About Me
Hey! My name is Andre. I'm a final year studying Mathematics & Computer Science at the National University of Singapore (NUS).
Machine learning is an exciting field at the intersection of mathematical theory (brutal math courses finally paying off.. *_*) and software engineering. There's no shortage of groundbreaking research in the ML landscape, and I aspire to be among those who bring these innovations into real-world applications.
I am now particularly interested in the intricacies of parallelism in optimizing training code. My goal is to become capable of bridging the gap between software development and ML deployment.
Beyond academia, I am a casual climber (an occasional diver, and avid backpacker) and am part of the school's Mountaineering club and Climbing club. Together with a couple of πΈπ°π―π₯π¦π³π§πΆπ, π§πΆπ―-ππ°π·πͺπ―π¨ π€πΆπ€π¬π°π°π΄, we scaled the Himalayas and it was simply fantastic!
Ongoing
Machine Learning Research @ NUS
Part of Prof He Bing Sheng's research group, focusing on adaptations of the transformer architecture. Fortunate enough to make some publications along the way!
Data Structures & Algorithms Teaching Resource
My stint as a CS2040S (a course offered in NUS on DSA) has convinced several capable and passionate ex-students of mine to join me in developing an open-source teaching material for future cohorts. Lovely!
Experience
Software Engineer Intern @ JP MorganChase (Singapore), June 2025 - August 2025
The bank was in its Agentic AI phase, so I learnt and built MCP server(s) for backend services.
Software Engineer Intern @ QuantEdge (Singapore), May 2025 - June 2025
Software Engineering meets Quantitative Trading - Learnt how to support the trading team.
Backend Engineer Intern @ Apple (Singapore), January 2025 - May 2025
Gained practical knowledge on system design and was taught what simplicity, reliability, and sustainability looks like.
Machine Learning Engineer Intern @ Pints.ai (Singapore), August 2024 - December 2024
Worked on finetuning LLMs using data and model parallelism techniques to achieve comparable performance to larger models.
Machine Learning Engineer Intern @ ASTRI (Hong Kong, SAR), June 2024 - August 2024
Learnt ML production and deployment lifecycle, and worked on Quant Research projects affiliated with QRT.
School of Computing (NUS), August 2022 - August 2024
Teaching Assistant for CS1010s (Programming Methodology in Python) and CS2040s (Data Structures and Algorithms) - Won an award!
Latest Posts
Hong Kong: The City That Never Sleeps
Bustling city. Classy heels. Dazzling lights. Furious pace. Utter shit.
Seeds of Change (2)
The seeds are beginning to sprout
Seeds of Change (1)
Toska: An Unexpected Yearning
Nothing Fancy, Pay Attention
Attention Mechanism behind LLMs - One of the more enlightening moments from this hectic semester
Skills
Languages (Ordered by proficiency)
Python, Java, C++, TypeScript
Libraries
TensorFlow, PyTorch, Scikit-learn, OpenCV, pandas, NumPy
Notable LLM Frameworks
vLLM, llama.cpp, DeepSpeed, Lightning AI, LitGPT, LangChain
Data Processing/Databases
PostgreSQL, Spark, Flink
Backend
Docker, Django, FastAPI, Spring Boot, Express, Nodejs