activity
20242026
most citedCausalMob: Causal Human Mobility Prediction with LLMs-derived Human Intentions toward Public Events

12 citations · 12 across the 16 of their papers we have counts for

collaborators

17 papers

cs.LG2026

Extending FAIR Principles with Observability for Trustworthy Federated Learning

Hangli Ge, Noboru Koshizuka

Federated learning (FL) keeps data at its source, but locality alone does not make a federation trustworthy. Without sufficient observability, an aggregator cannot determine whethe…

cs.NI2026

Cyberspace Search Intentions as Leading Indicators for Proactive Traffic Hotspot Detection

Hangli Ge, Dizhi Huang, Takeshi Kawasaki +1

This study proposes a cyber-physical data-driven framework for proactive detection of highway traffic hotspots and hot regions. The proposed framework bridges users' online search…

cs.LG2026

Towards Efficient and Evidence-grounded Mobility Prediction with LLM-Driven Agent

Linyao Chen, Qinlao Zhao, Zechen Li +7

Individual-level mobility prediction is central to urban simulation, transportation planning, and policy analysis. Supervised sequence models achieve strong accuracy but require ta…

cs.LG2026

TrajFlow: Nation-wide Pseudo GPS Trajectory Generation with Flow Matching Models

Peiran Li, Jiawei Wang, Haoran Zhang +4

The importance of mobile phone GPS trajectory data is widely recognized across many fields, yet the use of real data is often hindered by privacy concerns, limited accessibility, a…

cs.LG2026

TrajGPT-R: Generating Urban Mobility Trajectory with Reinforcement Learning-Enhanced Generative Pre-trained Transformer

Jiawei Wang, Chuang Yang, Jiawei Yong +6

Mobility trajectories are essential for understanding urban dynamics and enhancing urban planning, yet access to such data is frequently hindered by privacy concerns. This research…

cs.LG2026

Place with Intention: An Empirical Attendance Predictive Study of Expo 2025 Osaka, Kansai, Japan

Xiaojie Yang, Dizhi Huang, Hangli Ge +4

Accurate forecasting of daily attendance is vital for managing transportation, crowd flows, and services at large-scale international events such as Expo 2025 Osaka, Kansai, Japan.…

eess.SY2025

Realizing Space-oriented Control in Smart Buildings via Word Embeddings

Hangli Ge, Hiroaki Mori, Yasuhira Chiba +1

This paper presents a novel framework for implementing space-oriented control systems in smart buildings. In contrast to conventional device-oriented approaches, which often suffer…

cs.DC2025

A Proposal for High-Level Architectural Model Capable of Expressing Various Data Collaboration Platform and Data Space Concepts

Masaru Dobashi, Kohei Toshimitsu, Hirotsugu Seike +3

This paper proposes "Data Space High-Level Architecture Model" (DS-HLAM) for expressing diverse data collaboration platforms across regional implementations. The framework introduc…

cs.LG2025

Deep Unfolding for MIMO Signal Detection

Hangli Ge, Noboru Koshizuka

In this paper, we propose a deep unfolding neural network-based MIMO detector that incorporates complex-valued computations using Wirtinger calculus. The method, referred as Dynami…

eess.SY2025

Simulation of Emergency Evacuation in Large Scale Metropolitan Railway Systems for Urban Resilience

Hangli Ge, Xiaojie Yang, Zipei Fan +2

This paper presents a simulation for traffic evacuation during railway disruptions to enhance urban resilience. The research focuses on large-scale railway networks and provides fl…

cs.CY2025

Origin-Destination Extraction from Large-Scale Route Search Records for Tourism Trend Analysis

Hangli Ge, Dizhi Huang, Xiaojie Yang +4

This paper presents a novel method for transforming large-scale historical expressway route search records into a three-dimensional (3D) Origin-Destination (OD) map, enabling data…

cs.HC2025

Happiness Finder: Exploring the Role of AI in Enhancing Well-Being During Four-Leaf Clover Searches

Anna Yokokubo, Takeo Hamada, Tatsuya Ishizuka +2

A four-leaf clover (FLC) symbolizes luck and happiness worldwide, but it is hard to distinguish it from the common three-leaf clover. While AI technology can assist in searching fo…

cs.LG2025

Causality-Aware Next Location Prediction Framework based on Human Mobility Stratification

Xiaojie Yang, Zipei Fan, Hangli Ge +3

Human mobility data are fused with multiple travel patterns and hidden spatiotemporal patterns are extracted by integrating user, location, and time information to improve next loc…

math.NA2025

A Traffic Evacuation Model for Enhancing Resilience During Railway Disruption

Hangli Ge, Xiaojie Yang, Jinyu Chen +2

This paper introduces a traffic evacuation model for railway disruptions to improve resilience. The research focuses on the problem of failure of several nodes or lines on the rail…

cs.LG2025★ 12 cited

CausalMob: Causal Human Mobility Prediction with LLMs-derived Human Intentions toward Public Events

Xiaojie Yang, Hangli Ge, Jiawei Wang +4

Large-scale human mobility exhibits spatial and temporal patterns that can assist policymakers in decision making. Although traditional prediction models attempt to capture these p…

cs.IR2024

Time-Probability Dependent Knowledge Extraction in IoT-enabled Smart Building

Hangli Ge, Hirotsugu Seike, Noboru Koshizuka

Smart buildings incorporate various emerging Internet of Things (IoT) applications for comprehensive management of energy efficiency, human comfort, automation, and security. Howev…

cs.AI2024

FRTP: Federating Route Search Records to Enhance Long-term Traffic Prediction

Hangli Ge, Xiaojie Yang, Itsuki Matsunaga +2

Accurate traffic prediction, especially predicting traffic conditions several days in advance is essential for intelligent transportation systems (ITS). Such predictions enable mid…