CV

Education

M.Sc. in Artificial Intelligence for Biomedicine and Healthcare
University College London, United Kingdom
Sep. 2024 - Sep. 2025 (expected)
B.Sc. in Computer Science, Honors
McGill University, Canada
Sep. 2020 - May 2024
- Earned First Class Honors for exceptional academic performance in Computer Science

Research Assistant
McGill University | Spring 2023
- Contributed to machine learning model development for Drug Design using Graph neural networks
- Supervised by Professor Yi Yang
Research Assistant
University of Southern California | Winter 2024
- Explored Generative AI and foundational models in the context of AI for Science (AI4Science)
- Supervised by Professor Yue Zhao

Software Engineer Intern
Shanghai Hongpu Corporation | Summer 2022
- Drastically improved server file download times from 2 hours to 2 seconds by optimizing algorithms with a dynamic programming
- Solved a longstanding technical bottleneck that significantly enhanced operational efficiency
- Earned commendation and recognition from management for delivering impactful solutions

Excellent Teaching Assistance Award
SuZhou EA | SuZhou, China | July 2021
- Awarded for one-to-one teaching in IGCSE Math and Computer Science.
Programme de Bourses d’Excellence
Québec Higher Education Ministry | Montreal, Canada | September 2021
- Scholarship awarded for outstanding academic achievements.
First Class Honors in Computer Science
McGill University | Montreal, Canada | May 2024
- Graduated with First Class Honors Standing, recognizing academic excellence in Computer Science.

Developer | Sep. 2023 – 2024

Designed and implemented a Multilayer Perceptron (MLP) from scratch using NumPy for handwritten digit recognition (MNIST).

Researcher | 2023 – Present

Developed a multimodal model combining mid-axial, sagittal, and coronal MRI images with numeric data, leveraging custom ResNet for image analysis and linear layers for tabular data.
Investigating additional biomarkers and incorporating attention mechanisms to enhance predictive accuracy.

Developer | Oct. 2024

Built a custom Convolutional Neural Network (CNN) achieving high validation accuracy for X-ray-based pneumonia detection.
Applied techniques such as Batch Normalization and Dropout to enhance model robustness and prevent overfitting.

Kaggle Participant | Nov. 2024

Designed a hybrid model integrating EfficientNet and ResNet to classify retinal images for diabetic retinopathy detection.
Experimented with CosineAnnealingLR scheduler to improve training dynamics and model convergence.

Currently pursuing an MSc in Artificial Intelligence for Biomedicine and Healthcare at UCL.
Engaged in Kaggle competitions to advance practical applications of AI in healthcare.
Actively encouraging and mentoring motivated individuals passionate about the intersection of AI, health, and medicine to join collaborative projects.