Wen Cheng

• B.S. in Civil Engineering, Tongji University, 2000
• M.S. in Roadway & Traffic Engineering, Tongji University, 2002
• M.S. in Civil Engineering, University of Arizona, 2005
• Ph.D. in Civil Engineering, Arizona State University, 2006

Professional Licenses

• T.E., California Professional Traffic Engineer, License No. 2536
• P.E., Professional Engineer, California No. C72602
• PTOE, Professional Traffic Operations Engineer, Certificate No. 2432

1. Transportation Systems Design & Operation
2. Design of Transportation Facilities 
3. Traffic Safety Analysis
4. Advanced Computer Programming in Civil Engineering
5. Multimodal Traffic Analysis
6. Transportation Engineering
7. Traffic Signal Design
8. Highway Engineering
9. Application of Machine Learning to Civil Engineering
10. Infrastructure Economics 
11. Special Studies
12. Senior Projects
13. AutoCAD
14. Application of Computer Vision to Transportation and Civil Engineeing

(* indicate the corresponding author, ^ indicate student authors)

1. Y. Li, G. Gill^, W. Cheng*, M. Singh^, Y. Zhang, J. Kwong (2023). “Sensitivity Analysis of Bayesian Nonparametric Spatial Crash Frequency Models for Bicyclists”. Journal of Communications in Statistics - Simulation and Computation (Accepted for publication).
2. Gill, G^., W. Cheng*, M. Singh^, Y. Li (2022). “Comparative Evaluation of Alternative Bayesian Semiparametric Spatial Crash Frequency Models”. Journal of Traffic and Transportation Engineering (Accepted for publication).
3. Truong, L.^, E. Clay^, O. Mora, W. Cheng*, M. Singh^, X.Jia (2022). “Rotated Mask RCNN Detection for Parking Space Management System”, Journal of Transportation Research Record 2677 (1), 1564-1581 (DOI: 10.1177/03611981221105066 )
4. Singh, M.^, Y. Zhang, W. Cheng*, Y. Li, and E. Clay^ (2022). Exploration of Transit Station-Oriented Active Transportation Safety Using Bivariate Spatial Models with Different Covariate Inputs, Journal of safety research 83, 152-162.
5. Singh, M.^, W. Cheng*, R. Gopalakrishnan^, Y. Li, M. Cao^ (2021). Exploration of the Contributing Factors to the Walking and Biking Travel Frequency using Multi-Level Joint Models with Endogeneity. Journal of Traffic and Transportation Engineering, http://kns.cnki.net/kcms/detail/61.1494.U.20211027.2059.002.html.
6. Zhang, Y., G. Gill^, W. Cheng*, P. Reina, M. Singh^. (2021) “Exploring Influential Factors and Endogeneity of Traffic Flow of Different Lanes on Urban Freeways using Bayesian Multivariate Spatial Models”, Journal of Traffic and Transportation Engineering (http://kns.cnki.net/kcms/detail/61.1494.U.20211003.0950.002.html )
7. Cheng, W.*, M. Singh^, E. Clay^, J. Kwong, M. Cao,^ Y. Li, A. Truong (2021). “Exploring Temporal Interactions of Crash Counts in California Using Distinct Log-linear Contingency Table Models”, International Journal of Injury Control and Safety Promotion (DOI: 10.1080/17457300.2021.1928231 Link: https://doi.org/10.1080/17457300.2021.1928231 ).
8. Truong, L.^, O. Mora, W. Cheng*, H. Tang^ and M. Singh^ (2021). “Deep Learning to Detect Road Distress from Unmanned Aerial System Imagery”, Journal of Transportation Research Record (Link: https://doi.org/10.1177/03611981211004973 )
9. M. Singh^, W. Cheng*, D. Samuelson, E. Clay^, H. Tang^, Li, Y. (2021). “Exploring Influence of Crash Type on Injury Severity in Crashes at Intersection”, Journal of Advances in Transportation Studies Vol. 54, p61-74, DOI: 10.53136/97912599405445.
10. M. Singh^, W. Cheng*, D. Samuelson, E. Clay^, M. Cao^ (2021). “Development of Pedestrian-and Vehicle-Related Safety Performance Functions Using Bayesian Bivariate Hierarchical Models with Mode-Specific Covariates”, Journal of Safety Research 78, 180-188.
11. Cheng, W.*, G. Gill^, F. Wen and J. Zhou (2020). “Bayesian Bivariate Semiparametric Spatial Models for Ozone and PM2.5 Emissions”, Journal of Environmental Modelling and Assessment 26 (2), 237-249, (DOI: 10.1007/s10666-020-09732-8. Link: https://rdcu.be/b7i5L)
12. Cheng, W.*, G. Gill^, Y. Zhang, T. Vo, F. Wen, Y. Li (2019). “Exploring the Modeling and Site-Ranking Performance of Bayesian Spatiotemporal Crash Frequency Models with Mixture Components”. Journal of Accident Analysis and Prevention, 135, 135037.
13. Cheng, W.*, G. Gill^, J. Zhou,  J. Ensch, J. Kwong and X. Jia, (2019) “Alternative Multivariate Multimodal Crash Frequency Models”, Journal of Transportation Safety and Security, 1-25.
14. Cheng, W.*, G. Gill^, M. Dasu, and X. Jia (2018). “An Empirical Evaluation of Multivariate Spatial Crash Prediction Models”, Journal of Accident Analysis and Prevention, 119, 290-306.
15. Cheng, W.*, G. Gill^, T. Sakrani^, D. Ralls,^ X. Jia (2018). “Modeling the endogeneity of lane-mean speeds and lane-speed deviations using a Bayesian structural equations approach with spatial correlation”. Journal of Transportation Research Part A: Policy and Practice, 116, 220-231, (https://doi.org/10.1016/j.tra.2018.06.014)
16. Cheng, W.*, G. Gill^, T. Vo.^, J. Zhou, and T. Sakrani^ (2018). “Use of Multivariate Dirichlet Process Mixture Spatial Model to Estimate Active Transportation-related Crash Counts”, Journal of Transportation Research Record, 0361198118782797.
17. Gill, G.^, W. Cheng*, J. Zhou, T. Vo^, and X. Jia (2018). “Comprehensive Assessment of Temporal Treatments in Crash Prediction Models”, Journal of Transportation Research Record, 0361198118782763.
18. Xie, M., W. Cheng*, G. Gill^, J. Zhou, X. Jia, S. Choi (2018). “Predicting Likelihood of Hit-and-run Crashes Using Real-time Loop Detector Data and Hierarchical Bayesian Binary Logit Model with Random Effects”, Journal of Traffic Injury and Prevention. Vol. 19, Iss.2,  (10.1080/15389588.2017.1371302)
19. Cheng, W.*, G. Gill^, J. Ensch, J. Kwong, and X. Jia (2018). “Multimodal Crash Frequency Modeling: Multivariate Space-Time Models with Alternate Spatiotemporal Interactions”, Accident Analysis and Prevention, 113, pp. 159-170.
20. Cheng, W.*, Gill, G.^, Y. Zhang, Z. Cao (2018). “Bayesian Space-Time Crash Frequency Models with Mixture Components for Spatiotemporal Interaction”. Accident Analysis & Prevention, 112, pp. 84-93. (https://doi.org/10.1016/j.aap.2017.12.020)
21. Lee, A.^, W. Lin, G. Gill^, and W. Cheng* (2018). “An Enhanced Empirical Bayesian Method for Identifying Road Hot Spots and Predicting Number of Crashes”. Journal of Transportation Safety and Security (Accepted for publication, https://doi.org/10.1080/19439962.2018.1450314)
22. Cheng, W*., G. Gill^, S. Choi, X. Jia, J. Zhou, M. Xie (2018). “Comparative Evaluation of Temporal Correlation Treatment in Crash Frequency Modeling”, Journal of Transportmetrica A Transport Science, Volume 14, Issue 7, 615-633.
23. Cheng, W.*, Gill, G.^ S., Dasu, R., Xie, M., Jia, X., & Zhou, J. (2017). Comparison of Multivariate Poisson lognormal spatial and temporal crash models to identify hot spots of intersections based on crash types. Accident Analysis & Prevention, 99, pp. 330-341.
24. Cheng, W.*, X. Jiang, W. Lin, X. Wu, X. Jia, J. Zhou.(2017) “Ranking Cities for Safety Investigation by Potential for Safety Improvement”. Journal of Transportation Safety and Security, (DOI: 10.1080/19439962.2017.1279250).
25. Gill, G.^, W. Cheng*, M. Xie, T. Vo^, X. Jia, J. Zhou. (2017) “Evaluating the Influence of Neighboring Structures on Spatial Crash Frequency Modeling and Site Ranking Performance”, Journal of Transportation Research Record 2659, pp. 117-126. (DOI: 10.3141/2659-13).
26. Cheng, W*., G. Gill^, L. Loera^, X. Wang, J. Wang. (2017) “Evaluation of the Impact of Traffic Volume on Site Ranking”. Journal of Transportation Safety and Security, (DOI: 10.1080/19439962.2017.1321074).
27. Gill, G^. W. Cheng*, J. Zhou, & V. Shin (2017), “Comparative Analysis of Cost-weighted Site Ranking Using Alternate Distance-based Neighboring Structures for Spatial Crash Frequency Modeling”, Journal of Transportation Safety and Security . (DOI: 10.1080/19439962.2017.1354239)
28. Cheng, W.*, G. Gill^, T. Sakrani^, M. Dasu, J. Zhou (2017). “Predicting Motorcycle Crash Injury Severity using Weather Data and Alternative Bayesian Multivariate Crash Frequency Models”. Journal of Accident Analysis and Prevention, 108, pp. 172-180.
29. Gill, G^. and W. Cheng* (2017). “Assessment of Alternative Bayesian Hierarchical Models for Estimating Gas Emissions”, Journal of Global Environment, Health and Safety, iMedPub Journals (Vol. 1, No. 2:8)

1. PI: California Statewide Traffic Safety Ranking via Empirical Bayes Method, USDOT/National Highway Traffic Safety Administration, (2013~present, $2,501,634.00). Goal: Enhance accuracy of safety performance rankings of counties and incorporated cities in CA.
2. PI (CPP Portion): National University Tranportation Center: Center for Understanding Future Travel Behavior and Demand, USDOT, (2023-2028, $2,500,000.00). Goal: Improving Mobility for People and Goods in the US.
3. PI: Administration of the Dwight David Eisenhower Transportation Fellowship Program (DDETFP) Local Competition, FHWA (12/2022-8/2023, $50,000.00) Goal: Attract the nation's brightest minds to the field of transportation through the local administration of DDETFP program.
4. Co-PI: Understanding Mobility-Related Challenges for AAPI Older Adults, CSUTC SB1 Program (1/2023-12/2023, $75,000.00). Goal: Improve the level of mobility for AAPI older adults.
5. PI: Administration of the Dwight David Eisenhower Transportation Fellowship Program (DDETFP) Local Competition, FHWA (12/2021-8/2022, $50,000.00) Goal: Attract the nation's brightest minds to the field of transportation through the local administration of DDETFP program.
6. Co-PI: Enhancing the Mobility of Senior Adults, CSUTC SB1 Program (10/2021-8/2022, $75,000.00). Goal: Improve the level of mobility for older adults for the preparation of the aging Californians.
7. PI: Administration of the Dwight David Eisenhower Transportation Fellowship Program (DDETFP) Local Competition, FHWA (11/2020-8/2021, $50,000.00) Goal: Attract the nation's brightest minds to the field of transportation through the local administration of DDETFP program.
8. PI: Promotion of Deep Learning and Artificial Intelligence in Campus Living Lab and Transportation Laboratory of Civil Engineering, CPP SPICE (7/2020-6/2021, $12,600.00). Goal: Enhance access to multi-user StreetLight Data which can be fed into deep learning and artificial intelligence for campus safety improvement.
9. PI: Comprehensive Evaluation of Crowdsourcing Non-motorist Count Data, CSUTC SB1 Program (5/2020-4/2021, $75,000.00). Goal: Improve data collection accuracy for Non-motorist volume.
10. PI: Development of Active Transportation Safety Performance Functions in California, Caltrans (4/2018~11/2020, $175,000.00). Goal: Enhance active transportation safety in California.
11. Co-PI: Enhancement of Multimodal Traffic Safety in High Quality Transit Areas, CSUTC SB1 Program (5/2019-4/2020, $75,000.00). Goal: Improve multimodal transportation usage while enhancing safety of such modes.
12. Co-PI: Promotion of Active Transportation in High Quality Transit Areas, CPP SIRG Program (6/2019-5/2020, $16,200.00). Goal: Improve active transportation mode usage while enhancing safety of such mode.
13. Co-PI: 2018 National Summer Transportation Institute (NSTI) and National Flight Academy (NFA) initiative (6/2018~7/2018, $69277). Goal: Enhance the interests among current high school students in pursuing transportation careers in the future.
14. Co-PI: CPP RSCA from Chancellor's Office funds A Pilot Study: Cal Poly Pomona Campus Transportation Plan (1/2018~11/2018, $5000). Goal: Investigate and evaluate various traffic circulation plan on campus.
15. PI: sub-award to UC Davis- Santa Ana Mountains to eastern Peninsular Range Conservation Connectivity Infrastructure Planning Project for Interstate 15 and Closely Associated Roadways (3/2018~6/2019, $40,000.00). Goal: Identify best engineering alternatives for wild life connectivity across Interstate 15 in California.
16. PI: STEM Online/Hybrid Course Design Proposal, PPOHA/MENTORES project grant, (6/2017~9/2017, $4,500.00). Goal: Develop online/hybrid course for traffic and highway safety.
17. Co-PI: Advanced Research on the Built Environment and Collisions, Southern California Association of Governments (6/2017-10/2017, $50,000.00). Goal: Identify the collision hotspots by different transportation modes and the correlation of surrounding built environment with the different types of the hot spots in southern California
18. PI: Investigation of Multimodal Crashes using Full Bayesian Multivariate Spatial-Temporal Models, UCCONNECT and Caltrans (6/2016~present, $75,000.00). Goal: Enhance students’ passion in doing transportation research.
19. PI: UCCONNECT Summer Research Programs, UCCONNECT (6/2016~9/2016,$105,000.00). Goal: Enhance students’ passion in doing transportation research.
20. PI: UCCONNECT Technology Transfer, Educational and Student Research Support Programs, UCCONNECT (2014~present, $150,000.00). Goal: Assist students in pursuing transportation profession and/or advanced degrees.
21. Co-PI: Exploring the Relationship between Traffic Congestion and Traffic Safety, UCCONNECT (2014~2016, $20,000.00). Goal: Quantify the relationship between traffic crash severities and traffic flow characteristics.
22. PI: Identification of systematic method to enhance pedestrian safety, City of Glendale, CA (2011-2012, $25,000.00). Goal: Enhance pedestrian traffic safety in Glendale, CA.
23. PI: Enhancement of Student Learning, Roadway Safety, Traffic and Facility Planning Efficiency through Campus-Wide Multi-Modal Dynamic Traffic Simulation, CPP Kellogg Legacy Project Endowment (2014~present, $70,000.00). Goal: Enhance student learning and campus safety through the development of campus-wide traffic simulation.
24. PI: Campus Circulation Safety Evaluation and Enhancement, The CSU Campus as A Living Lab Grant Program (2013-2014, $17,000.00). Goal: Enhance and evaluate campus circulation safety.
25. PI: Incorporation of Greenhouse Gas Emission Reduction, Safety and Congestion Relief Considerations into Transportation Planning, First CPP SIRG Program (2012-2013, $13,000.00). Goal: Synchronize safety, congestion relief and gas emission reduction.