Keynote Speaker

Kegen Yu

Kegen Yu

Professor, China University of Mining and Technology, China
Speech Title: Deep Learning-Based Indoor WiFi Positioning

Abstract: Wi-Fi positioning is one of the mostly investigated indoor positioning techniques, mainly due to its low cost, easy deployment, and wide range of application scenarios. However, the Wi-Fi signal is highly volatile due to multipath propagation especially in dynamic indoor environments, seriously degrading positioning accuracy. Deep learning (DL), a subset of machine learning (ML), has several advantages such as good nonlinear mapping and good fault tolerance, suited for mitigating the effect of signal fluctuation and enhance Wi-Fi indoor positioning accuracy. This presentation mainly focuses on the basic theory and algorithms of Wi-Fi indoor positioning. Several DL models are also described, which were considered for Wi-Fi indoor positioning. Furthermore, we briefly summarize the challenges and trends of DL-based Wi-Fi indoor positioning.


Biography: Kegen Yu received the Ph.D. degree in electrical engineering from the University of Sydney in 2003. He has worked for universities and research institutions in Australia, China, and Finland. He is currently a distinguished professor with China University of Mining and Technology. He authored/coauthored three books Ground-Based Wireless Positioning (Wiley-IEEE Press, 2009), Wireless Positioning: Principles and Practice (Springer, 2018), and Theory and Practice of GNSS Reflectometry (Springer, 2021). He edited/co-edited four books Positioning and Navigation in Complex Environments (IGI Global, 2018), Indoor Positioning and Navigation (Science Press, 2019), Positioning and Navigation Using Machine Learning Methods (Springer, 2024), and Advances in GNSS Reflectometry (Springer, 2026). He coauthored over 200 refereed journal and conference articles. He has been ranked in the world’s top 2% scientists list since 2023 by Stanford University and Elsevier. He was honored with Vebleo Fellow in 2026. His research interests include GNSS-R, remote sensing, and positioning and navigation.