I’m a UK-based AI/ML engineer with a track record of applying machine learning to science and technology innovation. I build end-to-end pipelines, clean and transform real-world data, and develop signal classification models using Python, PyTorch, and related tools. My experience spans academia and industry, from EEG signal processing to neuro-interface prototypes, and I enjoy collaborating with cross-functional teams to translate technical requirements into impactful solutions. In addition to hands-on model development, I have experience collaborating with hardware teams and researchers to validate data quality and ensure alignment with performance metrics. I’m passionate about turning scientific questions into scalable ML solutions and sharing learnings with colleagues across disciplines.

Shu Ting Wong

I’m a UK-based AI/ML engineer with a track record of applying machine learning to science and technology innovation. I build end-to-end pipelines, clean and transform real-world data, and develop signal classification models using Python, PyTorch, and related tools. My experience spans academia and industry, from EEG signal processing to neuro-interface prototypes, and I enjoy collaborating with cross-functional teams to translate technical requirements into impactful solutions. In addition to hands-on model development, I have experience collaborating with hardware teams and researchers to validate data quality and ensure alignment with performance metrics. I’m passionate about turning scientific questions into scalable ML solutions and sharing learnings with colleagues across disciplines.

Available to hire

I’m a UK-based AI/ML engineer with a track record of applying machine learning to science and technology innovation. I build end-to-end pipelines, clean and transform real-world data, and develop signal classification models using Python, PyTorch, and related tools. My experience spans academia and industry, from EEG signal processing to neuro-interface prototypes, and I enjoy collaborating with cross-functional teams to translate technical requirements into impactful solutions.

In addition to hands-on model development, I have experience collaborating with hardware teams and researchers to validate data quality and ensure alignment with performance metrics. I’m passionate about turning scientific questions into scalable ML solutions and sharing learnings with colleagues across disciplines.

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Language

English
Advanced

Work Experience

Neuro Interface Engineer Intern at MyelinZ
February 1, 2025 - October 27, 2025
Analyzed biosignal (EEG, ERP) data to evaluate cognitive performance in gamified neuro-training environments. Integrated P300 markers to assess cognitive performance, improving feedback for cognitive game development. Collaborated with interdisciplinary teams to provide feedback on game mechanics to improve the effectiveness of cognitive training.
Technical Specialist (AI) at Matilda
January 31, 2025 - January 31, 2025
Designed and implemented EEG signal processing and classification pipelines, enabling signal monitoring in prototype wearable brain device. Collaborated with hardware manufacturers, validated data quality and ensured alignment with signal performance metrics. Liaised with manufacturers, translating technical requirements into actionable specifications to support prototyping.

Education

Bachelor of Engineering (BEng) at University of Oxford
January 1, 2017 - January 1, 2020
Master of Science in Artificial Intelligence (MSc AI) at Queen Mary University of London
January 1, 2023 - January 1, 2024
MPhil in Psychiatry at The University of Hong Kong
January 1, 2020 - January 1, 2022

Qualifications

IBM Data Science Professional Certificate
January 11, 2030 - October 27, 2025

Industry Experience

Healthcare, Life Sciences, Education, Professional Services, Software & Internet