Professor
Supervisor of Master's Candidates
Supervisor of Doctorate Candidates
He, Qing
Professor and Vice Department Chair
Department of Road and Railway Engineering,
School of Civil Engineering,
Southwest Jiaotong University, Chengdu, China
E-mail address: qhe@swjtu.edu.cn
Personal Website: https://faculty.swjtu.edu.cn/heqing/en/index.htm
Google Scholar: https://scholar.google.com/citations?user=SRLNuw8AAAAJ&hl=en
ORCID: https://orcid.org/0000-0003-2596-4984
Scopus Author ID: https://www.scopus.com/authid/detail.uri?authorId=36550317100
I. Professional Interests
Road and Rail Location Design and BIM; Data-Driven Intelligent Maintenance of Road and Rail Infrastructure; Transportation Planning and Management
II.Intelligent Transportation Infrastructure Introduction
Intelligent Transportation Infrastructure (ITI) is an open access, free of charge, online only journal publishing cutting-edge and innovative research to act as a bridge between advances being made in artificial intelligence and transportation infrastructure engineering.
ITI is mainly oriented to all aspects of transportation infrastructures focusing on the latest research achievements in the integrity, durability, and robustness of transportation infrastructure. It aims to promote the combination and intersection between infrastructure engineering technology and information intelligence technology and provide an interdisciplinary platform for relevant scholars to disseminate innovative research and engineering practice.
ITI covers the planning, design, construction, operation, inspection, monitoring, evaluation, maintenance, repair, and renewal of transportation infrastructure systems. The topics include but are not limited to the following directions:
· Green design and construction of transportation infrastructure
· Smart construction of transportation infrastructure.
· Inspection, online monitoring, and non-destructive assessment of transportation infrastructure.
· Protection and repair of transportation infrastructure.
· Resilience studies of transportation infrastructure systems (e.g. adaptation to disasters, climate change, and extreme weather).
· Operation and maintenance decision support and management (such as big data modeling and analysis, life cycle cost analysis, risk assessment, life cycle assessment, representation/modeling of interdependence, maintenance decision optimization), etc.
· Transportation engineering geology and ecological geology.
Official home page: https://academic.oup.com/iti
Submission homepage: https://mc.manuscriptcentral.com/iti
III. Education
Ph.D. Systems & Industrial Engineering, minor Civil Engineering
The University of Arizona, Tucson, AZ, USA
M.S. Industrial Engineering, The University of Arizona, Tucson, AZ, USA
M.S. Electrical Engineering, Southwest Jiaotong University, Chengdu, China
B.S. Electrical Engineering, Southwest Jiaotong University, Chengdu, China
IV. Employment
Professor and Vice Department Chair, Department of Road and Railway Engineering, School of Civil Engineering, Southwest Jiaotong University, Chengdu, China
Morton C. Frank Associate Professor, Department of Industrial and Systems Engineering and Department of Civil, Structural and Environmental Engineering, University at Buffalo, The State University of New York, Buffalo, NY
Stephen Still Assistant Professor, Department of Industrial and Systems Engineering and Department of Civil, Structural and Environmental Engineering, University at Buffalo, The State University of New York, Buffalo, NY
Postdoctoral Researcher, Business Analytics and Mathematical Sciences, IBM T J Watson Research Center, Yorktown Heights, NY
Graduate Student Assistant, Safe Transportation Research & Education Center, The University of California, Berkeley, CA
Graduate Student Assistant, Department of Systems & Industrial Engineering, The University of Arizona, Tucson, AZ.
V. Publications
(*: Qing He’s graduate students; **: Qing He’s undergraduate students; #: Corresponding author)
A. Peer Reviewed Book Chapters
BC1. He, Q*. Y. Kamarianakis, K. Jintanakul and L. Wynter, “Incident Duration Prediction with Hybrid Tree-based Quantile Regression”, S.V. Ukkusuri and K. Ozbay (eds.), Advances in Dynamic Network Modeling in Complex Transportation Systems, Complex Networks and Dynamic Systems, DOI 10.1007/978-1-4614-6243-9 12, Springer Science+Business Media, New York 2013.
BC2. Zhang, Z.# and Q. He*, “Social Media in Transportation Research and Promising Applications”, S.V. Ukkusuri, Chao Yang (eds.), Springer, Book title “Advances in Transportation Analytics in the Era of Big Data”, Complex Networks and Dynamic Systems 4, 2019
B. Peer Reviewed SCI Journal Publications
J77. Qihang Wang#, Tianci Gao#, Qing He*, Yong Liu, Jun Wu, Ping Wang. (in press). Severe Rail Wear Detection with Rail Running Band Images. Computer‐Aided Civil and Infrastructure Engineering. http://doi.org/10.1111/mice.12948
J76. Liu, Z.#, Ma, Q.#, Tang, H., Li, J., Wang, P., and He, Q.*, “Forecasting Estimated Times of Arrival of US Freight Trains”, Transportation Planning and Technology, in press, 2022.
J75. Chen, Z.#, Wang, Q.#, He, Q. *, Yu, T., Zhang, M., and Wang, P., (2022) ” CUFuse: Camera and Ultrasound Data Fusion for Rail Defect Detection” , IEEE Transactions on Intelligent Transportation Systems, 2022 (in press). DOI: 10.1109/TITS.2022.3189677
J74. Xiaoming Wang# , Qihang Wang#, Boyang An*, Qing He*, Ping Wang, Jun Wu. A GPU parallel scheme for accelerating 2D and 3D peridynamics models[J]. Theoretical and Applied Fracture Mechanics, 2022, 121: 103458.
J73. He, Q.*, Sun, H., Dobhal, M., Li, C., and Mohammadi, R., Railway Tie Deterioration Interval Estimation with Bayesian Deep Learning and Data-driven Maintenance Strategy. Construction and Building Materials, Volume 342, Part A, 1 August 2022, 128040
J72. Li, Y*, Wang, P., Cen, M., and He, Q. Iterative optimization adjustment method for ballastless track irregularity of high-speed railway. Journal of Surveying Engineering, Volume 148 Issue 4. November 2022
J71. Mohammadi, R# and He, Q*.A deep reinforcement learning approach for rail renewal and maintenance planning. Reliability Engineering & System Safety, Volume 225,
2022, 108615, https://doi.org/10.1016/j.ress.2022.108615.
J70. Mengxue Yi; Yong Zeng*; Zhangyue Qin; Ziyou Xia; Qing He. Realign Existing Railway Curves without Key Parameters Information. Journal of Transportation Engineering Part A: Systems. Volume 148 Issue 8. August 2022
J69. Gao, Y.#, Gao, T., Wu, Y., Wang, P., & He, Q* (2022). Low-construction-emission cross-section optimization for mountainous highway alignment designs. Transportation Research Part D: Transport and Environment, 2022. https://doi.org/10.1016/j.trd.2022.103249
J68. Zhengxing Chen#, Qihang Wang, Tianle Yu, Min Zhang, Qibin Liu, Jidong Yao, Yanhua Wu, Ping Wang, Qing He*, “Foreign Object Detection for Railway Ballastless Trackbeds: A Semisupervised Learning Method”. Measurement, in press. https://doi.org/10.1016/j.measurement.2022.110757
J67. Sabbaghtorkan, M.#, Batta, R.* and He, Q. “On the analysis of an idealized model to manage gasoline supplies in a short-notice hurricane evacuation”. OR Spectrum, 2022, https://doi.org/10.1007/s00291-022-00665-0.
J66. Yifeng Wang, Peigen Wang, Shoutai Li, Mingyuan Gao*, Huajiang Ouyang*, Qing He, Ping Wang*, An electromagnetic vibration energy harvester using a magnet-array-based vibration-to-rotation conversion mechanism, Energy Conversion and Management, Volume 253, 2022, https://doi.org/10.1016/j.enconman.2021.115146.
J65. Li, C.#, He, Q.*, Wang, P. (2021) "Estimation of Railway Track Longitudinal Irregularity Using Vehicle Response with Information Compression and Bayesian Deep Learning". Computer-Aided Civil and Infrastructure Engineering, December 2021. http://doi.org/10.1111/mice.12802
J64. Wang, Y., Li, S., Wang, P., Gao, M., Ouyang, H.*, He, Q., & Wang, P.* (2021). A multifunctional electromagnetic device for vibration energy harvesting and rail corrugation sensing. Smart Materials and Structures. https://doi.org/10.1088/1361-665X/ac31c5
J63. Cui, Y.#, He, Q.*, Bian, L., “Generating a Synthetic Probabilistic Daily Activity-Location Schedule using Large-Scale, Long-term and Low-Frequency Smartphone GPS data with Limited Activity Information”, Transportation Research Part C, in press.
J62. Gao, T.#, Wang, Q., Yang, K., Yang, C., Wang, P., and He, Q.*, Estimation of Rail Renewal Period in Small Radius Curves: A Data and Mechanics Integrated Approach. Measurement, in press
J61. Yifeng Wang, Shoutai Li, Mingyuan Gao*, Huajiang Ouyang*, Qing He, Ping Wang*. Analysis, design and testing of a rolling magnet harvester with diametrical magnetization for train vibration[J]. Applied Energy, 2021, 300: 117373.
J60. Chen, Z.#, Q. Wang, K. Yang, J. Yao, Y. Liu, P. Wang and Q. He*, “Deep Learning for the Detection and Recognition of Rail Defects in Ultrasound B-Scan Images”, Transportation Research Record 2021, volume 2675, issue 11 https://doi.org/10.1177/03611981211021547
J59. Yang, D., Q. He* and S. Yi, “Bilevel Optimization of Intercity Railway Alignment”, Transportation Research Record 2021, volume 2675, issue 11 https://doi.org/10.1177/03611981211023756
J58. Wang, Q.#, Tang, H., Wang, Y., Gao, T., Chen, Z., Wang, J., Wang, P., He, Q.*, (2021) “A Feature Engineering Framework for Online Fault Diagnosis of Freight Train Air Brakes”, Volume 182, September 2021, Measurement. https://doi.org/10.1016/j.measurement.2021.109672
J57. Shi, Y.#, A. Bartlett, R. Dmowski, D. Duchscherer, Q. He, C. Qiao, and A.W. Sadek*, “Preliminary Safety Evaluation of a Self-Driving, Low-speed Shuttle”, Journal of Transportation Engineering, Part A: Systems 147 (8), 04021036
J56. Li, C.#, K. Yang, H. Tang, P. Wang, J. Li, and Q. He*, “Fault Diagnosis for Rolling Bearings of a Freight Train Under Limited Fault Data: A Few-shot Learning Method”, Journal of Transportation Engineering, 2021, accepted.
J55. Gao, T.#, Li Z., Gao Y., Schonfeld P., Feng X., Wang Q., & He, Q.* (2021) A Deep Reinforcement Learning Approach to Mountain Railway Alignment Optimization. Computer‐Aided Civil and Infrastructure Engineering, 07 May 2021. https://doi.org/10.1111/mice.12694
http://link.springer.com/article/10.1007/s42421-021-00037-0
J54. Ghofrani, F.#, H., Sun, and Q. He*, “Analyzing Risk of Service Failures in Heavy Haul Rail Lines: A Hybrid Approach for Imbalanced Data”, Risk Analysis. accepted. 2020. DOI:10.1111/risa.13694
J53. Ghofrani, F.#, S. Yousefianmoghadam, Q. He*, and A. Stavridis, "Rail Breaks Arrival Rate Prediction: A Physics-Informed Data-Driven Analysis for Railway Tracks", Measurement 172 (2021), 108858. https://doi.org/10.1016/j.measurement.2020.108858
J52. Mohammadi, R.#, He Q.*, & Karwan M.,(2021) Data-driven Robust Strategies for Joint Optimization of Rail Renewal and Maintenance Planning, Omega-International Journal of Management Science, Volume 103, September 2021. https://doi.org/10.1016/j.omega.2020.102379
J51. Wang, Y., M. Gao, H. Ouyang*, S. Li, Q. He, and P. Wang*,(2020) “Modelling, Simulation, and Experimental Verification of a Pendulum-flywheel Vibrational Energy Harvester”, Smart Materials and Structures 29,115023.
J50. Wang, Y., Wang P., Li Z., Chen Z., He Q.*, "Forecasting Urban Rail Transit Vehicle Interior Noise and Its Applications in Railway Alignment Design", Journal of Advanced Transportation, vol. 2020, Article ID 5896739, 13 pages, 2020. https://doi.org/10.1155/2020/5896739
J49. Tang, L.#, Q. He*, D. Wang, and C. Qiao, “Multi-modal Traffic Signal Control in a Shared Space Street”, IEEE Transactions on Intelligent Transportation Systems (in press). 2020. DOI: 10.1109/TITS.2020.3011677
J48. Yang, D., Q. He*, and S. Yi, “Underground Metro Interstation Horizontal Alignment Optimization with an Augmented Rapidly Exploring Random Tree Connect Algorithm”, Journal of Transportation Engineering. 2020. https://doi.org/10.1061/JTEPBS.0000454
J47. Gao, T.#, J. Cong, P. Wang, Y. Wang and Q. He*, “Vertical Track Irregularity Analysis of High-Speed Railways on Simply-supported Beam Bridges based on the Virtual Track Inspection Method”, Proceedings of iMeche, Part F: Journal of Rail and Rapid Transit (in press)
J46. Cui, Y.#, Makhija, R.*, R. Chen, Q. He*, and A. Khani, “Understanding and Modeling the Social Preferences for Riders in Rideshare Matching”, Transportation. 2020. 10.1007/s11116-020-10112-0
J45. Li, C.#, P. Wang, T. Gao, J. Wang, C. Yang, H. Liu, and Q. He*. “A Spatial-Temporal Model to Identify the Deformation of Underlying Highspeed Railway Infrastructure”. Journal of Transportation Engineering Part A-Systems 146 (8), 2020. https://doi.org/10.1061/JTEPBS.0000408.
J44. Seliman, S.#, A. Sadek, and Q. He*, “Optimal Variable, Lane-based, Speed Limits at Freeway Lane-drops: A Multi-Objective Approach”, Journal of Transportation Engineering. 2020. https://doi.org/10.1061/JTEPBS.0000395
J43. Wang, Y., P. Wang, Q. Wang, Z. Chen, and Q. He*, “Using Vehicle Interior Noise Classification for Monitoring Urban Rail Transit Infrastructure”, Sensors, 2020, 20(4), 1112; https://doi.org/10.3390/s20041112
J42. Tang, L.#, Y. Shi, Q. He*, A.W. Sadek, and C. Qiao, “Performance Test of Autonomous Vehicle Lidar Sensors Under Different Weather Conditions”. Transportation Research Record: Journal of the Transportation Research Board, Vol 2674, Issue 1, 2020. https://doi.org/10.1177/0361198120901681
J41. Mahdavilayen, M.#, V. Paquet, and Q. He* “Using Microsimulation to Estimate Effects of Boarding Conditions on Bus Dwell Time and Schedule Adherence for Passengers with Mobility Limitations”, Journal of Transportation Engineering, Part A: Systems Vol. 146, Issue 6, June 2020. https://doi.org/10.1061/JTEPBS.0000365
J40. Khare, A.#, Q. He*, and R. Batta, “Predicting Gasoline Shortage During Disasters Using Social Media”, OR Spectrum (doi:10.1007/s00291-019-00559-8). https://link.springer.com/article/10.1007%2Fs00291-019-00559-8
J39. Sabbaghtorkan, M.#, R. Batta*, and Q. He, “Prepositioning of assets and supplies in disaster operations management: review and research gap identification”, European Journal of Operational Research (in press). https://doi.org/10.1016/j.ejor.2019.06.029
J38. Gao, M., J. Cong, J. Xiao, Q. He, S. Li, Y. Wang, Y. Yao, R. Chen, P. Wang*, “Dynamic modeling and experimental investigation of self-powered sensor nodes for freight rail transport”, Applied Energy Volume 257, 1 January 2020, 113969
J37. Ghofrani, F.#, Pathak, A#, R. Mohammadi#, A. Aref, and Q. He*, “Forecasting Rail Defect Frequency with Both Fracture Mechanics and Data Analytics: A Framework with Approximate Bayesian Computation”, Computer-Aided Civil and Infrastructure Engineering. Volume35, Issue2. February 2020. Pages 101-11. https://doi.org/10.1111/mice.12453
J36. Mohammadi, R.#, Q. He*, Ghofrani, F.#, Pathak, A#, and A. Aref, “Exploring the Impact of Foot-by-Foot Track Geometry on the Occurrence of Rail Defects”, Transportation Research Part C: Emerging Technologies, Volume 102, May 2019, Pages 153-172.
J35. Shi, Y.#, Q. He*, and Z. Huang “Capacity Analysis and Cooperative Lane-changing for Connected and Automated Vehicles: an Entropy-based Assessment Method”, Transportation Research Record: Journal of Transportation Research Board (https://doi.org/10.1177/0361198119843474), Volume 2673, Issue 8, 2019
J34. Ghofrani, F.#, Q. He*, R. Mohammadi#, M. Ni#, A. Pathak, and A. Aref, “Bayesian Survival Approach to Analyzing the Risk of Recurrent Rail Defects”, Transportation Research Record: Journal of Transportation Research Board, Vol. 2673(7) 281–293, https://doi.org/10.1177/0361198119844241, 2019
J33. Cui, Y#, C. Meng#, Q. He*, and J. Gao, “Forecasting Current and Next Trip Purpose with Social Media Data and Google Places”, Transportation Research Part C: Emerging Technologies, Volume 97, December 2018, Pages 159-174
J32. Kumar, P., A. Khani*, and Q. He, “A Robust Method for Estimating Transit Passenger Trajectories Using Automated Data”, Transportation Research Part C: Emerging Technologies, Volume 95, October 2018, Pages 731-747
J31. Zhang, Z.#, Q. He*, J. Gou, and X. Li, “Analyzing Travel Time Reliability and Its Influential Factors of Emergency Vehicles with Generalized Extreme Value Theory”, Journal of Intelligent Transportation Systems, 2018, DOI: 10.1080/15472450.2018.1473156
J30. Ghofrani, F.#, Q. He*, R. Goverde, and X. Liu, “Recent Applications of Big Data Analytics in Railway Transportation Systems: A Survey”, Transportation Research Part C: Emerging Technologies, Volume 90, May 2018, pp 226–246
J29. Caceres, H.#*, R. Batta, and Q. He, “Special Need Students School Bus Routing: Consideration for Mixed Load and Heterogeneous Fleet”, Socio-Economic Planning Sciences, Volume 65, March 2019, Pages 10-19
J28. Fetzer, J.##, H. Caceres#, Q. He* and R. Batta, “A Multi-Objective Optimization Approach to the Location of Road Weather Information System in New York State”, Journal of Intelligent Transportation Systems 22:6, 503-516, 2018, DOI: 10.1080/15472450.2018.1439389
J27. Cui, Y.#, Q. He*, and A Khani, “Travel Behavior Classification: An Approach with Social Network and Deep Learning”, Transportation Research Record: Journal of the Transportation Research Board, Vol 2672, Issue 47, pp 68-80, 2018
J26. Hou, Y.#*, S. Seliman#, E. Wang, J.D. Gonder, E. Wood, Q. He, A. Sadek, S. Lu, C. Qiao, “Cooperative and Integrated Vehicle and Intersection Control for Energy Efficiency (CIVIC-E2)” IEEE Transactions on Intelligent Transportation Systems, Volume: 19, Issue: 7, July 2018, pp 2325-2337
J25. Wang, W.#, Q. He*, Y. Cui and Z. Li, “Joint Prediction of Remaining Useful Life and Failure Type of Train Wheelsets: A Multi-task Learning Approach”, Journal of Transportation Engineering Part A: Systems, 144(6), 2018
J24. Cui, Y.#, Q. He*, Z. Zhang#, and Z. Li, “Identification of Railcar Asymmetric Wheel Wear with Extreme Value Theory”, Transport 34(5) 2019. 569-578. https://doi.org/10.3846/transport.2019.11657
J23. Sharma, S.#, Y. Cui#, Q. He*, R. Mohammadi#, and Z. Li, “Data-Driven Optimization of Railway Maintenance for Track Geometry”, Transportation Research Part C: Emerging Technologies, Volume 90, May 2018, pp 34–58
J22. Zhang, Z.#, Q. He*, J. Gao and M. Ni#, “A Deep Learning Approach for Detecting Traffic Accidents from Social Media Data” Transportation Research Part C: Emerging Technologies, Volume 86, January 2018, pp 580–596.
J21. Zhang, Z.#, Q. He*, and S. Zhu, “Potentials of Using Social Media to Infer the Longitudinal Travel Behavior: A Sequential Model-based Clustering Method”, Transportation Research Part C: Emerging Technologies, Volume 85, December 2017, pp 396–414.
J20. Caceres, H.#, R. Batta*, and Q. He, “School Bus Routing with Stochastic Demand and Duration Constraints”, Transportation Science, 51(4), 2017, 1349-1364.
J19. Devari. A#, A. Nikolae, Q. He*. “Crowdsourcing the Last Mile Delivery of Online Orders by Exploiting the Social Networks of Retail Store Customers”, Transportation Research Part E: Logistics and Transportation Review, Volume 105, September 2017, pp 105–122.
J18. Chen, C., H. Tong*, L. Xie, L. Ying, and Q. He. “Cross-Dependency Inference in Multi-Layered Networks: A Collaborative Filtering Perspective”. ACM Transactions on Knowledge Discovery from Data (TKDD) .11 (4), 42, 2017, pp 1-26
J17. Ni, M.#, Q. He*, and J. Gao, “Forecasting the Subway Passenger Flow under Event Occurrences with Social Media”, IEEE Transactions on Intelligent Transportation Systems, Volume: 18, Issue: 6, June 2017, pp 1623-1632.
J16. Caceres, H.#, H. Hwang#, and Q. He*, “Estimating Freeway Route Travel Time Distributions with Consideration of Time-of-Day, Inclement Weather and Traffic Incidents”, Journal of Advanced Transportation, Volume 50, Issue 6, October 2016, Pages 967–987
J15. Su, X.#, Caceres, H.#, Tong, H., and Q. He*, “Online Travel Mode Identification using Smartphones with Battery Saving Considerations”, IEEE Transactions on Intelligent Transportation Systems, Volume: 17, Issue: 10, Oct. 2016, pp 2921-2934.
J14. Zhang, Z.#, Q. He*, H. Tong, J. Gou, and X. Li, “Spatial-temporal Traffic Flow Pattern Identification and Anomaly Detection with Dictionary-based Compression Theory in a Large-scale Urban Network”, Transportation Research Part C: Emerging Technologies, Volume 71, October 2016, pp 284-302.
J13. He, Q.*, R. Kamineni#, and Z. Zhang#, “Traffic Signal Control with Partial Grade Separation for Oversaturated Conditions”, Transportation Research Part C: Emerging Technologies, Volume 71, October 2016, Pages 267-283.
J12. Zhang, Z.#, M. Ni#, Q. He*, J. Gao, J. Gou, and X. Li. “An Exploratory Study on the Correlation between Twitter Concentration and Traffic Surge.” Transportation Research Record: Journal of the Transportation Research Board, 2016, No. 2553, pp. 90–98.
J11. Zhang, Z.#, Q. He*, J. Gou, and X. Li, “Performance Measure for Reliable Travel Time of Emergency Vehicles”, Transportation Research Part C: Emerging Technologies, Volume 65, April 2016, pp 97–110.
J10. Asamoah, C.#, and Q. He*, “Dynamic Flashing Yellow for Emergency Evacuation Signal Timing Plan in a Corridor”, Transportation Research Record: Journal of the Transportation Research Board, No. 2532, 2015, pp 154-163.
J9. Ding, N.#, Q. He*, C. Wu, and J. Fetzer##, “Modeling Traffic Control Agency Decision Behavior for Multi-modal Manual Signal Control under Event Occurrences”, IEEE Transactions on Intelligent Transportation Systems, Volume:16, Issue:5, 2015, pp 2467 – 2478.
J8. Lin, L.#, M. Ni#, Q. He, J. Gao, and A. Sadek*, “Modeling the Impacts of Inclement Weather on Freeway Traffic Speed: An Exploratory Study Utilizing Social Media Data”, Transportation Research Record: Journal of the Transportation Research Board, Sep 2015, Vol. 2482, pp. 82-89.
J7. Li Z., and Q. He*. “Prediction of Railcar Remaining Useful Life by Multiple Data Source Fusion”, IEEE Transactions on Intelligent Transportation Systems, Volume:16, Issue:4, 2015, pp 2226 – 2235.
J6. He, Q.*, H. Li, D. Bhattacharjya, D. Parikh and A. Hampapur, “Track Geometry Defect Rectification Based on Track Deterioration Modelling and Derailment Risk Assessment”, Journal of Operations Research Society. Volume 66, 2015, pp 392-404.
J5. Ding, N.#, Q. He*, and C. Wu, “Performance Measures of Manual Multi-Modal Traffic Signal Control”, Transportation Research Record: Journal of the Transportation Research Board, No. 2438, 2014, pp 55-63.
J4. He, Q., K. L. Head* and J. Ding, “Multi-Modal Traffic Signal Control with Priority, Signal Actuation and Coordination", Transportation Research Part C: Emerging Technologies, Volume 46, September 2014, pp 65-82.
J3. Li H.*, D. Parikh, Q. He, B. Qian, Z. Li, D. Fang, and A. Hampapur. “Improving Rail Network Velocity: A Machine Learning Approach to Predictive Maintenance”, Transportation Research Part C: Emerging Technologies, Volume 45, 2014, pp 17-26.
J2. He, Q., K. L. Head* and J. Ding, “PAMSCOD: Platoon-based Multi-modal Traffic Signal Control with Online Data”, Transportation Research Part C: Emerging Technologies, Volume 20, Issue 1, February 2012, pp 164-184, and Proceedings of 19th International Symposium on Transportation and Traffic Theory (ISTTT 19), Berkeley, CA, 2011.
J1. He, Q., K. L. Head* and J. Ding, “Heuristic Algorithm for Priority Traffic Signal Control”, Transportation Research Record: Journal of the Transportation Research Board, No. 2259, 2011, pp 1–7.
C. Peer Reviewed NON-SCI Journal Publications
J60. Cui, Y.#, Q. He*, “Inferring Twitters’ Socio-Demographics to Correct Sampling Bias of Social Media Data for Augmenting Travel Behavior Analysis”, Journal of Big Data Analytics in Transportation. in press. 2021.
J55. Seliman, S.#, Q. He, and A. Sadek*, “Automated Vehicle Control at Freeway Lane-drops: A Deep Reinforcement Learning Approach”, Journal of Big Data Analytics in Transportation (in press).
J50. Bartlett, A.#, Q. Qiao, Q. He, and A. Sadek*, “Factors Affecting International Border Crossing Delays Based Upon a Rich Bluetooth Dataset”, Journal of Big Data Analytics in Transportation (in press). https://doi.org/10.1007/s42421-020-00016-x
J43. Ni, M.#, Q. He*, X. Liu, and A. Hampapur. “Same-Day Delivery with Crowdshipping and Store Fulfillment in Daily Operations”. Transportation Research Procedia 38, 2019, 894-913 (accepted and presented at ISTTT23, the leading transportation conference). https://doi.org/10.1016/j.trpro.2019.05.046
J40. Meng, C.#, Y. Cui#, Q. He, L. Su and J. Gao*, “Towards the Inference of Travel Purpose with Heterogeneous Urban Data”, IEEE Transactions on Big Data. 2019 10.1109/TBDATA.2019.2921823
J13. Kim, M.#*, R. Batta and Q. He, “Optimal Routing of Infiltration Operations”, Journal of Transportation Security. Volume 9, issue 1, 2016, pp 87–104.
VI. Professional Activities and Service
· Academic
o Associate Editor, IEEE Transactions on Intelligent Transportation Systems, March 2021- present
o Associate Editor, ASCE Journal of Transportation Engineering, Part A: Systems, March 2019- present
o Handling Editor, Transportation Research Record: Journal of the Transportation Research Board (TRR), January 2020- present
o Editorial Board, Big Data Analytics in Transportation, July 2018- present.
o Editorial Advisory Board, Transportation Research Part C: Emerging Technologies (Impact Factor: 6.08), March 2017- present
o Guest Editor (leading), special issue in “Big Data Railway Transportation”, Transportation Research Part C: Emerging Technologies, January 2017- present
o Chair, Traffic Simulation Subcommittee, Transportation Research Board Standing Committee in Traffic Signal Systems AHB25, April 2018 - present
o Chair for Intelligent Transportation System (ITS), The Special Interest Group (SIG) for Transportation Society and Logistics (TSL), INFORMS, September 2017 - present
§ Committee reasonability: organize INFORMS sessions in ITS.
o Chair of Student Paper Award Committee, Railway Application Section, INFORMS, December 2019 - December 2020
§ Committee reasonability: organize judge committee to evaluate student paper submissions and present the student award during INFORMS annual meeting.
o Public Relation Officer, Railway Application Section, INFORMS, December 2018 - December 2019
§ Committee reasonability: Managing and making new additions to RAS website; Managing RAS distribution list; Making sure RAS newsletter with quality content is published and distributed in a timely fashion; Identifying content, frequency and methods of communicating with the membership; Identifying and executing strategies to retain current members and recruit new members; Periodically (at least once a year) soliciting feedback on member satisfaction
