Xijia Wei

I am a PhD candidate (writing up) at University College London, supervised by Prof Nadia Berthouze, Prof Youngjun Cho, and Prof Kevin Chetty. I develop machine learning algorithms for novel sensing systems in healthcare. My research investigates multimodal machine learning that lets models learn communicative features from multisensory data without human intervention or label-hungry annotated datasets, towards robust performance in real-life scenarios. I am currently building a multisensory sensing system that recognises and understands human body behaviours across domains.

Before UCL, I studied Artificial Intelligence (MSc) under Dr Valentin Radu and Electronics and Electrical Engineering (BEng) under Prof Tughrul Arslan, both at the University of Edinburgh.

News

Feb 2026: Our research on earable acoustic sensing of cognitive load was featured by Scimex (Science Media Exchange) and Ingenium (Official Press of the University of Melbourne), highlighting the potential of everyday earbuds for real-time brain health monitoring. Paper
Dec 2025: Our paper “Listening to the Mind: Earable Acoustic Sensing of Cognitive Load” has been published in UbiComp Companion 2025. Link
Nov 2025: I gave a talk at the University of Macau on multimodal self-supervised learning applied to the healthcare domain.
Oct 2025: I presented four works at MobiCom 2025 on wireless sensing for human tracking, behaviour recognition, novel sensing applications, and an open-source multimodal sensing platform.
Oct 2025: I presented our work on acoustic sensing for auditory cognitive load measurement at UbiComp 2025, done in collaboration with Nokia Bell Labs.
Aug 2025: I served as an AC reviewer for AAAI.
May 2024: I gave a talk at the UCL EE Department on wireless sensing for healthcare.

Apr 2024: I passed my PhD upgrade viva.
Nov 2023: I served as an AC reviewer for IMWUT.
Oct 2023: I served as an AC reviewer for CHI 2024.
Sep 2023: Two papers accepted at ACII 2023, including my first-author paper “Leveraging WiFi Sensing toward Automatic Recognition of Protective Behaviors”. See you at MIT Media Lab, Cambridge, MA.
Jun 2023: I started my PhD research internship at Nokia Bell Labs in Cambridge this summer.
May 2023: I served as a PC member for ACII 2023.
Apr 2023: I passed my first-year viva on the topic of wireless human sensing.
Sep 2022: I gave a talk at HK PolyU on “Machine-learning based Sensor-fusion Localization”. Link
Aug 2022: Paper accepted at IPIN 2022, joint work with Valentin Radu: “Leveraging Transfer Learning for Robust Multimodal Positioning Systems based on Smartphone Multisensory Data”. See you in Beijing.
May 2022: I joined the UCL Interaction Centre (UCLIC) for my PhD adventure.
Apr 2022: Paper accepted at MobiUK 2022, joint work with Valentin Radu: “MMLoc+: A Transfer Learning based Multimodal Machine Learning Localization System for Dynamic Sensor Networks”.
Jan 2022: Paper published in IEEE, joint work with Zhiqiang Wei and Valentin Radu: “MM-Loc: Cross-sensor Indoor Smartphone Location Tracking using Multimodal Deep Neural Networks”. Link
Oct 2021: Journal article accepted in Sensors, joint work with Zhiqiang Wei and Valentin Radu: “Sensor-fusion for Smartphone Location Tracking using Hybrid Multimodal Deep Neural Networks”. Link
Sep 2021: Paper accepted at IPIN 2021: “MM-Loc: Cross-sensor Indoor Smartphone Location Tracking using Multimodal Deep Neural Networks”. Video
Jul 2019: Paper accepted at IPIN 2019, joint work with Valentin Radu: “Calibrating Recurrent Neural Networks on Smartphone Inertial Sensors for Location Tracking”. See you in Pisa.
Aug 2018: Paper accepted at MobiUK 2018, joint work with Valentin Radu: “End-to-End Machine Learning for Smartphone-based Indoor Localisation and Tracking using Recurrent Neural Networks”. See you in Cambridge.

Academic service

AC reviewer: AAAI (2025), CHI 2024, IMWUT (2023)
PC member: ACII 2023