CV

Education

• M.S. in University of Edinburgh, UK from 2017 to 2018
  • major: Artificial Intelligence
  • Research: End-to-End Machine Learning Positioning System based on Smartphone Multi-sensory; Multimodal Machine Learning
• B.S. in Hangzhou Dianzi University, Hangzhou, China from 2013 to 2017
  • major: Computer Science and Technology
  • Research: Face Gender Recognition using Support Vector Machine(SVM) classifier

Work experience

• Feb 2019: Software Engineer
  • Microsoft Suzhou
  • Bing Local Map team
  • Worked as an NLP engineer, aims to improve Bing Map search quality and increase its daily activity
• Aug 2022: Researcher
  • China Mobile (Suzhou) Software Technology Co.,Ltd
  • Key work items: MQTT fuzzing test, generative models, time-series models for message queues abnormal detection

Publications

Sensor-fusion for Smartphone Location Tracking using Hybrid Multimodal Deep Neural Networks

Xijia Wei, Zhiqiang Wei and Valentin Radu. Sensor-fusion for Smartphone Location Tracking using Hybrid Multimodal Deep Neural Networks. Sensors

MM-Loc: Cross-sensor Indoor Smartphone Location Tracking using Multimodal Deep Neural Networks

Xijia Wei, Zhiqiang Wei and Valentin Radu, MM-Loc: Cross-sensor Indoor Smartphone Location Tracking using Multimodal Deep Neural Networks in Proc. Int. Conf. Indoor Positioning Indoor Navigat. (IPIN), Nov. 2021, pp. 1–8.

An LSTM-based method for Message Queue Throughput Prediction

Wei Z, Zhao X, et al. An LSTM-based method for Message Queue Throughput Prediction[C]//Proceedings of the 2022 5th International Conference on Algorithms, Computing and Artificial Intelligence. 2022: 1-6.

SGANFuzz: A Deep Learning-based MQTT Fuzzing Method using Generative Adversarial Networks

Wei Z, Wei X, Zhao X, et al. SGANFuzz: A Deep Learning-based MQTT Fuzzing Method using Generative Adversarial Networks[J]. IEEE Access, 2024.

Skills

• Machine Learning & Pattern Recognition
• Natural Language Processing
  • Pre-train methods(word2vec,bert)
  • End-to-End neural machine translation
  • LLM fine-tuning
• Generative model(like GAN,VAE)
• Familiar with Python and JAVA
• Algorithms Design
• Mobile Sensing System Design
• Multimodal Machine Learning