dimension Reduction and Econometric Model to Investigate Rider Behaviors in Roadway Departure Motorcycle Crashes. Transportation Letters: The International Journal of Transportation Research, 17(10). https://doi.org/10.1080/19427867.2025.2516422

Sheykhfard, A., Jones, S., Sadeghvaziri, E., Koppel, S., Das, S., & Nankali, M. (2025). Integrating Empirical and Subjective Evidence on Young Drivers’ Risk Perceptions and Crash Factors. Transportation Research Record. https://doi.org/10.1177/03611981251350648

Kutela, B., Chengula, T. J., Ngeni, F., Lipu, C., Kidando, E., Liu, J., & Das, S. (2025). Examining Patterns of GPS-Related Traffic Crashes: Insights from a Matched Case–Control Approach through Crash Narratives. Journal of Transportation Engineering, Part A: Systems, 151(9). https://doi.org/10.1061/JTEPBS.TEENG-8910

Hossain, A., Das, S., jafari, M., Starewich, M., Chakraborty, R., & Kutela, B. (2025). Behavioral and psychological determinants of pedestrian collisions on arterial roads with evidence from random parameter models. Scientific Reports, 15(1). https://doi.org/10.1038/s41598-025-16762-3

Sheykhfard, A., Haghighi, F., Zadeh, A. A., Das, S., Oshanreh, M. M., Shaaban, K., & Soltani, A. (2025). Evaluating U-left turn and direct left turn movements at signalized intersections using traffic conflict indices. Journal of Traffic and Transportation Engineering (English Edition), 12(4). https://doi.org/10.1016/j.jtte.2024.01.004

Chakraborty, R., Liu, J., Tusti, A. G., Mimi, M. S., & Das, S. (2025). Impact of lighting conditions on nighttime crash severity among older and elderly drivers. Journal of Transportation Safety & Security, 17(12). https://doi.org/10.1080/19439962.2025.2529833

Chakraborty, R., Javed, S. A., Hossain, A., Mills, D., & Das, S. (2025). Identifying patterns in backing maneuver crashes utilizing differential evolution optimization algorithm. Journal of Transportation Safety & Security, 17(11), 1348–1376. https://doi.org/10.1080/19439962.2025.2529835

Das, S., Liu, J., Dzinyela, R., Dadashova, B., & Silvestri-Dobrovolny, C. (2025). Clustering patterns of roadway departure related motorcycle crashes using dimension reduction analysis. Journal of Transportation Safety & Security, 17(11). https://doi.org/10.1080/19439962.2025.2529831

Sakib, N., Paul, T., Das, S., & Hossain, A. (2025). Exploring the factors affecting injury severity in highway and non-highway crashes in Bangladesh applying machine learning and SHAP. IATSS Research, 49(2). https://doi.org/10.1016/j.iatssr.2025.06.001

Das, S. (2025). HyperSumm-RL: A Dialogue Summarization Framework for Modeling Leadership Perception in Social Robots. In HT ’25: Proceedings of the 36th ACM Conference on Hypertext and Social Media. https://doi.org/10.1145/3720553.3746685

Hossain, A., Sun, X., Das, S., Jafari, M., & Rahman, M. A. (2025). Investigating Pedestrian-Vehicle Crashes on Interstate Highways: Applying Random Parameter Logit Model. Accident Analysis & Prevention, 199. https://doi.org/10.1016/j.aap.2024.107503

Liu, J., Antariksa, G., Somvanshi, S., & Das, S. (2025). Revealing equity gaps in pedestrian crash data through explainable artificial intelligence clustering. Transportation Research Part D: Transport and Environment, 139. https://doi.org/10.1016/j.trd.2024.104538

Barua, S., Dutta, A. K., & Das, S. (2025). Modeling Distracted Driving: Analyzing Driver Gaze, Vehicle Positioning, and Psychological Response for Enhanced Traffic Safety. In 2025 IEEE Conference on Artificial Intelligence (CAI). Retrieved from https://ieeexplore.ieee.org/abstract/document/11050450

Chhetri, G., Anderson, D., Kutela, B., & Das, S. (2025). A Transformer-Based Cross-Platform Analysis of Public Discourse on the 15-Minute City Paradigm. In 24th International Conference on Machine Learning and Applications (ICMLA 2025). Retrieved from https://arxiv.org/abs/2509.11443

Somvanshi, S., Chhetri, G., Chhetri, G., & Das, S. (2025). Tabular Data with Class Imbalance: Predicting Electric Vehicle Crash Severity with Pretrained Transformers (TabPFN) and Mamba-Based Models. In 24th International Conference on Machine Learning and Applications (ICMLA 2025). Retrieved from https://arxiv.org/abs/2509.11449

Mimi, M. S., Islam, M. M., Sheykhfard, A., & Das, S. (2025). Crash risk patterns among older bicyclists: Insights from hybrid XGBoost-Cluster Correspondence Analysis. Journal of Safety Research, 95. https://doi.org/10.1016/j.jsr.2025.10.009

Jafari, M., Starewich, M., Das, S., Barua, S., & Tamakloe, R. (2025). Temporal stability analysis of crash injury severity in school zones: A mixed logit modeling approach. IATSS Research, 49(4). https://doi.org/10.1016/j.iatssr.2025.11.002

Fitzpatrick, K., Avelar, R., Das, S., Pratt, M., Le, M., & Venglar, S. (2025). Quantifying How Much Key Factors Influence Freeway Operational Speeds During Noncongested Periods. Journal of Traffic Control Device Research, 3(1). Retrieved from https://ncutcdjournal.org/index.php/jtcdr/article/view/24

Somvanshi, S., Islam, M. M., Chettri, G., Chakraborty, R., Mimi, M. S., Shuvo, S. A., … Das, S. (2025). From Tiny Machine Learning to Tiny Deep Learning: A Survey. ACM Computing Surveys. https://doi.org/10.1145/3776588

Hossain, A., Das, A., Javed, S. A., Das, S., & Mills, D. (2025). Analyzing Pedestrian–Automated Vehicle Crash Dynamics: A Comparative Study of Autonomous and Conventional Precrash Mode. Transportation Research Record. https://doi.org/10.1177/03611981251378496

Barua, S., Mimi, M. S., Javed, S. A., Tamakloe, R., & Das, S. (2025). Impact of temporal, spatial, and roadway factors on driver overrides in Level 2 automation: A bivariate binary probit model analysis. Transportation Research Part F: Traffic Psychology and Behaviour, 115. https://doi.org/10.1016/j.trf.2025.103356

Barua, S., Chakraborty, R., Islam, M. M., & Das, S. (2025). A data-driven approach to child pedestrian crash analysis using dimension reduction, clustering, and explainable AI. Accident Analysis & Prevention, 222. https://doi.org/10.1016/j.aap.2025.108229

Mimi, M. S., Islam, M. M., Tusti, A. G., Somvanshi, S., Das, S., & Ye, X. (2025). St-graphnet: a spatio-temporal graph neural network for understanding and predicting automated vehicle crash severity. In 1st ACM SIGSPATIAL International Workshop on Spatial Intelligence for Smart and Connected Communities. Association for Computing Machinery. https://doi.org/10.1145/3764924.3770894

Javed, S. A., Polock, S. B. B., Aghabayk, K., Barua, S., & Das, S. (2025). Pattern Recognition and Risk Analysis in U-Turn Crashes. Transportation Research Record. https://doi.org/10.1177/03611981251372467

Javed, S. A., Chakraborty, R., Hossain, A., & Das, S. (2025). Uncovering risk patterns in single and multiple ambulance crashes with association rules mining: evidence from Texas crash data. Transportmetrica A: Transport Science. https://doi.org/10.1080/23249935.2025.2592237

Tamakloe, R., Das, S., Adanu, E. K., & Park, D. (2025). Key factors affecting motorcycle-barrier crash severity: an innovative cluster-regression technique. Transportmetrica A: Transport Science, 21(1). https://doi.org/10.1080/23249935.2023.2230310

Sheykhfard, A., Qiao, F., Das, S., & Lord, D. (2025). A predictive analysis of crash proneness among freight drivers: insight into latent risk dimensions. Transportation Research Part F: Traffic Psychology and Behaviour, 114, 30–48. https://doi.org/10.1016/j.trf.2025.05.014

Liu, J., Chakraborty, R., Somvanshi, S., & Das, S. (2025). Impact of operating speed, roadway curvature, and precipitation on roadway departure risk in rural two-lane roads. Travel Behaviour and Society, 41. https://doi.org/10.1016/j.tbs.2025.101055

Jafari, M., Das, S., Barua, S., Mimi, M. S., & Starewich, M. (2025). Crash outcomes of yellow school buses: Random parameter and correlated random parameter logit models with heterogeneity in means. Accident Analysis & Prevention, 219. https://doi.org/10.1016/j.aap.2025.108109

Barua, S., Chakraborty, R., Mimi, M. S., Islam, M. M., & Das, S. (2025). Linking driver fatigue, safety rest area closures, and crash severity using cluster correspondence analysis. Journal of Transportation Safety & Security. https://doi.org/10.1080/19439962.2025.2554099

Tamakloe, R., Khorasani, M., Das, S., & Kim, I. (2025). Pattern recognition in crash clusters involving vehicles with advanced driving technologies. Accident Analysis & Prevention, 218. https://doi.org/10.1016/j.aap.2025.108072

Hossain, A., Das, S., Sun, X., Hasan, A. S., Jalayer, M., & Rahman, M. A. (2025). A hybrid data mining framework to investigate roadway departure crashes on rural two-lane Highways: Applying Fast and Frugal Tree with Association Rules Mining. Accident Analysis & Prevention, 217. https://doi.org/10.1016/j.aap.2025.108066

Hossain, A., Dzinyela, R., Jafari, M., Barua, S., Chakraborty, R., & Das, S. (2025). Assessing risk factors in ambulance-involved collisions: understanding the impact of COVID-19 pandemic. Transportmetrica A: Transport Science. https://doi.org/10.1080/23249935.2025.2532844

Huang, X., Ye, X., Stewart, K., & Das, S. (Eds.). (2025). Urban Human Mobility Practices, Analytics, and Strategies for Smart Cities. New York, NY, USA: Routledge. Retrieved from https://www.amazon.com/Urban-Human-Mobility-Practices-Strategies/dp/1032821620

Chakraborty, R., Mills, D. A., & Das, S. (2025). Children on Wheels: Identifying Crash Determinants using Cluster Correspondence Analysis. Accident Analysis & Prevention. https://doi.org/10.1016/j.aap.2025.108025

Das, S., Sakib, N., Geedapally, S. R., & Wei, Z. (2025). Understanding pedestrian hit-and-run crash patterns using Louisiana data. Transportation Safety and Environment, 7(3). https://doi.org/10.1093/tse/tdaf039

Jafari, M., Das, S., Tamakloe, R., Hossain, A., & Khan, M. N. (2025). Uncovering Individual Heterogeneity in Pedestrian Crash Severity with Mixed Logit Models: A Louisiana Case Study. Transportation Research Record, 2679(8). https://doi.org/10.1177/03611981251336135

Somvanshi, S., Liu, J., & Das, S. (2025). A Survey on Generative AI in Transportation Systems Management and Operation. In 2025 IEEE Conference on Artificial Intelligence (CAI). Retrieved from https://ieeexplore.ieee.org/abstract/document/11050708

Dzinyela, R., Dadashova, B., Das, S., Westfall, G., Silvestri-Dobrovolny, C., Adanu, E. K., & Lord, D. (2025). Analysis of motorcyclists crash severity using cluster correspondence and hierarchical binary logit models. Multimodal Transportation, 4(1). https://doi.org/10.1016/j.multra.2025.100197

Hossain, A., Barua, S., Das, S., & Starewich, M. J. (2025). Ambulance crash risk dynamics: a baseline (2017–2019) vs. pandemic-era (2020–2022) comparative study using a random parameter logit model. Transportmetrica A: Transport Science, 1–39. https://doi.org/10.1080/23249935.2025.2481578

Finley, M. D., Lopez, N., Das, S., Wei, H., Lin, W., Nian, D., & Ash, J. (2025). Investigation of Commercial Motor Vehicle (CMV)-Related Crashes in Ohio Work Zones. Retrieved from https://rosap.ntl.bts.gov/view/dot/86090

Kinero, K., Kasubi, F., Hossain, A., Das, S., & Kutela, B. (2025). Perception of cyber attacks on automated vehicles and its influence on road sharing and ridership: Insights of the US perspective from a 2021 nationwide survey. Transportation Research Part F: Traffic Psychology and Behaviour, (111). https://doi.org/10.1016/j.trf.2025.03.008

Jafari, M., Das, S., Starewich, M. J., & Das, S. (2025). SUV-pedestrian crash severity modelling considering unobserved heterogeneity in means and variances. Transportmetrica A: Transport Science, 1–45. https://doi.org/10.1080/23249935.2025.2453509

Islam, M. M., Liu, J., Chakraborty, R., & Das, S. (2025). Evaluating crash risk factors of farm equipment vehicles on county and non-county roads using interpretable tabular deep learning (TabNet). Accident Analysis & Prevention, 217. https://doi.org/10.1016/j.aap.2025.108048

Kutela, B., Das, S., Javed, S. A., Sheykhfard, A., Ngeni, F., Lyimo, S. M., … Langa, N. (2025). Understanding the intersection of transportation safety and quality of life: Insights from community surveys in Austin, Texas. Cities, 162. https://doi.org/10.1016/j.cities.2025.105964

Antariksa, G., Koeshidayatullah, A., Das, S., & Lee, J. (2025). XAI-driven contamination for self-supervised denoising with pixel-level anomaly detection in seismic data. Journal of Applied Geophysics, 238. https://doi.org/10.1016/j.jappgeo.2025.105723

Agheli, A., Aghabayk, K., Sadeghi, M., & Das, S. (2025). E-scooter crash severity in the United Kingdom: A comparative analysis using machine learning techniques and random parameters logit with heterogeneity in means and variances. IATSS Research, 49(2), 155–168. https://doi.org/10.1016/j.iatssr.2025.03.004

Khan, M. N., & Das, S. (2024). Advancing Traffic Safety through the Safe System Approach: A Systematic Review. Accident Analysis & Prevention.

Liu, J., Das, S., & Khan, M. (2024). Decoding the impacts of contributory factors and addressing social disparities in crash frequency analysis. Accident Analysis & Prevention. https://doi.org/10.1016/j.aap.2023.107375

Hossain, M., Zhou, H., Sun, X., Hossain, A., & Das, S. (2024). Crashes involving distracted pedestrians: Identifying risk factors and their relationships to pedestrian severity levels and distraction modes. Accident Analysis & Prevention. https://doi.org/10.1016/j.aap.2023.107359

Brauer, M., Roth, G. A., & Das, S. (2024). Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. The Lancet.

Das, S., Jafari, M., Hossain, A., Chakraborty, R., & Mimi, M. S. (2024). Toll road crash severity using mixed logit model incorporating heterogeneous mean structures. Transportmetrica A Transport Science.

Vollset, S. E., Ababneh, H. S., & Das, S. (2024). Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021. The Lancet.

Kutela, B., Novat, N., Kinero, A., Samulel, O., & Das, S. (2024). Understanding user behaviors and safety concerns on shared use paths in Edmonton, Canada. Cities.

Naghavi, M., Ong, K. L., & Das, S. (2024). Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021.

Sheykhfard, A., Azmoodeh, M., Kutela, B., Das, S., & Fountas, G. (2024). From self-reports to observations: Unraveling digital billboard influence on drivers. Transportation Research Part F: Psychology and Behaviour.

Wei, Z., Das, S., Wu., Y., Li, Z., & Zhang, Y. (2024). Modeling the lagged impacts of hourly weather and speed variation factors on the segment crash risk of rural interstate freeways: Applying a space–time-stratified case-crossover design. Accident Analysis & Prevention.

Kutela, B., Salum, J. H., Seif, S. R., Das, S., & Kidando, E. (2024). Navigating the blame game: Investigating automated vehicle fault in collisions under mixed traffic conditions. Robotics and Autonomous Systems.

Das, S., Barua, S., & Hossain, A. (2024). Unraveling the complex relationship between weather conditions and traffic safety. Journal of Transportation Safety & Security.

Chakraborty, R., Javed, S. A., Das, S., Kutela, B., & Khan, M. N. (2024). Impact of level 2 automation on driver behavior: A study using association rules mining. Transportation Research Part F: Traffic Psychology and Behaviour.

Kutela, B., Shita, H., Das, S., Kapaya, L., & Tarimo, E. (2024). Exploring the Role of Sponsoring Agencies in Shaping the MUTCD Using Supervised and Unsupervised Text Mining. Journal of Transportation Engineering, Part A: Systems.

Dzinyela, R., Shirazi, M., Das, S., & Lord, D. (2024). The negative Binomial-Lindley model with Time-Dependent Parameters: Accounting for temporal variations and excess zero observations in crash data. Accident Analysis & Prevention.

Somvanshi, S., Das, S., Javed, S. A., Antariksa, G., & Hossain, A. (2024). A Survey on Deep Tabular Learning. arXiv Preprint.

Kavianpour, S., Haghighi, F., Sheykhfard, A., Das, S., Fountas, G., & Oshanreh, M. M. (2024). Assessing the risk of pedestrian crossing behavior on suburban roads using structural equation model. Journal of Traffic and Transportation Engineering.

Sheykhfard, A., Haghighi, F., Saeidi, S., SafariTaherkhani, M., & Das, S. (2024). Understanding the influence of environmental factors on driver speed: A structural equation modeling analysis.

Kutela, B., Novat, N., Novat, N., Kalambay, P., & Das, S. (2024). Exploring Diversity of Activities on Shared-Use Paths: Factors and Implications for Planning and Design. Journal of Transportation Engineering, Part A: Systems.

Dzinyela, R., Adanu, E. K., Gupta, H., Koirala, P., Alnawmasi, N., Das, S., & Lord, D. (2024). Analyzing fatal crash patterns of recidivist drivers across genders and age Groups: A hazard-based duration approach. Accident Analysis & Prevention.

Kutela, B., Menon, N., Herman, J., Ruseruka, C., & Das, S. (2024). A regression-content analysis approach to assess public satisfaction with shared mobility measures against COVID-19 pandemic.

Liu, J., Zhan, F. B., Khan, M. N., & Das, S. (2024). Spatial analysis of geographical disparities in pedestrian safety. Transport Policy.

Hossain, A., Sun, X., Islam, S., Rahman, A., & Das, S. (2024). Single-vehicle roadway departure crashes at rural two-lane highway curved segments: a diagnosis using pattern recognition. International Journal of Transportation Science and Technology.

Dzinyela, R., Jafari, M., Das, S., Shimu, T. H., Alnawmasi, N., & Lord, D. (2024). Unconstrained and partially constrained temporal modelling of pedestrian injury severities. Transportmetrica A: Transport Science.

Das, S. (2024). Global estimates on the number of people blind or visually impaired by cataract: a meta-analysis from 2000 to 2020. Eye.

Chakraborty, R., Das, S., & Khan, M. N. (2024). Uncovering pedestrian midblock crash severity patterns using association rules mining. Transportmetrica A: Transport Science.

Hossain, A., Sun, X., Das, S., Jafari, M., & Codjoe, J. (2024). Investigating older driver crashes on high-speed roadway segments: a hybrid approach with extreme gradient boosting and random parameter model. Transportmetrica A: Transport Science.

Somvanshi, S., Liu, J., & Das, S. (2024). Gen-AI for TSMO Knowledge Management. ACM Computing Surveys. Retrieved from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5049945

Oliaee, A. H., Das, S., & Le, M. (2024). Automating Pedestrian Crash Typology Using Transformer Models. Transportation Research Record, 2679(2), 83–95. https://doi.org/10.1177/036119812412606

Das, S., Rahman, M. A., Liu, J., Ye, X., & Kutela, B. (2024). Association Patterns of Work Zone Crashes using Bayesian Network. Transportation Research Record. https://doi.org/10.1177/03611981241270161

Das, S., Somvanshi, S., Barua, S., & Liu, J. (2024). Gen-AI for Transportation Planning. ACM Computing Surveys. Retrieved from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5049928

Chakraborty, R., Das, S., Mimi, M. S., & Kutela, B. (2024). Investigating Factor Associations in Barrier Crashes through Cluster Correspondence Analysis. Transportation Research Record, 2679(4). https://doi.org/10.1177/03611981241297976

Sheykhfard, A., Haghighi, F., Saeidi, S., SafariTaherkhani, M., Fountas, G., & Das, S. (2024). Behavioral modeling of drivers near speed control cameras: A dual perspective from micro and macro data. Transportation Research Record, 2679(4). https://doi.org/10.1177/03611981241287787

Geedipally, S., Das, S., Wu, L., & Pratt, M. P. (2024). Safety Performance Functions for Frontage Roads. Transportation Research Record. https://doi.org/10.1177/03611981241277819

Das, S., Chakraborty, R., Sheykhfard, A., Kutela, B., & Ye, X. (2024). Using Perceptual Cycle Model and Text Mining to Investigate Ambulance Traffic Crashes. Transportation Research Record, 2679(2). https://doi.org/10.1177/03611981241270157

Kong, X., Zhang, Y., Chen, X., Das, S., & Sheykhfard, A. (2024). Case Study on the Relationship Between Socio-Demographic Characteristics and Work-from-Home Behavior Before, During, and After the COVID-19 Pandemic. Transportation Research Record. https://doi.org/10.1177/03611981231172946

Oliaee, A. H., Das, S., & Le, M. (2024). Automating Pedestrian Crash Typology using Transformer Models. Transportation Research Record.

Ye, X., Newman, G., Zhai, W., Retchless, D., Das, S., Ham, Y., … Huang, X. (n.d.). Towards coastal infrastructure resiliency: an AI-enabled decision-support framework for multi-scale comprehension and stakeholder empowerment. Transactions of the American Philosophical Society.

Steinmetz, J. D., Seeher, K. M., & Das, S. (2024). Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. The Lancet Neurology. https://doi.org/10.1016/S1474-4422(24)00038-3

Wei, Z., Das, S., Wu, Y., Li, Z., & Zhang, Y. (2024). Modelling the Lagged Impacts of Hourly Weather and Speed Variation Factors on the Segment Crash Risk of Rural Interstate Freeways: Applying a Space-Time-Stratified Case-Crossover Design. Accident Analysis and Prevention. https://doi.org/10.2139/ssrn.4379772

Faroughi, S. A., Pawar, N. M., Fernandes, C., Raissi, M., Das, S., Kalantari, N. K., & Mahjour, S. K. (2024). Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks and Operators in Scientific Computing for Fluid and Solid Mechanics. Journal of Computing and Information Science in Engineering.

Kutela, B., Das, S., Shita, H., & Novat, N. (2024). Understanding Socio-Demographic Factors associated with Shared-Use-Paths (SUPs) Utilization. Journal of Cycling and Micromobility Research.

Khan, M. N., Das, S., & Liu, J. (2024). Predicting Pedestrian-Involved Crash Severity Using Inception-v3 Deep Learning Model  . Accident Analysis & Prevention.

Khodadadi, A., Tsapakis, I., Shirazi, M., Das, S., & Lord, D. (2023). Derivation of the Empirical Bayesian method for the Negative Binomial-Lindley generalized linear model with application in traffic safety. Accident Analysis & Prevention, 170. https://doi.org/https://doi.org/10.1016/j.aap.2022.106638

Wei, Z., Das, S., Wu, Y., Li, Z., & Zhang, Y. (2023). Investigating the exposure-lag-response association of hourly weather and speed variation factors on rural freeway crash risk: A space-time-stratified case-crossover study. Accident Analysis & Prevention.

Al-Gharabi, A., Zubaidi, H., & Das, S. (2023). A scientometric analysis and bibliometric review of driver injury severity crash studies. Al-Qadisiyah Journal for Engineering Sciences, 16(1).

Das, S., & Zubaidi, H. (2023). City transit rider tweets: Understanding sentiments and politeness. Journal of Urban Technology, 30(1), 111–126.

Dobrovolny, C., Dadashova, B., Tabesh, M., Das, S., Kwon, H., Bligh, R., … Hallmark, S. (2023). Addressing Encroachment-Related Safety Issues in Work Zones: A Guide. Washington DC: NCHRP.

Das, S., Warner, J., Lavrenz, S., & Khanal, B. (2023). Safety Enhancements at Short-Storage-Space Railroad Crossings.

Dobrovolny, C., Dadashova, B., Tabesh, M., Das, S., Kwon, H., Bligh, R., … Hallmark, S. (2023). Determination of Work Zone Encroachments. NCHRP Web-Only Report.

J., M., Storey, B., Das, S., Habermann, J., & Bullard, L. (2023). Long-Term Vegetation Management Strategies for Roadsides and Roadside Appurtenances (350th ed.).

Das, S., Tsapakis, I., Torbic, D., Li, S., & Wang, Y. (2023). Developing AI-driven Safe Navigation Tool. SafeD UTC Report.

Moberg, M., Hamilton, E., & Das, S. (2023). Global, regional, and national mortality due to unintentional carbon monoxide poisoning. The Lancet Public Health.

Tamakloe, R., Adanu, E., Atandzi, J., Das, S., Lord, D., & Park, D. (2023). Stability of factors influencing walking-along-the-road pedestrian injury severity outcomes under different lighting conditions: A random parameters logit approach with heterogeneity in means and out-of-sample predictions. Accident Analysis & Prevention.

Sheykhfard, A., Haghighi, F., Kavianpour, S., Das, S., Farahani, P., & Fountas, G. (2023). Risk assessment of pedestrian red-light violation behavior using surrogate safety measures: Influence of human, road, vehicle, and environmental factors. IATSS Research. https://doi.org/https://doi.org/10.1016/j.iatssr.2023.11.003

Islam, S., Uddin, R., & Das, S. (2023). The burden of diseases and risk factors in Bangladesh, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet Global Health. https://doi.org/https://doi.org/10.1016/S2214-109X(23)00432-1

Ye, X., Li, S., Das, S., & Du, J. (2023). Enhancing routes selection with real-time weather data integration in spatial decision support systems. Spatial Information Research. https://doi.org/https://doi.org/10.1007/s41324-023-00564-8

Hossain, A., Sun, X., Alam, S., Das, S., & Sheykhfard, A. (2023). Crash Contributing Factors and Patterns Associated with Fatal Truck-Involved Crashes in Bangladesh: Findings from the Text Mining Approach. Transportation Research Record. https://doi.org/https://doi.org/10.1177/03611981231209031

Cullen, P., Cullen, A. E., Francis, K. L., & Das, S. (2023). Interpersonal violence and gender inequality in adolescents: a systematic analysis of Global Burden of Disease data from 1990 to 2019. Journal of Adolescent Health. https://doi.org/https://doi.org/10.1016/j.jadohealth.2023.08.044

Kutela, B., Das, S., & Sener, I. (2023). Exploring the Shared Use Pathway: A Review of the Design and Demand Estimation Approaches. Urban, Planning and Transport Research, 11(1). https://doi.org/10.1080/21650020.2023.2233597

Sheykhfard, A., Haghighi, F., Das, S., & Fountas, G. (2023). Evasive actions to prevent pedestrian collisions in varying space/time contexts in diverse urban and non-urban areas. Accident Analysis & Prevention. https://doi.org/https://doi.org/10.1016/j.aap.2023.107270

Das, S., Kutela, B., & Menon, N. (2023). Unlocking the narrative: using text mining to reveal the hidden factors behind suicide related traffic crashes. Archives of Suicide Research. https://doi.org/10.1080/13811118.2023.2247026

Das, S., Dutta, A., Tamakloe, R., & Khan, M. (2023). Analyzing the time-varying patterns of contributing factors in work zone-related crashes. Journal of Transportation Safety & Security, 1–28. https://doi.org/https://doi.org/10.1080/19439962.2023.2246020

Sheykhfard, A., Haghighi, F., Papadimitriou, E., Das, S., & Gelder, P. (2023). Exploring the Influence of Signal Countdown Timers on Driver Behavior: An Analysis of Pedestrian–Vehicle Conflicts at Signalized Intersections. Transportation Research Record. https://doi.org/10.1177/03611981231186987

Das, S., Kong, X., Wei, Z., Xiao, X., Mills, D., & Hossain, A. (2023). Probing into Driver Speeding Patterns and Their Influence on Child Occupancy in Urban Areas. Transportation Research Record. https://doi.org/https://doi.org/10.1177/03611981231188

Das, S., Hossain, A., Rahman, M., Sheykhfard, A., & Kutela, B. (2023). Case Study on the Traffic Collision Patterns of E-Scooter Riders. Transportation Research Record. https://doi.org/https://doi.org/10.1177/03611981231185770

Tamakloe, R., Das, S., Adanu, E. K., & Park, D. (2023). Key factors affecting motorcycle-barrier crash severity: an innovative cluster-regression technique. Transportmetrica A: Transport Science, 1–25. https://doi.org/10.1080/23249935.2023.2230310

Hossain, M., Zhou, H., & Das, S. (2023). Data mining approach to explore emergency vehicle crash patterns: A comparative study of crash severity in emergency and non-emergency response modes. Accident Analysis & Prevention. https://doi.org/https://doi.org/10.1016/j.aap.2023.107217

Kutela, B., Msechu, K., Kidando, E., Das, S., & Kitali, A. (2023). Eliciting the influence of roadway and traffic conditions on hurricane evacuation decisions using regression-content analysis approach. Travel Behaviour and Society. https://doi.org/https://doi.org/10.1016/j.tbs.2023.100623

Das, S., Sheykhfard, A., Liu, J., & Khan, M. (2023). Understanding non-motorists’ views on automated vehicle safety through Bayesian network analysis and latent dirichlet allocation. International Journal of Transportation Science and Technology. https://doi.org/10.1016/j.ijtst.2023.06.002

Das, S., Khodadadi, A., & Liu, J. (2023). Short-Duration Crash Modeling to Understand the Impact of Operating Speed on Freeway Crashes During COVID-19. Transportation Research Record. https://doi.org/10.1177/03611981231169283

Sheykhfard, A., Haghighi, F., & Das, S. (2023). How does talking with passengers threatens pedestrian life? An analysis of drivers’ performance based on real-world driving data. Transportation Research Part F: Traffic Psychology and Behaviour, 95, 464–479. https://doi.org/10.1016/j.trf.2023.05.010

Das, S., Hossein, A., Vierkant, V., & Liu, J. (2023). Using Bidirectional Encoder Representations from Transformers (BERT) to Classify Traffic Crash Severity Types. Natural Language Processing, 3. https://doi.org/10.1016/j.nlp.2023.100007

Rahman, M., Das, S., Codjoe, J., Mitran, E., Sun, X., Abedi, K., & Hossain, M. (2023). Applying Data Mining Methods to Explore Animal-Vehicle Crashes. Transportation Research Record. https://doi.org/10.1177/03611981231166688

Das, S., Vierkant, V., Gonzalez, J., Kutela, B., & Sheykfard, A. (2023). Bayesian Network for Motorcycle Crash Severity Analysis. Transportation Research Record. https://doi.org/10.1177/03611981231164386

Hasan, A., Jalayer, M., Das, S., & Kabir, M. (2023). Application of Machine Learning Models and SHAP to Examine Crashes Involving Young Drivers in New Jersey. International Journal of Transportation Science and Technology. https://doi.org/10.1016/j.ijtst.2023.04.005

Das, S., Khodadadi, A., & Liu, J. (2023). Scientometric and Bibliographic Analysis of Pedestrian Safety Research. Transportation Research Record. https://doi.org/https://doi.org/10.1177/03611981231167

Hossain, A., Sun, X., Thapa, R., Hossain, M., & Das, S. (2023). Exploring association of contributing factors to pedestrian fatal and severe injury crashes under dark-no-streetlight condition. IATSS Research. https://doi.org/https://doi.org/10.1016/j.iatssr.2023.03.002

Mahdi, A., Zubaidi, H., & Das, S. (2023). A scientometric analysis and bibliometric review of driver injury severity crashes studies. Al-Qadisiyah Journal for Engineering Sciences. https://doi.org/10.30772/qjes.v16i1.870

Das, S., Weng, Y., & Paal, S. (2023). Applying Few-Shot Learning in Classifying Pedestrian Crash Typing. Transportation Research Record. https://doi.org/10.1177/03611981231157393

Das, S., Hossain, A., Le, M., Pratt, M., & Wu, J. (2023). Classifying Pedestrian Maneuver Types Using the Advanced Language Model. Transportation Research Record. https://doi.org/10.1177/03611981231155187

Rahman, M., Dey, K., Pyrialakou, V., & Das, S. (2023). Factors influencing safety perceptions of sharing roadways with autonomous vehicles among vulnerable roadway users. Journal of Safety Research. https://doi.org/10.1016/j.jsr.2023.02.010

Sheykhfard, A., Haghighi, F., Fountas, G., Das, S., & Khanpour, A. (2023). How do driving behavior and attitudes toward road safety vary between developed and developing countries? Evidence from Iran and the Netherlands. Journal of Safety Research. https://doi.org/10.1016/j.jsr.2023.02.005

Das, S., Tamakloe, R., Zubaidi, H., Obaid, I., & Rahman, M. (2023). Bicyclist injury severity classification using a random parameter logit model. International Journal of Transportation Science and Technology. https://doi.org/https://doi.org/10.1016/j.ijtst.2023.02.001

Dey, K., Rahman, M., Das, S., & Williams, A. (2023). Left turn phasing selection considering vehicle to vehicle and vehicle to pedestrian conflicts. Journal of Traffic and Transportation Engineering. https://doi.org/10.1016/j.jtte.2021.07.006

Hossain, A., Sun, X., Alam, S., & Das, S. (2023). Crash Contributing Factors and Patterns Associated with Fatal Truck-involved Crashes in Bangladesh: Findings from Text Mining Approach. Transportation Research Record. https://doi.org/10.6084/m9.figshare.21937229.v1

Das, S., Rahman, M., Kabir, N., Oviedo-Trespalacios, O., Dey, K., & Hossain, M. (2023). Do people act differently while using ridesharing services with children? Transportation Research Part A: Policy and Practice, 171. https://doi.org/https://doi.org/10.1016/j.trf.2023.05.010

Faroughi, S. A., Pawar, N. M., Fernandes, C., Das, S., Kalantari, N., & Mahjour, K. (2022). Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks in Scientific Computing. Arxiv. https://doi.org/https://doi.org/10.48550/arXiv.2211.07377

Dixon, K., Park, E. S., Brewer, M., Wu, L., Geedipally, S., Srinivasan, R., … Rista, E. (2022). NCHRP Report 995: Guidelines for Treatments to Mitigate Opposite Direction Crashes. Transportation Research Board. https://doi.org/10.17226/26586

Das, S., Le, M., Fitzpatrick, K., & Wu, D. (2022). Did Operating Speeds During COVID-19 Result in More Fatal and Injury Crashes on Urban Freeways? Transportation Research Record: Journal of the Transportation Research Board. https://doi.org/10.1177/03611981221109597

Obaid, I., Alnedawi, A., Aboud, G. M., Tamakloe, R., Zubaidi, H., & Das, S. (2022). Factors associated with driver injury severity of motor vehicle crashes on sealed and unsealed pavements: Random parameter model with heterogeneity in means and variances. International Journal of Transportation Science and Technology. https://doi.org/10.1016/j.ijtst.2022.04.002

Das, S., & Sarkr, S. (2022). News media mining to explore speed-crash-traffic association during COVID-19. Transportation Research Record: Journal of the Transportation Research Board.

Hossain, M. M., Zhao, H., Rahman, M. A., Das, S., & Sun, X. (2022). Cellphone-Distracted Crashes of Novice Teen Drivers: Understanding Associations of Contributing Factors for Crash Severity Levels and Cellphone Usage Types. Traffic Injury Prevention. https://doi.org/https://doi.org/10.1080/15389588.2022.2097667

Das, S., Park, E. S., & Sarkar, S. (2022). Impact of operating speed measures on traffic crashes: Annual and daily level models for rural two-lane and rural multilane roadways. Journal of Transportation Safety & Security. https://doi.org/https://doi.org/10.1080/19439962.2022.2098441

Hasan, A. S., Kabir, M. A. B., Jalayer, M., & Das, S. (2022). Severity modeling of work zone crashes in New Jersey using machine learning models. Journal of Transportation Safety & Security. https://doi.org/https://doi.org/10.1080/19439962.2022.2098442

Das, S., Le, M., Hossain, A., Wu, D., & Pratt, M. (2022). Classifying Pedestrian Maneuver Types using Advanced Language Model. Transportation Research Record: Journal of the Transportation Research Board.

Kong, X., Das, S., Zhang, Y., Wu, L., & Wallis, J. (2022). In-Depth Understanding of Pedestrian–Vehicle Near-Crash Events at Signalized Intersections: An Interpretable Machine Learning Approach. Transportation Research Record: Journal of the Transportation Research Board. https://doi.org/https://doi.org/10.1177/03611981221136138

Das, S., Hossain, M., Rahman, A., Kong, X., Sun, X., & Mamun, G. (2022). Understanding Patterns of Moped And Seated Motor Scooter (50 Cc Or Less) Involved Fatal Crashes Using Cluster Correspondence Analysis. Transportmetrica A: Transport Science.

Hossain, M., Zhou, H., Das, S., Sun, X., & Hossain, A. (2022). Young Drivers and Cellphone Distraction: Pattern Recognition from Fatal Crashes. Journal of Transportation Safety & Security.

Das, S., & Trisha, N. (2022). Understanding social media usage patterns by transit agencies.

Das, S., Tamakloe, R., Zubaidi, H., & Vierkant, V. (2022). Virtual Public Engagement and Communications in a Transportation Conference during COVID-19.

Das, S., Dutta, A., Rahman, M., & Sun, X. (2022). Pattern recognition from light delivery vehicle crash characteristics. Journal of Transportation Safety & Security, 14(12), 2055–2073.

Wei, Z., Das, S., & Zhang, Y. (2022). Short duration crash prediction for rural two-lane roadways: applying explainable artificial intelligence. Transportation Research Record, 2676(12).

Hosseini, P., Khoshsirat, S., Jalayer, M., Das, S., & Zhou, H. (2022). Application of text mining techniques to identify actual wrong-way driving (WWD) crashes in police reports. International Journal of Transportation Science and Technology. https://doi.org/10.1016/j.ijtst.2022.12.002

Geedipally, S., Dixon, K., Wu, L., Pratt, M., Avelar, R., Das, S., … Saini, G. (2022). Calibrating the Highway Safety Manual Predictive Methods for Texas Highways.

Rahman, M., Das, S., & Sun, X. (2022). Understanding the drowsy driving crash patterns from correspondence regression analysis. Journal of Safety Research. https://doi.org/https://doi.org/10.1016/j.jsr.2022.10.017

Das, S., Wei, Z., & Dutta, A. (2022). Rules mining on hybrid electric vehicle consumer complaint database. Journal of Transportation Safety & Security, 1–21. https://doi.org/10.1080/19439962.2022.2147614

Kong, X., Das, S., Zhang, Y., Wei, Z., & Yuan, C. (2022). In-Depth Understanding of Pedestrian- Vehicle Near-Crash Events at Signalized Intersections: An Interpretable Machine Learning Approach. International Journal of Transportation Science and Technology. https://doi.org/10.1177/03611981221136138

Faroughi, S. A., Pawar, N. M., Fernandes, C., Das, S., Kalantari, N., & Mahjour, K. (2022). Deep Learning in Computational Mechanics: Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks. Arxiv. https://doi.org/https://doi.org/10.48550/arXiv.2211.07377

Kong, X., Das, S., Zhang, Y., Wu, L., & Wallis, J. (2022). In-Depth Understanding of Near-Crash Events Through Pattern Recognition. Transportation Research Record: Journal of the Transportation Research Board. https://doi.org/10.1177/03611981221097395

Rahman, M., Sun, X., & Das, S. (2022). Understanding the Drowsy Driving Crash Patterns from Corresponding Regression Analysis. Journal of Safety Research.

Das, S., Fitzpatrick, K., Wu, L., Wei, Z., Tsapakis, I., Paal, S., … Park, E. (2022). Develop a Real-Time Decision Support Tool for Rural Roadway Safety Improvements. TXDOT.

Das, S. (2022). Applying Explainable Machine Learning Techniques in Daily Crash Occurrence and Severity Modeling for Rural Interstates. Transportation Research Record. https://doi.org/10.1177/03611981221134629

Rahman, M., Das, S., Sun, X., Sun, M., & Hossain, M. (2022). Using Unsupervised Learning to Investigate Injury-Associated Factors of Animal-Vehicle Crashes. International Journal of Injury Control and Safety Promotion. https://doi.org/10.1080/17457300.2022.2125532

Das, S., X, K., & Hossain, M. (2022). Exploration on Prior Driving Modes for Automated Vehicle Collisions. International Journal of Urban Sciences. https://doi.org/10.1080/12265934.2022.2142650

Sohrabi, S., Wang, Y., Das, S., & Paal, S. (2022). Safe Route-Finding: A Review of Literature and Future Directions. Accident Analysis and Prevention. https://doi.org/10.1016/j.aap.2022.106816

Das, S., Wei, Z., & Dutta, A. (2022). Rules Mining and Narrative Analysis of Consumer Complaints on Hybrid Electric Vehicles.

Das, S., Aman, J. J. C., & Rahman, M. A. (2022). Content Analysis on Homelessness Issues at Airports by News Media Mining. Transportation Research Record: Journal of the Transportation Research Board. https://doi.org/10.1177/03611981221108151

Haberman, J., Holik, W., Huang, W., Das, S., Rista, E., & Clotch, D. (2022). NCHRP 06-18 Report: Guide for Snow and Ice Control Operations. Washington, D.C.: Transportation Research Board. Retrieved from https://onlinepubs.trb.org/onlinepubs/nchrp/docs/NCHRP_06-18_Final_Report.pdf

Das, S., Tamakloe, R., Kutela, B., & Hossain, A. (2022). Pattern Recognition from Injury Severity Types of Frontage Roadway Crashes. Journal of Transportation Safety and Security. https://doi.org/10.1080/19439962.2022.2123581

Rahman, S., Das, S., & Sun, X. (2022). Single-Vehicle Run-Off Road Crashes Because of Cellphone Distraction: Finding Patterns with Rule Mining. Transportation Research Record: Journal of the Transportation Research Board. https://doi.org/10.1177/03611981221122781

Das, S., Wei, Z., & Ravuri, V. (2022). Safety and Operations of Automated Delivery Vehicles. SafeD.

Das, S. (2022). Artificial Intelligence in Highway Safety. Boca Raton, FL, USA: CRC Press. Retrieved from https://www.amazon.com/Artificial-Intelligence-Highway-Safety-Subasish/dp/0367436701/

Ashifur Rahman, M., Das, S., & Sun, X. (2022). Using Cluster Correspondence Analysis to Explore Rainy Weather Crashes in Louisiana. Transportation Research Record: Journal of the Transportation Research Board, 2676(8), pp 159--173. https://doi.org/10.1177/03611981221082582

Kong, X., Li, Z., Zhang, Y., & Das, S. (2022). Bridge Deck Deterioration: Reasons and Patterns. Transportation Research Record: Journal of the Transportation Research Board, 2676(7), pp 570--584. https://doi.org/10.1177/03611981221080140

Tamakloe, R., Sam, E. F., Bencekri, M., Das, S., & Park, D. (2022). Mining groups of factors influencing bus/minibus crash severities on poor pavement condition roads considering different lighting status. Traffic Injury Prevention, 23(5), pp 308--314. https://doi.org/10.1080/15389588.2022.2066658

Das, S., Mousavi, S. M., & Shirinzad, M. (2022). Pattern recognition in speeding related motorcycle crashes. Journal of Transportation Safety \& Security, 14(7), pp 1121--1138. https://doi.org/10.1080/19439962.2021.1877228

Khodadadi, A., Tsapakis, I., Shirazi, M., Das, S., & Lord, D. (2022). Derivation of the Empirical Bayesian method for the Negative Binomial-Lindley generalized linear model with application in traffic safety. Accident Analysis \& Prevention, 170, 106638. https://doi.org/10.1016/j.aap.2022.106638

Fitzpatrick, K., Do, A., Avelar, R., Pratt, M., & Das, S. (2022). Improving Pedestrian Safety at Signalized Intersections: Impacts of Corner Radius. ITE Journal, 92(6), pp 37--43. Retrieved from https://trid.trb.org/view/2006270

Kong, X., Zhang, A., Xiao, X., Das, S., & Zhang, Y. (2022). Work from home in the post-COVID world. Case Studies on Transport Policy, 10(2), pp 1118--1131. https://doi.org/10.1016/j.cstp.2022.04.002

Das, S., Kong, X. J., Lavrenz, S. M., Wu, L., & Jalayer, M. (2022). Fatal crashes at highway rail grade crossings: A U.S. based study. International Journal of Transportation Science and Technology, 11(1), pp 107--117. https://doi.org/10.1016/j.ijtst.2021.03.002

Das, S., Trisha, N., Sener, I., & Walk, M. (2022). TCRP Synthesis 156: Uses of Social Media in Public Transportation. TCRP.

Tamakloe, R., Das, S., Aidoo, E. N., & Park, D. (2022). Factors affecting motorcycle crash casualty severity at signalized and non-signalized intersections in Ghana: Insights from a data mining and binary logit regression approach. Accident Analysis \& Prevention, 165, 106517. https://doi.org/10.1016/j.aap.2021.106517

Das, S., Sun, X., Dadashova, B., Rahman, M. S., & Sun, M. (2022). Identifying Patterns of Key Factors in Sun Glare-Related Traffic Crashes. Transportation Research Record: Journal of the Transportation Research Board, 2676(2), pp 165--175. https://doi.org/10.1177/03611981211037891

Tsapakis, I., Das, S., Anderson, P., Jessberger, S., & Holik, W. (2022). Improving Stratification Procedures and Accuracy of Annual Average Daily Traffic (AADT) Estimates for Non-Federal Aid-System (NFAS) Roads. Transportation Research Record: Journal of the Transportation Research Board, 2676(2), pp 393--406. https://doi.org/10.1177/03611981211043544

Kutela, B., Das, S., & Dadashova, B. (2022). Mining patterns of autonomous vehicle crashes involving vulnerable road users to understand the associated factors. Accident Analysis \& Prevention, 165. https://doi.org/10.1016/j.aap.2021.106473

Das, S., Tabesh, M., Dadashova, B., & Dobrovolny, C. (2022). Diagnosis of Encroachment-Related Work-Zone Crashes by Applying Pattern Recognition. Transportation Research Record. https://doi.org/https://doi.org/10.1177/03611981231152254

Das, S., Sun, X., Goel, S., Sun, M., Rahman, A., & Dutta, A. (2022). Flooding Related Traffic Crashes: Findings from Association Rules. Journal of Transportation Safety \& Security, 14(1), pp 111--129. https://doi.org/10.1080/19439962.2020.1734130

Das, S., & Kong, X. (2022). Quantifying Bridge Element Vulnerability over Time. Transportation Research Record: Journal of the Transportation Research Board, 2676(1), pp 460--471. https://doi.org/10.1177/03611981211036380

Das, S., & Dutta, A. (2022). Twelve-Year Analysis of Transportation Research Board Annual Meeting’s Official Hashtag. Transportation Research Record: Journal of the Transportation Research Board, 2676(1), pp 763--772. https://doi.org/10.1177/03611981211037232

Fitzpatrick, K., Avelar, R., Pratt, M. P., Das, S., Lord, D., Texas A\&M Transportation Institute, & Administration, F. H. (2022). Crash Modification Factor for Corner Radius, Right-Turn Speed, and Prediction of Pedestrian Crashes at Signalized Intersections (p. 136p). Retrieved from https://www.fhwa.dot.gov/publications/research/safety/21105/21105.pdf

Fitzpatrick, K., Das, S., Pratt, M. P., Dixon, K., & Gates, T. (2021). Development of a Posted Speed Limit Setting Procedure and Tool. Transportation Research Board. Retrieved from http://www.trb.org/Main/Blurbs/182154.aspx

Fitzpatrick, K., Das, S., Pratt, M. P., Dixon, K., & Gates, T. (2021). Posted Speed Limit Setting Procedure and Tool: User Guide. Transportation Research Board. Retrieved from http://www.trb.org/Main/Blurbs/182038.aspx

Das, S., Trisha, N. F., Sener, I. N., & Walk, M. (2021). Uses of Social Media in Public Transportation. Transportation Research Board. Retrieved from https://www.trb.org/Main/Blurbs/182636.aspx

Hosseini, P., Jalayer, M., Das, S., & Board, T. R. (2021). A Multiple Correspondence Approach to Identify Contributing Factors Related to Work Zone Crashes (p. 19p). Retrieved from https://annualmeeting.mytrb.org/OnlineProgram/Details/15753

Das, S., & Board, T. R. (2021). American Generations and Traffic Fatalities: Exploratory Evaluation from Person Level Data (p. 17p). Retrieved from https://annualmeeting.mytrb.org/OnlineProgram/Details/15775

Hosseini, P., Jalayer, M., Das, S., Zhou, H., & Board, T. R. (2021). Identifying Wrong-Way Driving (WWD) Crashes in Police Reports Using Text Mining Techniques (p. 16p). Retrieved from https://annualmeeting.mytrb.org/OnlineProgram/Details/15775

Das, S., Dutta, A., & Board, T. R. (2021). Light Delivery Vehicles Crashes: Identifying Insights using Joint Dimension Reduction and Clustering (p. 16p). Retrieved from https://annualmeeting.mytrb.org/OnlineProgram/Details/15793

Das, S., Theel, M., & Board, T. R. (2021). Pandemic and Transportation Research: Bibliometric Analysis and Topic Modeling (p. 16p). Retrieved from https://annualmeeting.mytrb.org/OnlineProgram/Details/15738

Das, S., Lavrenz, S. M., Wu, L., Jalayer, M., Kong, X., & Board, T. R. (2021). Pattern Recognition from Rail Grade Crossing Fatal Crashes (p. 17p). Retrieved from https://annualmeeting.mytrb.org/OnlineProgram/Details/15713

Das, S., Wang, R., & Board, T. R. (2021). Racism discussed in Transportation Research: Bibliometric Analysis and Topic Modeling (p. 16p). Retrieved from https://annualmeeting.mytrb.org/OnlineProgram/Details/15738

Shipp, E., Das, S., Smith, S., Wu, L., Sun, X., Texas A\&M Transportation Institute, … Administration, F. H. (2021). Louisiana’s Alcohol-Impaired Driving Problem: An Analysis of Crash and Cultural Factors (p. 185p). Retrieved from https://www.ltrc.lsu.edu/pdf/2021/FR_655.pdf

Geedipally, S. R., Brewer, M., Wunderlich, R., Pratt, M. P., Wu, L., Das, S., … Administration, F. H. (2021). Examine Trade-Offs Between Center Separation and Shoulder Width Allotment for a Given Roadway Width (p. 146p). Retrieved from https://static.tti.tamu.edu/tti.tamu.edu/documents/0-7035-R1.pdf

Fitzpatrick, K., Avelar, R., Pratt, M. P., Das, S., & Lord, D. (2021). Crash Modification Factor for Corner Radius, Right-Turn Speed, and Prediction of Pedestrian Crashes at Signalized Intersections. Federal Highway Administration. Retrieved from https://www.fhwa.dot.gov/publications/research/safety/21106/21106.pdf

Das, S., Datta, S., Zubaidi, H. A., & Obaid, I. A. (2021). Applying interpretable machine learning to classify tree and utility pole related crash injury types. IATSS Research, 45(3), pp 310--316. https://doi.org/10.1016/j.iatssr.2021.01.001

Sun, M., Sun, X., Rahman, M., Akter, M., & Das, S. (2021). Modeling two-way stop-controlled intersection crashes with zero-inflated models on Louisiana rural two-lane highways. IATSS Research, 45(3), pp 303--309. https://doi.org/10.1016/j.iatssr.2020.12.007

Kong, X., Das, S., Zhou, Hongmin “Tracy,” & Zhang, Y. (2021). Patterns of near-crash events in a naturalistic driving dataset: Applying rules mining. Accident Analysis \& Prevention, 161. https://doi.org/10.1016/j.aap.2021.106346

Das, S., Tsapakis, I., & Khodadadi, A. (2021). Safety performance functions for low-volume rural minor collector two-lane roadways. IATSS Research, 45(3), pp 347--356. https://doi.org/10.1016/j.iatssr.2021.02.004

Das, S. (2021). Understanding Fatal Crash Reporting Patterns in Bangladeshi Online Media using Text Mining. Transportation Research Record: Journal of the Transportation Research Board, 2675(10), pp 960--971. https://doi.org/10.1177/03611981211014200

Das, S., Tamakloe, R., Zubaidi, H., Obaid, I., & Alnedawi, A. (2021). Fatal pedestrian crashes at intersections: Trend mining using association rules. Accident Analysis \& Prevention, 160. https://doi.org/10.1016/j.aap.2021.106306

Das, S., Sun, X., & Sun, M. (2021). Rule-based safety prediction models for rural two-lane run-off-road crashes. International Journal of Transportation Science and Technology, 10(3), pp 235--244. https://doi.org/10.1016/j.ijtst.2020.08.001

Das, S., Dutta, A., & Tsapakis, I. (2021). Topic Models from Crash Narrative Reports of Motorcycle Crash Causation Study. Transportation Research Record: Journal of the Transportation Research Board, 2675(9), pp 449--462. https://doi.org/10.1177/03611981211002523

Das, S. (2021). Autonomous vehicle safety: Understanding perceptions of pedestrians and bicyclists. Transportation Research Part F: Traffic Psychology and Behaviour, 81, pp 41--54. https://doi.org/10.1016/j.trf.2021.04.018

Fitzpatrick, K., Das, S., Gates, T., Dixon, K. K., & Park, E. S. (2021). Considering Roadway Context in Setting Posted Speed Limits. Transportation Research Record: Journal of the Transportation Research Board, 2675(8), pp 590--602. https://doi.org/10.1177/0361198121999618

Kong, X., Das, S., & Zhang, Y. (2021). Mining patterns of near-crash events with and without secondary tasks. Accident Analysis \& Prevention, 157. https://doi.org/10.1016/j.aap.2021.106162

Khodadadi, A., Tsapakis, I., Das, S., Lord, D., & Li, Y. (2021). Application of different negative binomial parameterizations to develop safety performance functions for non-federal aid system roads. Accident Analysis \& Prevention, 156. https://doi.org/10.1016/j.aap.2021.106103

Das, S., Dutta, A., & Geedipally, S. R. (2021). Applying Bayesian data mining to measure the effect of vehicular defects on crash severity. Journal of Transportation Safety \& Security, 13(6), pp 605--621. https://doi.org/10.1080/19439962.2019.1658674

Ashifur Rahman, M., Sun, X., Das, S., & Khanal, S. (2021). Exploring the Influential Factors of Roadway Departure Crashes on Rural Two-Lane Highways with Logit Model and Association Rules Mining. International Journal of Transportation Science and Technology, 10(2), pp 167--183. https://doi.org/10.1016/j.ijtst.2020.12.003

Das, S., Wei, Z., Kong, X., & Xiao, X. (2021). Mining crowdsourced data on bicycle safety critical events. Transportation Research Interdisciplinary Perspectives, 10. https://doi.org/10.1016/j.trip.2021.100360

Zubaidi, H., Obaid, I., Alnedawi, A., Das, S., & Haque, M. M. (2021). Temporal instability assessment of injury severities of motor vehicle drivers at give-way controlled unsignalized intersections: A random parameters approach with heterogeneity in means and variances. Accident Analysis \& Prevention, 156, 106151. https://doi.org/10.1016/j.aap.2021.106151

Das, S. (2021). Exploratory Analysis of Unmanned Aircraft Sightings using Text Mining. Transportation Research Record: Journal of the Transportation Research Board, 2675(5), pp 291--300. https://doi.org/10.1177/0361198120987230

Kong, X. J., Das, S., Zhang, Y., & Xiao, X. (2021). Lessons learned from pedestrian-driver communication and yielding patterns. Transportation Research Part F: Traffic Psychology and Behaviour, 79, pp 35--48. https://doi.org/10.1016/j.trf.2021.03.011

Das, S., Geedipally, S. R., & Fitzpatrick, K. (2021). Inclusion of speed and weather measures in safety performance functions for rural roadways. IATSS Research, 45(1), pp 60--69. https://doi.org/10.1016/j.iatssr.2020.05.001

Rahman, M. T., Dey, K., Das, S., & Sherfinski, M. (2021). Sharing the road with autonomous vehicles: A qualitative analysis of the perceptions of pedestrians and bicyclists. Transportation Research Part F: Traffic Psychology and Behaviour, 78, pp 433--445. https://doi.org/10.1016/j.trf.2021.03.008

Kong, X., Das, S., Zhou, H., & Zhang, Y. (2021). Characterizing phone usage while driving: Safety impact from road and operational perspectives using factor analysis. Accident Analysis \& Prevention, 152. https://doi.org/10.1016/j.aap.2021.106012

Park, E. S., Fitzpatrick, K., Das, S., & Avelar, R. (2021). Exploration of the relationship among roadway characteristics, operating speed, and crashes for city streets using path analysis. Accident Analysis \& Prevention, 150. https://doi.org/10.1016/j.aap.2020.105896

Das, S., Kong, X., & Tsapakis, I. (2021). Hit and run crash analysis using association rules mining. Journal of Transportation Safety \& Security, 13(2), pp 123--142. https://doi.org/10.1080/19439962.2019.1611682

Zubaidi, H. A., Obaid, I. A., Alnedawi, A., & Das, S. (2021). Motor vehicle driver injury severity analysis utilizing a random parameter binary probit model considering different types of driving licenses in 4-legs roundabouts in South Australia. Safety Science, 134. https://doi.org/10.1016/j.ssci.2020.105083

Jalayer, M., Pour-Rouholamin, M., Patel, D., Das, S., & Parvardeh, H. (2021). A Penalized-Likelihood Approach to Characterizing Bridge-Related Crashes in New Jersey. Traffic Injury Prevention, 22(1), pp 63--67. https://doi.org/10.1080/15389588.2020.1842379

Das, S. (2021). Data Dive into Transportation Research Record Articles: Authors, Coauthorships, and Research Trends. TR News, (331), pp 25--31. Retrieved from http://www.trb.org/Publications/Blurbs/182002.aspx

Das, S. (2021). Traffic volume prediction on low-volume roadways: a Cubist approach. Transportation Planning and Technology, 44(1), pp 93--110. https://doi.org/10.1080/03081060.2020.1851452

Das, S., Dutta, A., & Tsapakis, I. (2020). Automated vehicle collisions in California: Applying Bayesian latent class model. IATSS Research, 44(4), pp 300--308. https://doi.org/10.1016/j.iatssr.2020.03.001

Das, S., Ashraf, S., Dutta, A., & Tran, L.-N. (2020). Pedestrians Under Influence (PUI) Crashes: Patterns from Correspondence Regression Analysis. Journal of Safety Research, 75, pp 14--23. https://doi.org/10.1016/j.jsr.2020.07.001

Dadashova, B., Griffin, G. P., Das, S., Turner, S., & Sherman, B. (2020). Estimation of Average Annual Daily Bicycle Counts using Crowdsourced Strava Data. Transportation Research Record: Journal of the Transportation Research Board, 2674(11), pp 390--402. https://doi.org/10.1177/0361198120946016

Das, S., Dutta, A., & Brewer, M. A. (2020). Case Study of Trend Mining in Transportation Research Record Articles. Transportation Research Record: Journal of the Transportation Research Board, 2674(10), pp 1--14. https://doi.org/10.1177/0361198120936254

Das, S., & Dutta, A. (2020). Extremely serious crashes on urban roadway networks: Patterns and trends. IATSS Research, 44(3), pp 248--252. https://doi.org/10.1016/j.iatssr.2020.01.003

Das, S., Dutta, A., & Sun, X. (2020). Patterns of Rainy Weather Crashes: Applying Rules Mining. Journal of Transportation Safety \& Security, 12(9), pp 1083--1105. https://doi.org/10.1080/19439962.2019.1572681

Rahman, M., Sun, X., & Das, S. (2020). Reconfiguring Urban Undivided Four-Lane Highways to Five-Lane: A Nonideal but Very Effective Solution for Crash Reduction. Journal of Transportation Engineering, Part A: Systems, 146(10), 04020116. https://doi.org/10.1061/JTEPBS.0000422

Geedipally, S. R., Das, S., Pratt, M. P., & Lord, D. (2020). Determining Skid Resistance Needs on Horizontal Curves for Different Levels of Precipitation. Transportation Research Record: Journal of the Transportation Research Board, 2674(9), pp 358--370. https://doi.org/10.1177/0361198120929334

Das, S., & Geedipally, S. (2020). Rural Speed Safety Project for USDOT Safety Data Initiative: Findings and Outcome. ITE Journal, 90(9), pp 38--42. Retrieved from https://trid.trb.org/view/1742688

Das, S., Islam, M., Dutta, A., & Shimu, T. H. (2020). Uncovering Deep Structure of Determinants in Large Truck Fatal Crashes. Transportation Research Record: Journal of the Transportation Research Board, 2674(9), pp 742--754. https://doi.org/10.1177/0361198120931507

Kong, X., Das, S., Jha, K., & Zhang, Y. (2020). Understanding Speeding Behavior from Naturalistic Driving Data: Applying Classification Based Association Rule Mining. Accident Analysis \& Prevention, 144. https://doi.org/10.1016/j.aap.2020.105620

Das, S. (2020). Identifying key patterns in motorcycle crashes: findings from taxicab correspondence analysis. Transportmetrica A: Transport Science, 17(4), pp 593--614. https://doi.org/10.1080/23249935.2020.1802362

Das, S., Storey, B., Shimu, T. H., Mitra, S., Theel, M., & Maraghehpour, B. (2020). Severity analysis of tree and utility pole crashes: Applying fast and frugal heuristics. IATSS Research, 44(2), pp 85--93. https://doi.org/10.1016/j.iatssr.2019.08.001

Das, S., Dutta, A., Dey, K., Jalayer, M., & Mudgal, A. (2020). Vehicle involvements in hydroplaning crashes: Applying interpretable machine learning. Transportation Research Interdisciplinary Perspectives, 6, 100176. https://doi.org/10.1016/j.trip.2020.100176

Das, S., Le, M., & Dai, B. (2020). Application of machine learning tools in classifying pedestrian crash types: A case study. Transportation Safety and Environment, 2(2), pp 106--119. https://doi.org/10.1093/tse/tdaa010

Das, S., & Griffin, G. P. (2020). Investigating the Role of Big Data in Transportation Safety. Transportation Research Record: Journal of the Transportation Research Board, 2674(6), pp 244--252. https://doi.org/10.1177/0361198120918565

Avelar, R., Geedipally, S., Das, S., Wu, L., Kutela, B., Lord, D., … Administration, F. H. (2020). Evaluation of Roadside Treatments to Mitigate Roadway Departure Crashes: Technical Report (p. 120p). Retrieved from https://static.tti.tamu.edu/tti.tamu.edu/documents/0-6991-R1.pdf

Das, S., & Tsapakis, I. (2020). Interpretable Machine Learning Approach in Estimating Traffic Volume on Low-volume Roadways. International Journal of Transportation Science and Technology, 9(1), pp 76--88. https://doi.org/10.1016/j.ijtst.2019.09.004

Das, S., Geedipally, S., Avelar, R., Wu, L., Fitzpatrick, K., Banihashemi, M., … Administration, F. H. (2020). Rural Speed Safety Project for USDOT Safety Data Initiative: [supporting dataset]. Texas A\&M Transportation Institute. Retrieved from https://rosap.ntl.bts.gov/view/dot/48840

Turner, S., Martin, M., Griffin, G., Le, M., Das, S., Wang, R., … Technology. (2020). Exploring Crowdsourced Monitoring Data for Safety (p. 45p). Retrieved from https://www.vtti.vt.edu/utc/safe-d/wp-content/uploads/2020/04/TTI-Student-05_Final-Research-Report_Final.pdf

Das, S., Geedipally, S., Avelar, R., Wu, L., Fitzpatrick, K., Banihashemi, M., … Administration, F. H. (2020). Rural Speed Safety Project for USDOT Safety Data Initiative (p. 120p). Retrieved from https://rosap.ntl.bts.gov/view/dot/48840

Tsapakis, I., Das, S., Khodadadi, A., Lord, D., Morris, J., Li, E., … Technology. (2020). Use of Disruptive Technologies to Support Safety Analysis and Meet New Federal Requirements (p. 37p). Retrieved from https://safed.vtti.vt.edu/wp-content/uploads/2021/04/Final-Version-04-113-Use-of-Disruptive-Technologies-to-Support-Safety-Analysis-and-Meet-New-Federal-Requirements.pdf

Das, S., Le, M., Pratt, M. P., & Morgan, C. (2020). Safety effectiveness of truck lane restrictions: a case study on Texas urban corridors. International Journal of Urban Sciences, 24(1), pp 35--49. https://doi.org/10.1080/12265934.2019.1585929

Jalayer, M., O’Connell, M., Zhou, H., Szary, P., Das, S., & Board, T. R. (2019). Application of Unmanned Aerial Vehicle to Inspect and Inventory Interchange Assets to Mitigate Wrong-Way Entries (p. 16p). Retrieved from https://trid.trb.org/view/1573022

Sun, M., Sun, X., Shan, D., Armstrong, D., Das, S., & Board, T. R. (2019). Louisiana Pedestrian Crash Analysis with Multinomial Logit Model and Bayesian Network (p. 9p). Retrieved from https://trid.trb.org/view/1573239

Das, S., Tsapakis, I., & Datta, S. (2019). Safety Performance Functions of Low-Volume Roadways. Transportation Research Record: Journal of the Transportation Research Board, 2673(12), pp 798--810. https://doi.org/10.1177/0361198119853559

Das, S., Wang, R., Safety Through Disruption University Transportation Center (Safe-D), Office of the Assistant Secretary for Research, & Technology. (2019). Exploring Crowdsourced Monitoring Data for Safety - Travel Patterns using GPS Waypoint Data (TTI-Student-05) [supporting dataset]. Virginia Tech Transportation Institute Dataverse. Retrieved from https://rosap.ntl.bts.gov/view/dot/50717

Das, S. (2019). \#TRBAM: Social Media Interactions from Transportation’s Largest Conference. TR News, (324), pp 18--23. Retrieved from http://www.trb.org/Main/Blurbs/180592.aspx

Tsapakis, I., Sharma, S., Dadashova, B., Geedipally, S., Sanchez, A., Le, M., … Administration, F. H. (2019). Evaluation of Highway Safety Improvement Projects and Countermeasures: Technical Report (p. 244p). Retrieved from http://tti.tamu.edu/documents/0-6961-R1.pdf

Sun, X., & Das, S. (2019). Estimating Annual Average Daily Traffic for Low-Volume Roadways: A Case Study in Louisiana (p. pp 190--201). Transportation Research Board. Retrieved from http://www.trb.org/Publications/Blurbs/179567.aspx

Das, S., Minjares-Kyle, L., Wu, L., & Henk, R. H. (2019). Understanding Crash Potential Associated with Teen Driving: Survey Analysis Using Multivariate Graphical Method. Journal of Safety Research, 70, pp 213--222. https://doi.org/10.1016/j.jsr.2019.07.009

Das, S., Bibeka, A., Sun, X., Zhou, Hongmin “Tracy,” & Jalayer, M. (2019). Elderly Pedestrian Fatal Crash-Related Contributing Factors: Applying Empirical Bayes Geometric Mean Method. Transportation Research Record: Journal of the Transportation Research Board, 2673(8), pp 254--263. https://doi.org/10.1177/0361198119841570

Das, S., Dutta, A., Lindheimer, T., Jalayer, M., & Elgart, Z. (2019). YouTube as a Source of Information in Understanding Autonomous Vehicle Consumers: Natural Language Processing Study. Transportation Research Record: Journal of the Transportation Research Board, 2673(8), pp 242--253. https://doi.org/10.1177/0361198119842110

Jalayer, M., O’Connell, M., Zhou, H., Szary, P., & Das, S. (2019). Application of Unmanned Aerial Vehicles to Inspect and Inventory Interchange Assets to Mitigate Wrong-Way Entries. ITE Journal, 89(7), pp 36--42. Retrieved from https://trid.trb.org/view/1659126

Das, S., Dutta, A., Kong, X., & Sun, X. (2019). Hit and Run Crashes: Knowledge Extraction from Bicycle Involved Crashes using First and Frugal Tree. International Journal of Transportation Science and Technology, 8(2), pp 146--160. https://doi.org/10.1016/j.ijtst.2018.11.001

Das, S., Jha, K., Fitzpatrick, K., Brewer, M., & Shimu, T. H. (2019). Pattern Identification from Older Bicyclist Fatal Crashes. Transportation Research Record: Journal of the Transportation Research Board, 2673(6), pp 638--649. https://doi.org/10.1177/0361198119841863

Trueblood, A. B., Pant, A., Kim, J., Kum, H.-C., Perez, M., Das, S., & Shipp, E. M. (2019). A Semi-Automated Tool for Identifying Agricultural Roadway Crashes in Crash Narratives. Traffic Injury Prevention, 20(4), pp 413--418. https://doi.org/10.1080/15389588.2019.1599873

Das, S., Geedipally, S. R., Dixon, K., Sun, X., & Ma, C. (2019). Measuring the Effectiveness of Vehicle Inspection Regulations in Different States of the U.S. Transportation Research Record: Journal of the Transportation Research Board, 2673(5), pp 208--219. https://doi.org/10.1177/0361198119841563

Fitzpatrick, K., McCourt, R., & Das, S. (2019). Current Attitudes among Transportation Professionals with Respect to the Setting of Posted Speed Limits. Transportation Research Record: Journal of the Transportation Research Board, 2673(4), pp 778--788. https://doi.org/10.1177/0361198119838504

Das, S., Dutta, A., Medina, G., Minjares-Kyle, L., & Elgart, Z. (2019). Extracting patterns from Twitter to promote biking. IATSS Research, 43(1), pp 51--59. https://doi.org/10.1016/j.iatssr.2018.09.002

McCourt, R., Fitzpatrick, K., Koonce, P., & Das, S. (2019). Speed Limits: Leading to Change. ITE Journal, 89(4), pp 38--43. Retrieved from https://trid.trb.org/view/1598110

Turner, S., Benz, R., Hudson, J., Griffin, G., Lasley, P., Dadashova, B., … Administration, F. H. (2019). Improving the Amount and Availability of Pedestrian and Bicyclist Count Data in Texas (p. 100p). Retrieved from http://tti.tamu.edu/documents/0-6927-R1.pdf

Das, S., Dutta, A., Avelar, R., Dixon, K. K., Sun, X., & Jalayer, M. (2019). Supervised association rules mining on pedestrian crashes in urban areas: identifying patterns for appropriate countermeasures. International Journal of Urban Sciences, 23(1), pp 30--48. https://doi.org/10.1080/12265934.2018.1431146

Fitzpatrick, K., Das, S., Texas A\&M Transportation Institute, Safety through Disruption University Transportation Center (Safe-D), Office of the Assistant Secretary for Research, & Technology. (2019). Vehicle Operating Speed on Urban Arterial Roadways (p. 31p). Retrieved from http://hdl.handle.net/10919/89097

Das, S., Minjares-Kyle, L., Dixon, K., Palanisamy, A., & Dutta, A. (2018). \#TRBAM: Exploring Knowledge Management, Research Trends, and Networks by Social Media Mining (p. 20p). Retrieved from https://trid.trb.org/view/1495087

Minjares-Kyle, L., Das, S., Medina, G., & Henk, R. H. (2018). Knowledge about Crash Risk Factors and Self-Reported Driving Behavior: Exploratory Analysis on Multi-State Teen Driver Survey (p. 19p). Retrieved from https://trid.trb.org/view/1495088

Bibeka, A., Das, S., Martin, M. W., Jalayer, M., & Munira, S. (2018). Macro-Level Analysis of Association between Non-motorized Trips, Socio-Economic Characteristics, and Crime (p. 16p). Retrieved from https://trid.trb.org/view/1494623

Rahman, M., Sun, X., & Das, S. (2018). Safety Performance Evaluation of Urban Undivided Four-Lane to Five-Lane Conversion in Louisiana (p. 17p). Retrieved from https://trid.trb.org/view/1497216

Das, S., Le, M., Pratt, M. P., & Morgan, C. (2018). Safety Performance of Truck Lane Restrictions in Texas: Empirical Bayes Observational Before–After Analysis (p. 17p). Retrieved from https://trid.trb.org/view/1495903

Das, S., Medina, G., Minjares-Kyle, L., & Elgart, Z. (2018). Social Media Hashtags Associated with Bike Commuting: Applying Natural Language Processing Tools (p. 18p). Retrieved from https://trid.trb.org/view/1495848

Das, S., Mudgal, A., Dutta, A., & Geedipally, S. R. (2018). Vehicle Consumer Complaint Reports Involving Severe Incidents: Mining Large Contingency Tables. Transportation Research Record: Journal of the Transportation Research Board, 2672(32), pp 72--82. https://doi.org/10.1177/0361198118788464

Das, S., Dutta, A., Dixon, K., Minjares-Kyle, L., & Gillette, G. (2018). Using Deep Learning in Severity Analysis of At-Fault Motorcycle Rider Crashes. Transportation Research Record: Journal of the Transportation Research Board, 2672(34), pp 122--134. https://doi.org/10.1177/0361198118797212

Dadashova, B., Griffin, G., Das, S., Turner, S., Graham, M., Texas A\&M Transportation Institute, … Administration, F. H. (2018). Guide for Seasonal Adjustment and Crowdsourced Data Scaling (p. 78p). Retrieved from https://static.tti.tamu.edu/tti.tamu.edu/documents/0-6927-P6.pdf

Pratt, M. P., Geedipally, S. R., Wilson, B., Das, S., Brewer, M., Lord, D., … Administration, F. H. (2018). Pavement Safety-Based Guidelines for Horizontal Curve Safety (p. 176p). Retrieved from https://static.tti.tamu.edu/tti.tamu.edu/documents/0-6932-R1.pdf

Fitzpatrick, K., Das, S., Texas A\&M Transportation Institute, Safety through Disruption University Transportation Center (Safe-D), Office of the Assistant Secretary for Research, & Technology. (2018). Vehicle Operating Speed on Urban Arterial Roadways (TTI-01-04) [supporting dataset]. Virginia Tech Transportation Institute Dataverse. Retrieved from http://hdl.handle.net/10919/89097

Fitzpatrick, K., Das, S., Texas A\&M Transportation Institute, Safety through Disruption University Transportation Center (Safe-D), Office of the Assistant Secretary for Research, & Technology. (2018). Vehicle Operating Speed on Urban Arterial Roadways (TTI-01-04) [supporting dataset]. Virginia Tech Transportation Institute Dataverse. Retrieved from http://hdl.handle.net/10919/89097

Das, S., Brimley, B. K., Lindheimer, T. E., & Zupancich, M. (2018). Association of reduced visibility with crash outcomes. IATSS Research, 42(3), pp 143--151. https://doi.org/10.1016/j.iatssr.2017.10.003

Das, S., Sun, X., Dixon, K., & Rahman, M. (2018). Safety effectiveness of roadway conversion with a two way left turn lane. Journal of Traffic and Transportation Engineering (English Edition), 5(4), pp 309--317. https://doi.org/10.1016/j.jtte.2017.11.002

Turner, S., Sener, I., Martin, M., White, L. D., Das, S., Hampshire, R., … Associates, Inc. (2018). Guide for Scalable Risk Assessment Methods for Pedestrians and Bicyclists (p. 122p). Retrieved from https://safety.fhwa.dot.gov/ped_bike/tools_solve/fhwasa18032/fhwasa18032.pdf

Das, S., Dutta, A., Jalayer, M., Bibeka, A., & Wu, L. (2018). Factors Influencing the Patterns of Wrong-Way Driving Crashes on Freeway Exit Ramps and Median Crossovers: Exploration using ‘Eclat’ Association Rules to Promote Safety. International Journal of Transportation Science and Technology, 7(2), pp 114--123. https://doi.org/10.1016/j.ijtst.2018.02.001

Das, S., Avelar, R., Dixon, K. K., & Sun, X. (2018). Investigation on the wrong way driving crash patterns using multiple correspondence analysis. Accident Analysis \& Prevention, 111, pp 43--55. https://doi.org/10.1016/j.aap.2017.11.016

Das, S., Minjares-Kyle, L., Avelar, R. E., Dixon, K. K., Bommanayakanahalli, B., & Board, T. R. (2017). Improper Passing Related Crashes on Rural Roadways: Using Association Rules Negative Binomial Miner (p. 17p). Retrieved from https://trid.trb.org/view/1439264

Das, S., Avelar, R. E., Dixon, K. K., Sun, X., & Board, T. R. (2017). Pedestrian Crash Analysis Using Association Rules Mining (p. 19p). Retrieved from https://trid.trb.org/view/1437503

Das, S., Brimley, B. K., Lindheimer, T., Zupancich, M., & Board, T. R. (2017). Safety Impacts of Reduced Visibility in Inclement Weather (p. 17p). Retrieved from https://trid.trb.org/view/1438547

Das, S., Sun, X., Dutta, A., Zupancich, M., & Board, T. R. (2017). Twitter in Circulating Transportation Information: A Case Study on Two Cities (p. 16p). Retrieved from https://trid.trb.org/view/1438524

Das, S., Dixon, K. K., Avelar, R. E., Fitzpatrick, K., & Board, T. R. (2017). Using Machine Learning Techniques to Estimate Non-motorized Trips for Rural Roadways (p. 16p). Retrieved from https://trid.trb.org/view/1438537

Das, S., Dixon, K. K., Sun, X., Dutta, A., & Zupancich, M. (2017). Trends in Transportation Research: Exploring Content Analysis in Topics. Transportation Research Record: Journal of the Transportation Research Board, (2614), pp 27--38. https://doi.org/10.3141/2614-04

Dixon, K. K., Fitzpatrick, K., Avelar, R., Das, S., Texas A\&M Transportation Institute, Transportation, T. D. of, & Administration, F. H. (2017). Analysis of the Shoulder Widening Need on the State Highway System (p. 168p). Retrieved from https://static.tti.tamu.edu/tti.tamu.edu/documents/0-6840-1.pdf

Das, S., Brimley, B. K., Lindheimer, T., Pant, A., Texas A\&M Transportation Institute, Center for Advancing Transportation Leadership, … Technology. (2017). Safety Impacts of Reduced Visibility in Inclement Weather (p. 61p). Retrieved from http://www.atlas-center.org/wp-content/uploads/2017/04/SafetyImpacts_VisibilityWeather_FinalReport.pdf

Turner, S., Sener, I., Martin, M., Das, S., Shipp, E., Hampshire, R., … Administration, F. H. (2017). Synthesis of Methods for Estimating Pedestrian and Bicyclist Exposure to Risk at Areawide Levels and on Specific Transportation Facilities (p. 93p). Retrieved from https://safety.fhwa.dot.gov/ped_bike/tools_solve/fhwasa17041/fhwasa17014.pdf

Sun, X., Das, S., Broussard, N., Road, S. N., & Transport Research Institute (VTI). (2016). Developing crash models with supporting vector machine for urban transportation planning (p. 12p). Retrieved from http://vti.diva-portal.org/smash/get/diva2:926110/FULLTEXT01.pdf

Das, S., Sun, X., LeBoeuf, C., & Board, T. R. (2016). Estimating Traffic Volume of Nonstate Roadways with Support Vector Regression (p. 18p). Retrieved from https://trid.trb.org/view/1393168

Das, S., Sun, X., & Dutta, A. (2016). Text Mining and Topic Modeling of Compendiums of Papers from Transportation Research Board Annual Meetings. Transportation Research Record: Journal of the Transportation Research Board, (2552), pp 48--56. https://doi.org/10.3141/2552-07

Fitzpatrick, K., Das, S., Contreras, A., Texas A\&M Transportation Institute, Center for Advancing Transportation Leadership, Safety (ATLAS Center), … Technology. (2016). Is Age a Factor in Crashes at Channelized Right-Turn Lanes? An Exploration of Potential Relationships (p. 46p). Retrieved from http://www.atlas-center.org/wp-content/uploads/2014/10/ATLAS-2016-14-Final-Research-Report-Fitzpatrick.pdf

Das, S., & Sun, X. (2016). Association Knowledge for Fatal Run-off-road Crashes by Multiple Correspondence Analysis. IATSS Research, 39(2), pp 146--155. https://doi.org/10.1016/j.iatssr.2015.07.001

Das, S., Sun, X., & Board, T. R. (2015). Zero-Inflated Models for Different Severity Types in Rural Two-Lane Crashes (p. 14p). Retrieved from https://trid.trb.org/view/1337677

Das, S., & Sun, X. (2015). Factor Association with Multiple Correspondence Analysis in Vehicle–Pedestrian Crashes. Transportation Research Record: Journal of the Transportation Research Board, (2519), pp 95--103. https://doi.org/10.3141/2519-11

Sun, X., Das, S., University of Louisiana, Lafayette, Transportation, L. D. of, Development, & Administration, F. H. (2015). Developing a Method for Estimating AADT on all Louisiana Roads (p. 98p). Retrieved from http://www.ltrc.lsu.edu/pdf/2015/FR_548.pdf

Das, S., Sun, X., Wang, F., & LeBoeuf, C. (2015). Estimating Likelihood of Future Crashes for Crash-prone Drivers. Journal of Traffic and Transportation Engineering (English Edition), 2(3), pp 145--157. https://doi.org/10.1016/j.jtte.2015.03.003

Das, S., Sun, X., & Board, T. R. (2014). Exploring Clusters of Contributing Factors for Single-Vehicle Fatal Crashes Through Multiple Correspondence Analysis (p. 17p). Retrieved from https://trid.trb.org/view/1288303

Das, S., Sun, X., & Board, T. R. (2014). Investigating the Pattern of Traffic Crashes Under Rainy Weather by Association Rules in Data Mining (p. 19p). Retrieved from https://trid.trb.org/view/1287867

Sun, X., Das, S., Zhang, Z., Wang, F., & LeBoeuf, C. (2014). Investigating Safety Impact of Edgelines on Narrow, Rural Two-Lane Highways by Empirical Bayes Method. Transportation Research Record: Journal of the Transportation Research Board, (2433), pp 121--128. https://doi.org/10.3141/2433-14

Sun, X., Das, S., University of Louisiana, Lafayette, Transportation, L. D. of, Development, & Administration, F. H. (2014). A Comprehensive Study on Pavement Edge Line Implementation (p. 71p). Retrieved from http://www.ltrc.lsu.edu/pdf/2014/FR_508.pdf

Sun, X., Das, S., Rasel, S. K., Wang, F., & Board, T. R. (2013). Analyzing Crash-Prone Drivers in Multiple Crashes for Better Safety Educational and Enforcement Strategies (p. 13p). Retrieved from https://trid.trb.org/view/1242293

Das, S., Sun, X., Rasel, S., Wang, F., & Board, T. R. (2013). Investigating Safety Impact of Raised Pavement Markers on Freeways in Louisiana (p. 12p). Retrieved from https://trid.trb.org/view/1242721

Sun, X., Das, S., Sk, R., Fan, W., Road, S. N., & Transport Research Institute (VTI). (2013). Predicting drivers’ crash risk based on their crash history (p. 14). Retrieved from http://vti.diva-portal.org/smash/get/diva2:759067/FULLTEXT01.pdf

Sun, X., Das, S., University of Louisiana, Lafayette, Transportation, L. D. of, Development, Louisiana State University, Baton Rouge, & Administration, F. H. (2013). Developing Louisiana Crash Reduction Factors (p. 72p). Retrieved from http://www.ltrc.lsu.edu/pdf/2013/FR_506.pdf

Sun, X., Das, S., Fruge, N., Bertinot, R. L., & Magri, D. (2013). Four-Lane to Five-Lane Urban Roadway Conversions for Safety. Journal of Transportation Safety \& Security, 5(2), pp 106--117. https://doi.org/10.1080/19439962.2012.711439

Sun, X., Das, S., Fruge, N. P., Bertinot, R. J., Magri, D., & Board, T. R. (2012). Crash Modification Factor for an Inexpensive yet Very Cost Effective Safety Improvement: Converting Undivided Four-Lane Urban Roadways to Five-Lane Roadways (p. 17p). Retrieved from https://trid.trb.org/view/1128928

Sun, X., Das, S., University of Louisiana, Lafayette, Transportation, L. D. of, Development, & Administration, F. H. (2012). Safety Improvement from Edge Lines on Rural Two-Lane Highways (p. 84p). Retrieved from http://www.ltrc.lsu.edu/pdf/2012/fr_487.pdf