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MSc in Applied Machine Learning

Imperial College London, London, United Kingdom

• Graduated with high Merit.
• Awarded Distinction grade for the Master thesis.

BEng in Mechatronic Engineering

University of Manchester, Manchester, United Kingdom

• Graduated with high First-Class Honours.
• Awarded 83% for the Final Year Project.

W. Lai, Q. Yang, Y. Mao, E. Sun and J. Ye, "Knowledge Distilled Ensemble Model for sEMG-based Silent Speech Interface," IEEE EUROCON 2023 - 20th International Conference on Smart Technologies, Torino, Italy, 2023, pp. 117-122, doi: 10.1109/EUROCON56442.2023.10198974.

Software Engineer Intern

Huawei Technologies Co., Ltd., Dongguan

• Worked in the R&D team to deliver 5G signalling system using C++ based on Huawei cloud service engine.
• Ran meetings with senior engineers and managers regularly to ensure efficient development.
• Wrote scripts in Lua for policy management module (used less than 50% of allocated time).

Fall Detection using a Networked UWB Radar System

• Delivered a real−time indoor fall detection system based on deep learning methods.
• Generated a dataset consisting of fall/non−fall samples from 10 subjects.
• Evaluated popular machine/deep learning methods (e.g., ResNet) in terms of classification accuracy, inference time and memory footprint.
• The best−performing method achieved a test accuracy of 98.3% with an inference time of 4.63 ms and model size of 141 KB.

Silent Speech Interface based on sEMG Sensors

• Built a robust and affordable (less than £100) silent speech interface (SSI) from scratch.
• Generated a dataset consisting of EMG data samples from 5 subjects.
• Trained popular machine/deep learning methods and evaluated their performance.
• Best−performing model achieved 86.1% test accuracy on both PC and microcontroller.
• Ranked first among all groups from the same course.

Knowledge Distilled Ensemble Model for sEMG−based Silent Speech Interface

• Extended previous work on SSI by using more sophisticated sEMG sensors to classify 26 NATO phonetic words.
• Proposed a deep learning method, which distills the knowledge from an ensemble voting classifier consisting of multiple 1D ResNet18.
• Best−performing method achieved 85.9% test accuracy.
• Awarded best student paper in IEEE Student Paper Contest at 2022 IEEE ACDS conference.

Human−centred Robotics: CareBot

• Developed a robot to provide daily assistance (sending fall alert and help finding objects) to the elderly.
• Developed and deployed navigation, fall detection & object finding modules on Pepper.
• Pre−trained YOLOv4−tiny and MoveNet used to perform object detection and fall detection due to their superior speed.
• Used ROS to provide inter−module communication & distributed computing, MongoDB for data storage and Docker to ease development process.
• Presented the work in a live demo and compiled a technical report; awarded the highest grade amongst competitors.

Self−Organising Multi−Agent Systems: Simulation of El hoyo

• Investigated the social behaviour of intelligent agents under resource constraints.
• Designed and implemented a type of agent based on reinforcement learning (Policy Hill Climbing) in Golang. (GitHub)
• Resulting agentbeat all other types of implementation w.r.t. self−organising ability.

Deep Learning for Human Activity Recognition Optimised for Microcontroller

• Delivered an end−to−end system capable of recognising 6 human activities using wearable inertial sensors.
• Built & evaluated a set of CNN−based models using TensorFlow.
• Compressed the best−performing model using quantization, making it 14.6x faster and 3.9x smaller.
• Successfully deployed the model on an Arduino with only 1MB CPU flash.

Autonomous Driving Embbeded System

• Delivered a line−following buggy from scratch.
• Developed the control system based on PID algorithm to compensate sensor errors.
• Regretfully, this project was interrupted by COVID19 pandemic.

• Top 5 Student Paper, IEEE Region 8 Student Paper Contest [Link]

• Best Student Paper, Student Paper Contest at Imperial College [Link]

• Gold Award, UKMT Junior Mathematical Challenge