"AML-TN sponsored internships highlight the value of developing young researchers as the next generation of machine learning specialists."
About

👋🏼 I am an undergraduate student at the University of British Columbia (UBC) interested in Machine Learning/Artificial Intelligence and Optimization. I have worked as a Research Assistant (RA) applying AI to many fields and as a software engineer. I am passionate about understanding how large neural networks work to develop safe and interpretable AI.
Awards
"These awards subsidize professors to hire international undergraduate students to work full-time on their research projects in the Summer Session (May to August)."
Selected Projects
Visualizing Neural Network Feature Transformations ✖️➕
Takes some time to load. Made with TensorFlow JS.
Experience
Bringing safe and interpretable AI into medicine. Developing software to ingest medical guidelines and provide medical recommendations using recent advances in Natural Language Processing (NLP) like Large Language Models (LLMs) and contextual embeddings. Collaborating with computer scientists, physicians and clinical researchers.
Developing a Retrieval-Augmented Generation (RAG) and program-aided agentic pipeline using open-source tools to extract and process clinical text from medical guidelines. The goal is to provide physicians with the latest evidence-based data through a natural interface while minimizing hallucinations.
Working with SCARP and Electrical and Computer Engineering to use large language models (LLMs) to analyze public records from Vancouver's housing development approval process. The work bridges AI and social science to address Canada's housing crisis and develop scalable, ethical AI tools for urban planning research.
Applied AI-based drug discovery tools like AlphaFold and ProteinMPNN to optimize sequences and 3D structures of proteins and enzymes. These tools are used to help the company optimize its sequence for desired characteristics.
Revamped automation systems for bioprocess engineering, eliminating control loop errors and enhancing system reliability by 100%. Engineered robust communication systems for sensors, pumps, motors, and valves. Developed an intuitive user interface and implemented cloud-based data backup solutions.
Contributed to SEO efforts using Wix to enhance the company's online presence.
Led the development of bespoke software solutions tailored to the unique challenges of multiphasic fluid experiments. Developed efficient (storage and compute) deep learning based particle tracking software to analyze particles in fluid behavior efficiently with single-particle precision. Built around an easy-to-use UI.
Automated and developed data collection software for new instruments invented by the research group.
Collaborated closely with interdisciplinary teams of researchers and engineers to understand the project requirements, identify technological gaps, and devise effective solutions that advance research objectives.
Additional Experience
Working with the faculty of arts to develop modules in existing faculty of arts courses that highlight how AI can be used in their field. For example, sequence modelling in economics or computer vision in archeology. Funded by UBC's Teaching and Learning Enhancement fund (TELF).
As the co-president, I lead initiatives to advance AI knowledge and guide members in developing impactful projects. Currently, I am supervising a team to develop a system that facilitates the free generation of headshots from photos through on-device generative models.
Leading the ML sub-team to explore and tune open-sourced models for object detection and tracking. This is a small piece of the puzzle on our drones that compete in two university-level autonomous drone competitions every year.
Automated brewing with IoT controlled devices while also trying to make glow in the dark beer using green fluorescent protein (GFP).
As an IT Helpdesk Support member, I provided technical assistance to faculty, staff, and students for audiovisual equipment and systems across campus.