Xijia Wei

Xijia Wei

PhD in ML @UCL

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experience

Embedded Software Engineer & AI Researcher

Guozi Robotics Co., Ltd, Hangzhou, China

  • Optimised the inspection robots chassis control system using supervised machine learning techniques
  • Evaluated real-time robot performances of accuracy and robustness under practical scenarios

AI Researcher

Scotland Microelectronics Centre, Edinburgh, UK

  • Developed an end-to-end neural network navigation system on smartphone platforms
  • Researched machine learning algorithms to improve human activity recognition accuracy
  • Evaluated system performances using WiFi fingerprints and magnetometer cross-sensory dataset
  • Built an Android application to sample and recognise user activities on smartphones

AI Researcher

University of Edinburgh, Edinburgh, UK

  • Proposed a novel end-to-end multimodal network architecture for smartphone sensor-fusion tracking system
  • Responsible for research project design, conceptualisation, data analysis and system development
  • Published papers as the first author at the Sensors Journal and the IPIN Conference
  • Presented at the IPIN19/21/22 International Conference

Fintech Department Manager & Tech Lead

CNPC, Beijing, China

  • In charge of the FinTech Research Group
  • Led the Commercial Paper Exchange/Risk Management Platform Engineering Team
  • Optimised the system intelligence by utilising AI algorithms to detect money-laundering behaviours
  • Implemented robotic process automation technologies to the Treasury Management System
  • Developed the AI-based Position Investment Strategy Assistant

Research Assistant

UCL Interaction Centre, London, UK

  • Collaborate in UKRI-funded & EU-funding projects
  • Investigate on multimodal machine learning architecture for human understanding system
  • Data collection, processing and analysis
  • Innovate multimodal machine learning algorithms
  • Deploy in real-life scenarios

Research Scientist (PhD Internship)

Nokia Bell Labs, Cambridge, UK

  • Investigate acoustic signal processing techniques for acoustic sensing
  • Explore machine learning architecture for acoustic-based cognitive workload recognition for mental healthcare regulation
  • Develop App and conduct user studies to validate system usability and efficiency
  • Authored and contributed to scientific papers
  • Filed patent for innovative solutions

HFC GenAI Fellow (PhD Internship)

Scale AI, San Francisco, US (remote)

  • Post-training of LLMs for specific-domain knowledge
  • Propose expertise evaluation on generalized pre-trained LLMs
  • Contribute to research publications

portfolio

publications

Calibrating Recurrent Neural Networks on Smartphone Inertial Sensors for Location Tracking

Published in 2019 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2019

Calibrating recurrent neural networks on smartphone inertial sensors for location tracking.

Recommended citation: Wei, Xijia and Radu, Valentin. (2019). "Calibrating Recurrent Neural Networks on Smartphone Inertial Sensors for Location Tracking." 2019 International Conference on Indoor Positioning and Indoor Navigation (IPIN). pp. 1-8.

MM-Loc: Cross-sensor indoor smartphone location tracking using multimodal deep neural networks

Published in 2021 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2021

Cross-sensor indoor smartphone location tracking using multimodal deep neural networks.

Recommended citation: Wei, Xijia, Wei, Zhiqiang, and Radu, Valentin. (2021). "MM-Loc: Cross-sensor indoor smartphone location tracking using multimodal deep neural networks." 2021 International Conference on Indoor Positioning and Indoor Navigation (IPIN). pp. 1-8.

Leveraging Transfer Learning for Robust Multimodal Positioning Systems based on Smartphone Multisensory Data

Published in 2022 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2022

Leveraging transfer learning for robust multimodal positioning systems based on smartphone multisensory data.

Recommended citation: Wei, Xijia and Radu, Valentin. (2022). "Leveraging Transfer Learning for Robust Multimodal Positioning Systems based on Smartphone Multisensory Data." 2022 International Conference on Indoor Positioning and Indoor Navigation (IPIN). pp. 1-8.

Understanding the Quality of Body Movement by Leveraging WiFi Sensing

Published in MobiUK 2023, 2023

Understanding the quality of body movement by leveraging WiFi sensing.

Recommended citation: Wei, Xijia, Shi, Fangzhan, Wu, Shuang, Chetty, Kevin, Cho, Youngjun, and Berthouze, Nadia. (2023). "Understanding the Quality of Body Movement by Leveraging WiFi Sensing." MobiUK 2023.

Leveraging WiFi Sensing Toward Automatic Recognition of Pain Behaviors

Published in International Conference on Affective Computing + Intelligent Interaction (ACII), 2023

Leveraging WiFi sensing toward automatic recognition of pain behaviors.

Recommended citation: Wei, Xijia, Olugbade, Temitayo, Shi, Fangzhan, Wu, Shuang, Williams, Amanda, Gold, Nicholas, Cho, Youngjun, Chetty, Kevin, and Bianchi-Berthouze, Nadia. (2023). "Leveraging WiFi Sensing Toward Automatic Recognition of Pain Behaviors." International Conference on Affective Computing + Intelligent Interaction.

FabricTouch: A multimodal fabric assessment touch gesture dataset to slow down fast fashion

Published in 2023 11th International Conference on Affective Computing and Intelligent Interaction (ACII), 2023

A multimodal fabric assessment touch gesture dataset to slow down fast fashion.

Recommended citation: Olugbade, Temitayo, Lin, Lili, Sansoni, Alice, Warawita, Nihara, Gan, Yuanze, Wei, Xijia, Petreca, Bruna, Boccignone, Giuseppe, Atkinson, Douglas, Cho, Youngjun, et al. (2023). "FabricTouch: A multimodal fabric assessment touch gesture dataset to slow down fast fashion." 2023 11th International Conference on Affective Computing and Intelligent Interaction (ACII). pp. 1-8.

Vomee: A Multimodal Sensing Platform for Video, Audio, mmWave and Skeleton Data Capturing

Published in Proceedings of the 2025 ACM Workshop on Access Networks with Artificial Intelligence, 2025

A multimodal sensing platform for capturing video, audio, mmWave and skeleton data.

Recommended citation: Wei, Xijia, Fang, Yuan, Chetty, Kevin, Cho, Youngjun, and Bianchi-Berthouze, Nadia. (2025). "Vomee: A Multimodal Sensing Platform for Video, Audio, mmWave and Skeleton Data Capturing." Proceedings of the 2025 ACM Workshop on Access Networks with Artificial Intelligence. pp. 36-40.

mmWaveTryOn: The first mmWave-RGB Dataset for Clothes Try-On Multimodal Gesture Recognition

Published in Proceedings of the 2025 ACM Workshop on Access Networks with Artificial Intelligence, 2025

The first mmWave-RGB dataset for clothes try-on multimodal gesture recognition.

Recommended citation: Wei, Xijia, Fang, Yuan, Liu, Zihan, Zhu, Xiyue, Wang, Jiawei, Liu, Yifu, Petreca, Bruna, Baurley, Sharon, Chetty, Kevin, Cho, Youngjun, et al. (2025). "mmWaveTryOn: The first mmWave-RGB Dataset for Clothes Try-On Multimodal Gesture Recognition." Proceedings of the 2025 ACM Workshop on Access Networks with Artificial Intelligence. pp. 31-35.

Multi-Sensor Fusion for Indoor Smartphone Localization with Attention Mechanism

Published in Proceedings of the 3rd ACM Workshop on Smart Wearable Systems and Applications, 2025

Multi-sensor fusion for indoor smartphone localization with attention mechanism.

Recommended citation: Li, Haoxuan, Wei, Xijia, Wei, Zhiqiang, Radu, Valentin, Wang, Cheng, and Li, Wenda. (2025). "Multi-Sensor Fusion for Indoor Smartphone Localization with Attention Mechanism." Proceedings of the 3rd ACM Workshop on Smart Wearable Systems and Applications. pp. 19-24.

WiProt: A WiFi-RGBD Fusion System for Robust Protective Behaviour Recognition

Published in Proceedings of the Second International Workshop on Radio Frequency (RF) Computing, 2025

A WiFi-RGBD fusion system for robust protective behaviour recognition.

Recommended citation: Wei, Xijia, Fang, Yuan, Shi, Fangzhan, Wu, Shuang, Williams, Amanda, Gold, Nicolas, Chetty, Kevin, Cho, Youngjun, and Bianchi-Berthouze, Nadia. (2025). "WiProt: A WiFi-RGBD Fusion System for Robust Protective Behaviour Recognition." Proceedings of the Second International Workshop on Radio Frequency (RF) Computing. pp. 6-11.

CubeDN: Real-Time Drone Detection in 3D Space from Dual mmWave Radar Cubes

Published in 2025 IEEE International Conference on Robotics and Automation (ICRA), 2025

Real-time drone detection in 3D space from dual mmWave radar cubes.

Recommended citation: Fang, Yuan, Shi, Fangzhan, Wei, Xijia, Chen, Qingchao, Chetty, Kevin, and Julier, Simon. (2025). "CubeDN: Real-Time Drone Detection in 3D Space from Dual mmWave Radar Cubes." 2025 IEEE International Conference on Robotics and Automation (ICRA). pp. 3977-3983.

Cognitive Load Monitoring via Earable Acoustic Sensing

Published in ICASSP 2025-2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2025

Cognitive load monitoring via earable acoustic sensing.

Recommended citation: Quan, Jiatao, Al-Naimi, Khaldoon, Wei, Xijia, Liu, Yang, Kawsar, Fahim, Montanari, Alessandro, and Dang, Ting. (2025). "Cognitive Load Monitoring via Earable Acoustic Sensing." ICASSP 2025-2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). pp. 1-5.

Listening to the Mind: Earable Acoustic Sensing of Cognitive Load

Published in Companion of the 2025 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp Companion 2025), 2026

Earable acoustic sensing offers a powerful and non-invasive modality for capturing fine-grained auditory and physiological signals directly from the ear canal, enabling continuous and context-aware monitoring of cognitive states.

Recommended citation: Wei, Xijia, Dang, Ting, Al-Naimi, Khaldoon, Liu, Yang, Kawsar, Fahim, and Montanari, Alessandro. (2026). "Listening to the Mind: Earable Acoustic Sensing of Cognitive Load." Companion of the 2025 ACM International Joint Conference on Pervasive and Ubiquitous Computing. pp. 665-671.
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