Final year MEng Computer Science student at University College London. Experienced Python full-stack developer with expertise in Machine Learning (Generative AI) and Cloud/Web. Fluent in English, Chinese and Malay. Limited proficiency in Korean and Japanese. Achieved “Top in the World” in Cambridge GCE A-Level Mathematics 2019.
Recent
Education
Master of Engineering in Computer Science
September 2020 - June 2024
- Minor in Intelligent Systems
- Integrated Masters - Direct continuation from Bachelor's Degree
- Treasurer of UCL Portuguese Speaking Society 22/23
Experiences
Machine Learning Engineer
June 2022 - February 2024
- Console Application: Full Stack. Interface implementation and API gateway token authorisation.
- Model Hub: Cloud. RESTful endpoint protection for user/admin API key authentication.
- Deployment: Compiler Engineering. Introduced the RocM backend for AMD hardware support.
- Ivy ML Models: Applied Lead. Expanded the collection from scratch to 15+ within 4 months.
- Ivy Transpiler: MLE. Introduced features of native compilation and cross-framework NumPy code compilation.
- Ivy Framework: Software Engineering. Introduced exception handling, global properties, sparse arrays, and frontend APIs.
- Tech Stack: Python, C++, Nvidia CUDA, AMD RocM, Tailwind CSS, Node.js, React.js, Next.js, TypeScript, Fast API, Flask, Prisma, Alembic, SQL, Docker, GCP, AWS, Git, Transformers, Linux
Systems Engineer Intern
October 2021 - April 2022
- QnA Chatbot for Clinical Tabular Data: ML systems engineering. Full stack development.
- Developed TAPAS RESTful endpoints with database and interface for lab report analysis.
- Tech Stack: Python, TAPAS, Rasa NLU/NLP, Django, React.js, HTML, CSS, Git, Transformers
Projects
Generative AI for Music
September 2023 - April 2024
- Music-conditioned Image Generation
- Image-conditioned Music Generation
- Tech Stack: Python, Pillow, NumPy, SciPy, PyTorch, Transformers, Diffusers, Matplotlib, Git
Network Analysis of Programming Languages
- Applied PageRank and HITS for analysing key driver in the evolution network.
- Analysed the community structure of the network with modularity.
- Tech Stack: Python, NetworkX, NumPy, Matplotlib, Git
Multi-Agent Reinforcement Learning in Portfolio Management
- Explored the effect of different RL algorithms in competitive vs. cooperative MARL settings.
- Algorithms: Advantaged Actor-Critic (A2C), Deep Deterministic Policy Gradient (DDPG), Proximal Policy Optimisation (PPO)
- Tech Stack: Python, OpenAI Gym, Stable Baselines 3, Pandas, Git
Skills
Tech Stack
os
framework
cloud/web
others
Languages
Fluent
English, Chinese, Malay
Limited
Korean, Japanese