Publications for NSF Project HELP

 

Journals or Juried Conference Papers

  • Ye, Wei and Hu, Xinyue and Liu, Tian and Sun, Ruoyu and Li, Yanhua and Zhang, Zhi-Li. (2022). 5GNN: extrapolating 5G measurements through GNNs. Proceedings of the 1st International Workshop on Graph Neural Networking (GNNet '22:). 36 to 41. 

  • Wu, Ziyan and Zhang, Yang and Feng, Wendi and Zhang, Zhi-Li. (2022). NFlow and MVT Abstractions for NFV Scaling. 

  • Zhang, Zhi-Li and Dayalan, Udhaya Kumar and Ramadan, Eman and Salo, Timothy J. (2021). Towards a Software- Defined, Fine- Grained QoS Framework for 5G and Beyond Networks. NAI'21: Proceedings of the ACM SIGCOMM 2021 Workshop on Network-Application Integration. 7 to 13.

  • Tian, Feng and Zhang, Yang and Ye, Wei and Jin, Cheng and Wu, Ziyan and Zhang, Zhi-Li. (2021). Accelerating Distributed Deep Learning using Multi-Path RDMA in Data Center Networks. ACM SIGCOMM Symposium on Software Defined Networking Research (SOSR'21).

  • Rathee, Sandhya and Varyani, Nitin and Haribabu, K. and Bajaj, Aakash and Bhatia, Ashutosh and Jashnani, Ram and Zhang, Zhi-Li. (2021). GlobeSnap: An Efficient Globally Consistent Statistics Collection for Software-Defined Networks. Journal of Network and Systems Management. 29 (3).

  • Ren, Huimin and Pan, Menghai and Li, Yanhua and Zhou, Xun and Luo, Jun. (2020). ST-SiameseNet: Spatio-Temporal Siamese Networks for Human Mobility Signature Identification. Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 1306 to 1315.

  • Zhang, Yingxue and Li, Yanhua and Zhou, Xun and Kong, Xiangnan and Luo, Jun. (2020). Curb-GAN: Conditional Urban Traffic Estimation through Spatio-Temporal Generative Adversarial Networks. Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 842 to 852.

  • Ramadan, Eman and Narayanan, Arvind and Dayalan, Udhaya Kumar and Fezeu, Rostand A. and Qian, Feng and Zhang, Zhi-Li. (2021). Case for 5G-aware video streaming applications. 5G-MeMU '21: Proceedings of the 1st Workshop on 5G Measurements, Modeling, and Use Cases. 27 to 34.

  • Ramadan, Eman and Mekky, Hesham and Jin, Cheng Jin and Dumba, Braulio and Zhang, Zhi-Li. (2021). Taproot: Resilient Diversity Routing with Bounded Latency. ACM SIGCOMM Symposium on SDN Research (SOSR).

  • Zhang, Xin and Li, Yanhua and Zhou, Xun and Zhang, Ziming and Luo, Jun. (2020). TrajGAIL: Trajectory Generative Adversarial Imitation Learning for Long-Term Decision Analysis. 2020 IEEE International Conference on Data Mining (ICDM). 801 to 810.

  • Learning for Traffic Dynamics Prediction. 2020 IEEE International Conference on Data Mining (ICDM). 1418 to 1423.

  • Ding, Yichen and Zhou, Xun and Bao, Han and Li, Yanhua and Hamann, Cara and Spears, Steven and Yuan, Zhuoning. (2020). Cycling-Net: A Deep Learning Approach to Predicting Cyclist Behaviors from Geo-Referenced Egocentric Video Data. Proceedings of the 28th International Conference on Advances in Geographic Information Systems. 337 to 346.

  • Kumar, Pramesh and Khani, Alireza. (2021). Adaptive Park-and-ride Choice on Time-dependent Stochastic Multimodal Transportation Network. Networks and Spatial Economics.

  • Zhang, Yufeng and Khani, Alireza. (2021). Integrating transit systems with ride-sourcing services: A study on the system users’ stochastic equilibrium problem. Transportation Research Part A: Policy and Practice. 150 (C) 95 to 123.

  • Zhang, Xin and Li, Yanhua and Zhang, Ziming and Zhang, Zhi-Li. (2020). f-GAIL: Learning f-Divergence for Generative Adversarial Imitation Learning. Advances in neural information processing systems.

  • Zhang, Xin and Li, Yanhua and Zhou, Xun and Luo, Jun. (2020). cGAIL: Conditional Generative Adversarial Imitation Learning—An Application in Taxi Drivers’ Strategy Learning. IEEE Transactions on Big Data. 1 to 1.

  • Pan, Menghai and Huang, Weixiao and Li, Yanhua and Zhou, Xun and Luo, Jun. (2020). xGAIL: Explainable Generative Adversarial Imitation Learning for Explainable Human Decision Analysis. Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 1334 to 1343.

  • Bao, Han and Zhou, Xun and Zhang, Yingxue and Li, Yanhua and Xie, Yiqun. (2020). COVID-GAN: Estimating Human Mobility Responses to COVID-19 Pandemic through Spatio-Temporal Conditional Generative Adversarial Networks. Proceedings of the 28th International Conference on Advances in Geographic Information Systems. 273 to 282.

  • Narayanan, Arvind and Ramadan, Eman and Mehta, Rishabh and Hu, Xinyue and Liu, Qingxu and Fezeu, Rostand A. and Dayalan, Udhaya Kumar and Verma, Saurabh and Ji, Peiqi and Li, Tao and Qian, Feng and Zhang, Zhi-Li. (2020). Lumos5G: Mapping and Predicting Commercial mmWave 5G Throughput. ACM IMC 2020. 176 to 193. 

  • Levin, Michael W. and Wong, Eugene and Nault-Maurer, Benjamin and Khani, Alireza. (2020). Parking infrastructure design for repositioning autonomous vehicles. Transportation Research Part C: Emerging Technologies. 120 (C) 102838. 

  • Pan, Menghai and Huang, Weixiao and Li, Yanhua and Zhou, Xun and Liu, Zhenming and Bao, Jie and Zheng, Yu and Luo, Jun. (2020). Is Reinforcement Learning the Choice of Human Learners?: A Case Study of Taxi Drivers. Proceedings of the 28th International Conference on Advances in Geographic Information Systems. 357 to 366. 

  • Zhang, Xin and Li, Yanhua and Zhang, Ziming and Zhang, Zhi-Li.. (2020). f-GAIL: Learning f-Divergence for Generative Adversarial Imitation Learning. Advances in neural information processing systems.

  • Kumar, Pramesh and Khani, Alireza. (2021). An algorithm for integrating peer-to-peer ridesharing and schedule-based transit system for first mile/last mile access. Transportation Research Part C: Emerging Technologies. 122 (C) 102891.

  • Benjaafar, Saif and Hu, Ming. (2019). Operations Management in the Age of the Sharing Economy: What Is Old and What Is New? Manufacturing and service operations management. 22 (1) 1.

  • Vahedian Khezerlou, Amin and Zhou, Xun and Tong, Ling and Li, Yanhua and Luo, Jun. (2019). Forecasting Gathering Events through Trajectory Destination Prediction: a Dynamic Hybrid Model. IEEE Transactions on Knowledge and Data Engineering. 1 to 1.

  • Li, Yanhua and Huang, Weixiao. (2019). Imitation Learning from Human-Generated Spatial-Temporal Data. the 3rd ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery - GeoAI 2019. 9 to 10. 

  • Zhang, Xin and Li, Yanhua and Zhou, Xun and Luo, Jun. (2019). Unveiling Taxi Drivers' Strategies via cGAIL: Conditional Generative Adversarial Imitation Learning. 2019 IEEE International Conference on Data Mining (ICDM). 1480 to 1485.

  • Wu, Guojun and Li, Yanhua and Luo, Jun. (2019). Transforming Policy via Reward Advancement. 2019 IEEE 58th Conference on Decision and Control (CDC). 4609 to 4614.

  • Ding, Yichen and Zhou, Xun and Wu, Guojun and Li, Yanhua and Bao, Jie and Zheng, Yu and Luo, Jun. (2019). Mining Spatio-temporal Reachable Regions With Multiple Sources over Massive Trajectory Data. IEEE Transactions on Knowledge and Data Engineering. 1 to 1. 

  • Yang, Mingzhou and Li, Yanhua and Zhou, Xun and Lu, Hui and Tian, Zhihong and Luo, Jun. (2020). Inferring Passengers’ Interactive Choices on Public Transits via MA-AL: Multi-Agent Apprenticeship Learning. The Web Conference 2020. 1637 to 1647. 

  • Federal Government's License = Acknowledged. (Completed by Zhang, Zhi-Li on 09/07/2020 ) Full text Citation details He, Tianfu and Bao, Jie and Li, Ruiyuan and Ruan, Sijie and Li, Yanhua and Song, Li and He, Hui and Zheng, Yu. (2020). What is the Human Mobility in a New City: Transfer Mobility Knowledge Across Cities. The Web Conference 2020. 1355 to 1365.

  • Zhang, Yingxue and Li, Yanhua and Zhou, Xun and Kong, Xiangnan and Luo, Jun. (2019). TrafficGAN: Off-Deployment Traffic Estimation with Traffic Generative Adversarial Networks. 2019 IEEE International Conference on Data Mining (ICDM). 1474 to 1479. 

  • Pan, Menghai and Huang, Weixiao and Li, Yanhua and Zhou, Xun and Liu, Zhenming and Song, Rui and Lu, Hui and Tian, Zhihong and Luo, Jun. (2020). DHPA: Dynamic Human Preference Analytics Framework: A Case Study on Taxi Drivers’ Learning Curve Analysis. ACM Transactions on Intelligent Systems and Technology. 11 (1) 1 to 19. 

  • Narayanan, Arvind and Ramadan, Eman and Carpenter, Jason and Liu, Qingxu and Liu, Yu and Qian, Feng and Zhang, Zhi-Li. (2020). A First Look at Commercial 5G Performance on Smartphones. The Web Conference (WWW) 2020. 894 to 905. 

  • Zhang, Cong and Li, Yanhua and Bao, Jie and Ruan, Sijie and He, Tianfu and Lu, Hui and Tian, Zhihong and Liu, Cong and Tian, Chao and Lin, Jianfeng and Li, Xianen. (2019). Effective Recycling Planning for Dockless Sharing Bikes. the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. 62 to 70. 

  • Ruan, Sijie and Bao, Jie and Liang, Yuxuan and Li, Ruiyuan and He, Tianfu and Meng, Chuishi and Li, Yanhua and Wu, Yingcai and Zheng, Yu. (2020). Dynamic Public Resource Allocation Based on Human Mobility Prediction. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies. 4 (1) 1 to 22. 

  • Zhang, Yufeng and Khani, Alireza. (2020). Identifying Critical Links in Transportation Network Design Problems for Maximizing Network Accessibility. Transportation Research Record: Journal of the Transportation Research Board. 2674 (2) 237 to 251. 

  • Hajdu, László and Bóta, András and Krész, Miklós and Khani, Alireza and Gardner, Lauren M.. (2020). Discovering the Hidden Community Structure of Public Transportation Networks. Networks and Spatial Economics. 20 (1) 209 to 231. 

  • He, Tianfu and Bao, Jie and Ruan, Sijie and Li, Ruiyuan and Li, Yanhua and He, Hui and Zheng, Yu. (2019). Interactive Bike Lane Planning using Sharing Bikes' Trajectories. IEEE Transactions on Knowledge and Data Engineering. 1 to 1.

  • Pan, Menghai and Li, Yanhua and Zhou, Xun and Liu, Zhenming and Song, Rui and Lu, Hui and Luo, Jun. (2019). Dissecting the Learning Curve of Taxi Drivers: A Data-Driven Approach. the 2019 SIAM International Conference on Data Mining.

  • Lyu, Yan and Chow, Chi-Yin and Lee, Victor C.S. and Ng, Joseph K.Y. and Li, Yanhua and Zeng, Jia. (2019). CB-Planner: A bus line planning framework for customized bus systems. Transportation Research Part C: Emerging Technologies. 101 (C) 233 to 253. 

  • Fisher, Tom. "What Shared Autonomous Vehicles Might Mean for Urban Design Practice". Journal of Urban Design, Volume 24, Issue 6, 2019.

  • Khezerlou, Amin Vahedian and Tong, Ling and Street, W. Nick and Li, Yanhua. (2019). Predicting Urban Dispersal Events: A Two-Stage Framework through Deep Survival Analysis on Mobility Data. the Thirty-Third AAAI Conference on Artificial Intelligence, Vol 33 (2019) ISSN 2374-3468. 

  • Xinlian Yu and Alireza Khani, Operation of shared autonomous vehicle systems: optimal fleet sizing and depot deployment. INFORMS Annual Meeting, Oct 20-23, 2019, Seattle WA.

  • Kumar, P. & A. Khani, An algorithm for integrating peer-to-peer ridesharing and schedule-based transit system for first mile/last mile access.Transportation Research Part C: Emerging Technologies.

  • Pramesh Kumar and Alireza Khani, Adaptive park-and-ride choice on time-dependent stochastic multimodal transportation network.

  • Yufeng Zhang and Alireza Khani, A Linear Programming-based Algorithm for Traffic Assignment Problem with Link Interaction. INFORMS Annual Meeting, Oct 20-23, 2019, Seattle WA.

  • Pramesh Kumar and Alireza Khani, Solving transit first mile/last mile problem with ridesharing, Under review, Transportation Research Part B: Methodological.

  • Yufeng Zhang and Alireza Khani, A Stochastic Equilibrium Problem in the Integrated Transit System with Ride-sourcing Services, submitted to Transportation Research Part B: Methodological.

  • SCCS: Smart Cloud Commuting System with Shared Autonomous Vehicles Menghai Pan, Yanhua Li, Zhi-Li Zhang, Jun Luo IEEE Transactions on Big Data. 

  • Benjaafar, S., H. Bernhard, and C. Courcoubetis, “Drivers, Riders, and Service Providers: Ride Sharing and the Future of Congestion,” Management Science, under second round of review, 2019. 

  • Benjaafar, S., J. Ding, and T. Taylor, “Labor Welfare in On-Demand Service Platforms,” Manufacturing and Service Operations Management, under second round of review, 2019.

  • Benjaafar, S., X. Li, and X. Li, “Inventory Repositioning in On-Demand Product Rental Networks,” Operations Research, under second round of review, 2019.

  • Benjaafar, S. and B. Pourghannad, “Peer to Peer Trading of Usage Allowances,” Manufacturing and Service Operations Management, under review, 2020. 

  • Yu, Y. and S. Benjaafar, “Price-Directed Cost Sharing and Demand Allocation among Service Providers with Multiple Demand Sources and Facilities,” Manufacturing and Service Operations Management, 2019. 

  • Benjaafar, S., G. Kong and X. Li, “Peer-to-Peer Product Sharing: Implications for Ownership, Usage and Social Welfare in the Sharing Economy,” Management Science, 65, 477–493, 2019). https://doi.org/10.1287/mnsc.2017.2970.

  • Zhang, Y. & A. Khani. Integrating Transit Systems with Ride-sourcing Services: A Study on the System Users’ Stochastic Equilibrium Problem. Transportation Research Part A: Policy and Practice.

  • Yu, X., P. Kumar, &A. Khani, A Two-stage Stochastic Programming Model for OptimalDepot Location of Autonomous Mobility-on-Demand Systems.Transportation Science. 

  • Tomhave, B. & A. Khani, Refined Choice Set Generation and the Investigation of Multi-criterion Transit Route Choice Behavior.Transportation Research Part A: Policy and Practice. 

  • Levin, M., E. Wong, B. Nault-Maurer & A. Khani, Parking infrastructure design for repositioning autonomous vehicles.Transportation Research Part C: Emerging Technologies. 

  • S Benjaafar, S Xiao, X Yang, “Do Workers and Customers Benefit from Competition between On-Demand Service Platforms?” Management Science, 2020.

  • Benjaafar, S., H. Liu, and S. Wu, “Dimensioning On-Demand Vehicle Sharing Systems,” Management Science, 2020.

  • Wu, S., S. Xiao, and S. Benjaafar, “Two-Sided Competition Between On-Demand Service Platforms,” Manufacturing and Service Operations Management, 2020.

Other Publications

  • Fan, Yingling; Wexler, Noah; Ryan, Galen; Douma, Frank; Hong, Chris; Li, Yanhua; and Zhi-Li Zhang (2021). Advancing Social Equity with Shared Autonomous Vehicles: Literature Review, Practitioner Interviews, and Stated Preference Surveys.. Working Report under preparation; The survey dataset can be found at https://networking.umn.edu/datasets- nsf-project-help.
  • Benjaafar, S., Xiaotang Yang, and Z. Wang (2021). Autonomous Vehicles for Ride-Hailing. working paper. 
  • Benjaafar, S., J. Xiao, S. Xiao and N. Witte (2021). Do Free Rides Lead to Lower Patient No-Show Rates: Insights from a Quasi-Experiment. working paper, 2020 (a preliminary version of the paper was presented at 31st Workshop on Information Systems and Economic (WISE), December 16-19, 2020).
  • Benjaafar, S., S. Xiao and X. Yang (2021). Do Workers and Customers Benefit from Competition Between On-Demand Service Platforms? Manufacturing and Service Operations Management, under second round of review.
  • Tom Fisher et al (2022). Future Streets: Leveraging AVs for greater health, equity, livability, and prosperity. A research report on some of the key findings of the project, more specifically, the impact of CAVs on future streets and urban design. The report can be found at https://conservancy.umn.edu/handle/11299/227891.
  • Benjaafar, S. and X. Shen (2021). Pricing on Spatial Networks. working paper.
  • Fan, Yingling and Welxer, Noah (2021). Public Attitudes and Preferences Toward a Hypothetical Future System of Shared Automated Vehicles: Examining the Roles of Gender, Race, Income, and Health. 
  • Zhi-Li Zhang, Saif Benjaafar, Frank Douma, Yingying Fan, Tom Fisher and Alireza Khani (2022). Turning Point: Shared Automated Vehicles Could Make Cities More Livable, Equitable. Summary report highlighting our key findings that targets various stakeholders.The report can be found at: The report can be found at: https://cts-d8resmod-prd.oit.umn.edu/pdf/cts-22-07.pdf.
  • S. Wu, S. Xiao and S. Benjaafar (2021). Two-Sided Competition between On-Demand Service Platforms. Manufacturing and Service Operations Management, being revised for resubmission.