👤 About Me

My name is Hangli Ge (葛杭丽 | 葛杭麗). I am currently a Project Lecturer at the University of Tokyo. My research topics include ubiquitous computing, IoT, signal processing, spatio-temporal big data, knowledge graph, especially in the fields of smart city, traffic optimization, urban computing, digital twin, etc. I also have research and development experience in the telecommunications industry.

🎓 Ph.D. degree of Interdisciplinary Information studies from The University of Tokyo in 2019
📍 Affiliation: Interfaculty Initiative in Information Studies, The University of Tokyo from 2019

📝 Recent Publications & News

More Publications 👉 Google Scholar

• Hangli Ge, Xiaojie Yang, Jinyu Chen, Francesco Flammini, Noboru Koshizuka, “A Traffic Evacuation Model for Enhancing Resilience During Railway Disruption” – AI4RAILS 6th International Workshop on “Artificial Intelligence for RAILwayS” colocated with EDCC, 2025, Accpeted.

• Xiaojie Yang, Hangli Ge, Jiawei Wang, Zipei Fan, Renhe Jiang, Ryosuke Shibasaki, Noboru Koshizuka, “CausalMob: Causally Predicting Human Mobility with LLMs-derived Human Intentions toward Public Events”, - 2025, 31st SIGKDD Conference on Knowledge Discovery and Data Mining, Video

• Ge, Hangli, Xiaojie Yang, Itsuki Matsunaga, Dizhi Huang, and Noboru Koshizuka. “FRTP: Federating Route Search Records to Enhance Long-term Traffic Prediction.” In 2024 IEEE International Conference on Big Data (BigData), pp. 6842-6849. IEEE, 2024.

• Hangli Ge, Takashi Michikata, and Noboru Koshizuka.“K-neighboring on Multi-weighted Graphs for Passenger Count Prediction on Railway Networks.” 情報処理学会論文誌 Journal of Information Processing 32 (2024): 575-585. (特選論文・Specially Selected Paper)

• Xiaojie Yang, Zipei Fan, Hangli Ge, Takashi Michikata, Noboru Koshizuka, “Causality-Aware Next Location Prediction Framework Based on Human Mobility Stratification” The 21st IEEE International Conference on Ubiquitous Intelligence and Computing (UIC 2024)

• Hangli Ge, Hirotsugu Seike, and Noboru Koshizuka. “Time-Probability Dependent Knowledge Extraction in IoT-enabled Smart Building.” In 2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 503-508. IEEE, 2024.

• Hiroki Oikawa, Hangli Ge, Noboru koshizuka, “Dynamic Representative Data Management of Multiple Time Series for Edge Computing” IEEE International Conference on Communications (ICC 2023),960-966, IEEE, 2023.

• Kosugi, Yuto, Itsuki Matsunaga, Hangli Ge, Takashi Michikata, and Noboru Koshizuka. “Traffic congestion prediction using toll and route search log data.” In 2022 IEEE International Conference on Big Data (Big Data), pp. 5971-5978. IEEE, 2022.

• Oikawa, Hiroki, Hangli Ge, Koshizuka, Noboru “Efficient Compressed Ratio Estimation using Online Sequential Learning for Edge Computing”In 2023 IEEE 34th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) (pp. 1-7). IEEE

• Itsuki Matsunaga, Yuto Kosugi, Hangli Ge, Takashi Michikata, Noboru Koshizuka, “Improving Long-Term Traffic Prediction with Online Search Log Data” 2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC). IEEE, 2023

• Hiroki Oikawa, Hangli Ge, Noboru koshizuka, “On-line Interpolation-based Data Management for Time-Series Data toward Edge Computing” GLOBECOM 2022-2022 IEEE Global Communications Conference, 5050-5056

• Hangli Ge, Lifeng Lin, Renhe Jiang, Takashi Michikata, Noboru Koshizuka, “Multi-weighted Graphs Learning for Passenger Count Prediction on Railway Network”, In 2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC) (pp.374-382).IEEE.

• Hangli Ge, Zhe Sun, Yasuhira Chiba, and Noboru Koshizuka. “Accurate indoor location awareness based on machine learning of environmental sensing data.” Computers & Electrical Engineering 98 (2022): 107676.

• Hangli Ge, Xiaohui Peng, Noboru Koshizuka, Applying knowledge inference on event-conjunction for automatic control in smart building, Applied Sciences 11 (3), 935, 2021

🔹 Grants & Funding

🚀 Last updated: [2025/03/29]