RESEARCH EXPERIENCE

・2025.04 - present: Lecturer (Assistant Professor), Waseda University

・2024.12 - 2025.03: Project Researcher, the University of Tokyo

・2023.05 - 2024.11: Reseach Fellow, Monash University 

・2021.04 - 2022.12: Project Assistant Professor, Kanazawa University

・2020.07 - 2021.02: Project Reseacher, the University of Tokyo 

・2019.10 - 2021.03: Postdoctoral Researcher, Tokyo Institute of Technology

・2019.10 - 2020.03: Visiting Researcher, Institue of Transport Studies, Monash University (Host reseacher: Dr. Nan Zheng and Prof. Hai L. Vu)

EDUCATION

・2016.10 - 2019.09: Dr.Eng. Department of Civil and Environmental Engineering, Tokyo Institute of Technology  

・2014.04 - 2016.09: M.Eng. Department of Civil Engineering, Tokyo Institute of Technology  

・2010.04 - 2014.03: B.Eng.  Department of Civil Engineering, Waseda University 

PUBLICATIONS 

1. Song, Y.,  Ngoduy, D., Dantsuji, T. , and Ding, C., 2025. Revealing the Impact of Electric Vehicle Charging on Coupled Transportation and Power Networks: A Stochastic Dynamic User Equilibrium Approach.  Transportation Research Part A, 199, 104590. 

2. Dantsuji, T. and Yamaguchi, H., 2025. Understanding changes in traffic conditions during the Tokyo 2020 Olympic and Paralympic Games. Case Studies on Transport Policy, 21, 101509. 

3. Yue, S., Zong, F., Dantsuji, T., and Ngoduy, D., 2025. A Sequencing Game Approach for Eco-friendly Platoon Merging in A Connected Environment. IEEE Transactions on Intelligent Transportation Systems, 26(8), pp.11677-11695. 

4. Liu, S.,  Ge, Q.,  Han, K.,  Fukuda, D., and Dantsuji, T., 2025. Mechanism design for coordinating vehicle-based mobile sensing tasks within the ride-hailing platform. Transportation Research Part C, 176, 105151. 

5. Dantsuji, T. and Nakagawa, M., 2025. Understanding changes in traffic demand during the Tokyo 2020 Olympic and Paralympic Games. Transportation Research Part A, 191, 104308. 

6. Dantsuji, T. and  Takayama, Y., 2024. Hypercongestion, autonomous vehicles, and urban spatial structure. Transportation Science, 58 (6), pp.1167-1426.  [ISTTT 25 Proceedings] 

7. Wang, T., Ngoduy, D., Li, Y., Lyu, H, Zou, G., and Dantsuji, T., 2024. Koopman theory meets graph convolutional network: Learning the complex dynamics of non-stationary highway traffic flow for spatiotemporal prediction. Chaos, Solitons & Fractals, 187, 115437. 

8. Wang, T., Ngoduy, D., Zou, G., Dantsuji, T., Liu, Z., and Li, Y., 2024.  PI-STGnet: Physics-integrated spatiotemporal graph neural network with fundamental diagram leaener for highway traffic flow prediction. Expert Systems with Application, 258, 125144. 

9. Dantsuji, T., Sugishita, K. and Fukuda, D., 2023. Understanding changes in travel patterns during the COVID-19 outbreak in the three major metropolitan areas of Japan. Transportation Research Part A, 175, 103762.

10. Dantsuji, T., Takayama, Y. and Fukuda, D., 2023. Perimeter control in a mixed bimodal bathtub model. Transportation Research Part B, 173, pp.267-291

11. Dantsuji, T., Hoang, H. N., Zheng, N. and Vu, L. H., 2022. A novel metamodel-based framework for large-scale dynamic origin-destination demand calibration. Transportation Research Part C, 136, 103545.

12. Dantsuji, T., Fukuda, D. and Zheng, N., 2021. Simulation-based joint optimization framework for congestion mitigation in multimodal urban network: A macroscopic approach. Transportation, 48, pp.673-697. 

13. Dantsuji, T., Hirabayashi, S., Fukuda, D. and Ge, Q., 2020. Cross comparison of spatial partitioning methods for an urban transportation network. International Journal of Intelligent Transportation Systems Research, 18, pp.412-421.

14. Zheng, N., Dantsuji, T., Wang, P. and Geroliminis, N., 2017. Macroscopic Approach for Optimizing Road Space Allocation of Bus Lanes in Multimodal Urban Networks Through Simulation Analysis. Transportation Research Record, 2651(1), pp.42-51. 

WORKING PAPERS

・ A hybrid neural network for real-time OD demand calibration under disruptions (with Dong Ngoduy, Ziyuan Pu, Seunghyeon Lee, and Hai L. Vu)

・Autonomous vehicles, urban develoyment, and welfare effects (with Zhi-Chun Li, Wen-Jing Liu, André de Palma, and Yuki Takayama)

・Knowledge-data fusion oriented traffic state estimation: A stochastic physics-informed deep learning approach (with Ting Wang, Ye Li, Rongjun Cheng, Guojian Zou, and Dong Ngoduy)

・A Bimodal Macroscopic Fundamental Diagram-Constrained Genetic Algorithm for Dynamic Dedicated Bus Lane Design 

・A unified online origin-destination prediction - calibration framework with meta-learned analytical and data-driven surrogates for proactive traffic management (with Zeren Xing, Lindong Xie, Edward Chung, Azusa Toriumi, and Takashi Oguchi)

・A new framework for vehicle trajectory prediction based on physics-informed deep learning models (with Song Xue, Hai L. Vu, and Dong Ngoduy)

・Validation of network-level traffic dynamics models using a real-world dataset (with Kentaro Wada and Keita Kuwabara)

・Do ride-hailing services compete with or complement mass transit? A multimodal morning commute problem (with Yuki Takayama and Zhi-Chun Li)

WORK IN PROGRESS

・Perimeter control with transit priority in bimodal multiregion networks: A deep reinforcement learning approach

・A real-time calibration technique for microscopic mixed traffic simulators

・A  computaionally efficient calibration technique for agent-based simulators

CONFERENCE PRESENTATIONS/PROCEEDINGS 

・Dantsuji, T., Takayama, Y., and Li, ZC. Do ride-hailing services compete with or complement mass transit? A multimodal morning commute problem. The 29th Hong Kong Society for Transportation Studies (HKSTS) Conference, Hong Kong 2025.  (Accepted)

・Dantsuji, T. A Bimodal Macroscopic Fundamental Diagram-Constrained Genetic Algorithm for Dynamic Dedicated Bus Lane Design. The IEEE 28th International Conference on Inteligent Transportation Systems (ITSC 2025), Gold Coast, 2025. (Accepted)

・Dantsuji T., Ngoduy D., Pu Z., Lee S., and Vu, L. A hybrid neural network for real-time OD demand calibration under disruptions. The 28th Hong Kong Society for Transportation Studies (HKSTS) Conference, Hong Kong 2024. 

・Dantsuji T., Ngoduy D., Pu Z., Lee S., and Vu, L. A hybrid neural network for real-time OD demand calibration under disruptions. The 45th Australasian Transport Research Forum, Melbourne, 2024. 

・Dantsuji, T. and Takayama, Y. Hypercongestion, autonomous vehicles, and urban spatial structure. The 25th International Symposium on Transportation and Traffic Theory (ISTTT 25), Michigan, 2024.

・Dantsuji, T. and Takayama, Y. Perimeter control, autonomous vehicle, and urban spatial structure. Annual School and Conference of the International Transportation Economics Association (ITEA 2023), Santander, 2023. 

・Dantsuji, T. and Fukuda, D. A bi-modal morning commute problem in urban cities with road space allocation and congestion pricing. Annual School and Conference of the International Transportation Economics Association (ITEA 2019), Paris, 2019 

・Dantsuji, T. Simulation-based joint optimization framework for congestion mitigation in multimodal urban network: A macroscopic approach. World Conference on Transport Research (WCTR2019), Mumbai, 2019. 

・Hirabayashi, S., Dantsuji, T., Fukuda, D. and Ge, Q. Cross comparison of spatial partitioning methods for urban transportation network. International Symposium of Transport Simulation (ISTS ’18) and the International Workshop on Traffic Data Collection and its Standardization (IWTDCS ’18), Matsuyama, August 2018. 

・Dantsuji, T. and Fukuda, D. Departure time and Transport Mode Choices in Cities with Road Bottleneck and Crowding in Transit. Annual School and Conference of the International Transportation Economics Association (ITEA 2018), Hong Kong, 2018 

・Dantsuji, T., Fukuda, D. and Zheng, N. A macroscopic approach for optimizing road space allocation of bus lanes in multimodal urban networks through simulation analysis: An application to the Tokyo CBD network. The IEEE 20th International Conference on Intelligent Transportation Systems (ITSC), Yokohama, 2018 

・Dantsuji, T. and Fukuda, D. Evaluation of Impact of Olympic Lanes on Urban-Scale Traffic Network in Central Tokyo Based on Macroscopic Fundamental Diagram Approach. The 21st Hong Kong Society for Transportation Studies (HKSTS) Conference, Hong Kong 2017. 

・Zheng, N., Dantsuji, T., Wang, P. and Geroliminis, N. Macroscopic Approach for Optimizing Road Space Allocation of Bus Lanes in Multimodal Urban Networks Through Simulation Analysis. Transportation Research Board 96th Annual Meeting, Washington DC, 2017. 

・Dantsuji, T., Oka, H., Hagino, Y., Fukuda, D. Preliminary study of the freight vehicle probe data from the urban freight survey in the Tokyo Metropolitan Area 2014. URBE 2015 - URban freight and BEhavior change, Rome, 2015 

WORKSHOPS, SEMINARS AND COMPETITIONS 

・Dantsuji, T.  Understanding Changes in Traffic Demand during the Tokyo 2020 Olympic and Paralympic Games, UTokyo-Cambridge Joint Seminar, 2025

・Dantsuji, T.  A hybrid neural network for real-time OD demand calibration under disruptions, the 18th UTokyoIPL-CUTI seminar, Tokyo, Japan. 2025

・Dantsuji, T. and Takayama, Y. Hypercongestion, autonomous vehicles, and urban spatial structure, International Workshop on The Future of Cities at Huazhong University of Science and Technology,  Wuhan, China, 2024

・Dantsuji, T. Perimeter control in a mixed bi-modal bathtub, Advances Behavior Modelling and Urban Networks Research Seminar, online, 2022

・Dantsuji, T. Modeling urban transportation systems. Network science seminar, Kanazawa, 2021

・Dantsuji, T. A novel metamodel-based framework for large-scale dynamic origin-destination demand calibration. International BinN Research Seminar, Tokyo, 2021. 

・Dantsuji, T. Simulation-based joint optimization framework for congestion mitigation in multimodal urban network: A macroscopic approach. Seminar organized by Institute of Transport Studies of Monash University, Melbourne, 2019. 

・Dantsuji, T. Simulation-based joint optimization framework for congestion mitigation in multi- modal urban network: A macroscopic approach. Symposium CSIS DAYS 2018, Chiba, 2018 

・Dantsuji, T. Departure Time and Mode Choice in Urban Cities with Bottleneck Congestion and Crowding Cost. Workshop ”Big data and Transportation Dynamics”, Tokyo, 2018 

・Sugishita, K., Dantsuji, T. and Nakanishi, W., Understanding universal and strategic properties of pass networks in football games based on complex network analysis. The 7th Sport Data Analsysis Competition (Football), Tokyo, 2017 

・Dantsuji, T. Macroscopic Approach for Optimizing Road Space Allocation of Bus Lanes in Multimodal Urban Networks Through Simulation Analysis. Urban Economics Workshop, Kyoto, 2017. 

・Dantsuji, T. Macroscopic Approach for Optimizing Road Space Allocation of Bus Lanes in Multimodal Urban Networks Through Simulation Analysis. International BinN Research Seminar, Tokyo, 2017.