GroupWiLo: Accurate and Low-cost Wi-Fi-based Localization with Minimization of Parameter Total Variation

Adaptive driving behavior modeling towards diverse driving situations using inverse reinforcement learning

Kentaro Nishi, Masamichi Shimosaka Fine-Grained Driving Behavior Prediction via Context-Aware Multi-Task Inverse Reinforcement Learning In proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020.

Robust indoor localization across smartphone models with ellipsoid features from multiple RSSIs

Early destination prediction by mobile phone sensing

Irregularity prediction based on transit app logs

Working-Relationship Detection from Fitbit Sensor Data

Urban dynamics analysis with large-scale Location data from smartphones

Modeling risk anticipation and defensive driving on residential roads using inverse reinforcement learning

Consistent collective activity recognition with fully connected CRFs

Steered Crowdsensing