Xijia Wei

Xijia Wei
PhD Student
Pronouns: he/him/his
[email address hidden]
+44 (0) 7754 10664
UCLIC, University College London
66 - 72 Gower Street
London, WC1E 6EA
United Kingdom

Brief biography

I am currently a PhD student at University College London (UCL) under the supervision of Prof Nadia Berthouze. I focus on sensor fusion based ubiquitous computing. I am investigating multimodal machine learning to allow models automatically learn communicative features from multisensory data without human intervention to make robust inferences under various real-life scenarios.

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

Publications

  1. X. Wei, and V. Radu, "Leveraging Transfer Learning for Robust Multimodal Positioning Systems based on Smartphone Multisensory Data," 2022 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2022, pp. 1-8.
  2. X. Wei and V. Radu, "MMLoc+: A Transfer Learning based Multimodal Machine Learning Localization System for Dynamic Sensor Networks," 2022 UK Mobile, Wearable and Ubiquitous Systems Research Symposium (MobiUK), 2022.
  3. X. Wei, Z. Wei, and V. Radu, "Sensor-Fusion for Smartphone Location Tracking Using Hybrid Multimodal Deep Neural Networks," Sensors, vol. 21, no. 22, p. 7488, Nov. 2021, doi: 10.3390/s21227488.
  4. X. Wei, Z. Wei and V. Radu, "MM-Loc: Cross-sensor Indoor Smartphone Location Tracking using Multimodal Deep Neural Networks," 2021 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2021, pp. 1-8, doi: 10.1109/IPIN51156.2021.9662519.
  5. X. Wei and V. Radu, "Calibrating Recurrent Neural Networks on Smartphone Inertial Sensors for Location Tracking," 2019 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2019, pp. 1-8, doi: 10.1109/IPIN.2019.8911768.
  6. X. Wei and V. Radu, "End-to-End Machine Learning for Smartphone-based Indoor Localisation and Tracking using Recurrent Neural Networks," 2018 UK Mobile, Wearable and Ubiquitous Systems Research Symposium (MobiUK), 2018.