CV

Education

Teachers College, Columbia University, PhD in Biobehavioural Science, 2024 - Present

Research focus: Hands' force internal model for healthy people (robotic movement principle)
Supervisor: Prof. Andrew Gorden

Imperial College London, MRes in Bioengineering, 2020 - 2021

Research Assistant, Imperial College London London, UK Apr 2022 - Sep 2024

Force + IMU Time-series pipeline (movement classification)

Built a MATLAB/Python-based post-processing pipeline for multimodal sensor data (force + IMU), including band-pass and noise filtering, segmentation, normalization, and feature extraction to support downstream modeling.
Trained and validated a subject-wise time-series logistic regression model for movement classification; achieved AUROC 0.705 and accuracy 0.727, and improved robustness using normalization and data augmentation.
Coordinated with a 4-person research team; maintained clear documentation for pipeline usage and contributed to shared workflow management using Google Cloud tools.

FES study (Clinical motion capture data collection & curation)

Recruited participants through London hospitals and conducted clinical movement trials for multimodal data collection.
Curated and quality-checked motion capture datasets (labelling, cleaning, organization) to enable subsequent musculoskeletal analyses and reproducible reporting.
Supported experiments using functional electrical stimulation (FES) to evaluate effects on hip muscle performance in early-stage knee osteoarthritis.

PhD researcher, Teachers College, Columbia University New York, USA Dec 2024 - Present

Mechanical representation during object grasping

Developing force models for typical grasped objects by using force sensors and clustering algorithms, and analysing mechanical feedback characteristics during dominant-hand grasping tasks
Designing analysis workflows to quantify grasp performance from force-based measures.

Data/Research intern (Registry analytics), Teachers College, Columbia University New York, USA Dec 2025 - Present

MSUD Patient Registry (CoRDS)

Cleaned and analysed survey data from 120 MSUD respondents using Python and SAS; produced clear summaries to support report writing and manuscript preparation.
Organized survey items into a structured framework (questionnaire mind map) to improve clarity and consistency across domains.
Preparing a poster presentation for GMDI 2026.

MRes researcher, Imperial College London London, UK Oct 2020 – Oct 2022

Conducted literature review and developed research methodology to estimate biomechanical performance in unilateral medial knee OA during stair activities.
Used musculoskeletal modeling software to estimate knee biomechanics; analyzed results and presented findings at an international conference.
Published in Annals of Biomedical Engineering.

Brain research Intern, University of Cambridge Cambridge, UK Jun 2021 – Dec 2022

Explored clustering of brain tumor subregions and evaluated associations with survival model outcomes; presented results via poster.

Programming: Python, MATLAB, LaTeX, C++ (intermediate)
Signal processing/Time series: filtering (Butterworth), segmentation, feature extraction, normalization, statistical modeling, visualization, pipeline building
Machine learning: regression, K-means clustering, Dynamic time warping, Cross-validation, evaluation metric (AUROC)
Data Analysis: data cleaning, missing-data handling, reproducible analysis/reporting
Languages: Mandarin (Native), English (C1 level), Cantonese (Fluent), Japanese (Fluent)