Abstract

Mobility is an important key to many promising intelligent applications in sectors of smart cities and smart environments. As advanced sensing and communication technologies are rapidly developed, an interesting technical challenge is arising -- “Can we exploit multi-modal data from mobile devices to analyze social structures over trajectories?”. This talk will review wireless, visual, acoustic perception techniques for mobility analytics. Furthermore, our recent research outcomes in location-less trajectory modeling are introduced. This talk will introduce alternative techniques to find the correlation between trajectories and recognize the social structures among mobile devices without ranging and localization technologies. How to model the spatial and social relationships among mobile users using multi-modal data from mobile devices will be introduced.

Bio.

Dr. Fang-Jing Wu is an associate professor at National Taiwan University. Dr. Wu was an assistant professor at TU Dortmund in Germany from 2018 to 2023. Before TU Dortmund, she was a research scientist at Cloud Service and Smart Things Group, NEC Laboratories Europe from 2016 to 2017. Before NEC Labs, she was a scientist at the Institute of Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR), Singapore from 2013 to 2015. Before joining A*STAR, she was a research fellow at Nanyang Technological University in 2012. She was awarded a Ph.D. degree in Computer Science from the National Chiao Tung University in 2011. She was a visiting researcher at Imperial College London from 2010 to 2011. Her current research interests are primarily in pervasive computing, wireless sensor networks, wireless communications and networks, cyber-physical systems, mobile crowdsourcing, mobile computing, wearable sensing, and Internet of Things.

All faculty and students are welcome to join.