Bio
👋🏼 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.
I am the ML Lead for UBC Uncrewed Aerial Systems (UAS) and the director of ML at the UBC AI club.
Experience
AI and Automation Developer 🧪
Lux Bio
September 2024 - May 2025
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.
Undergraduate Research Assistant 🥼
UBC Engineering at Frostad Research Group
May 2024 - September 2024
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.
Information Technology Helpdesk Support 👨💻
UBC Information Technology
May 2023 – May 2024
As an IT Helpdesk Support member, I provided technical assistance to faculty, staff, and students for audiovisual equipment and systems across campus. My responsibilities included troubleshooting hardware and software issues, responding to service requests, and ensuring the smooth operation of audiovisual resources in learning spaces and events. I worked with technologies such as Crestron Systems, JavaScript, HTML/CSS, and React to maintain and enhance audiovisual systems.
Awards
Advanced Machine Learning Network: AML-TN (April 2025)
April 2024
Issued by - Department of Computer Science, UBC | Funded by - UBC, CIFAR, NSERC
- “AML-TN sponsored internships highlight the value of developing young researchers as the next generation of machine learning specialists.”
2X Undergraduate Research Award: WLIURA
May 2024, 2025 Issued and funded by - University of British Columbia
- “These awards subsidize professors to hire international undergraduate students to work full-time on their research projects in the Summer Session (May to August).”
Other Experience
UBC Uncrewed Aircraft Systems ✈️
September 2024 – Present 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.
UBC AI Club 🦾
January 2025 – Present As the Director of Machine Learning, 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 potentially, through on-device generative models.
UBC Department of Computer Science 🏥
January 2024 – Present As part of a directed research course supervised by Dr. Raymond Ng and Dr. John Jose Nunez, I am contributing to a research project at UBC’s Psychiatry and Computer Science Departments. My work involves developing a Retrieval-Augmented Generation (RAG) and program-aided LLM 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.
Beaty Biodiversity Museum 🌿
September 2024 – Present
As part of the Machine Learning team, I utilize computer vision techniques to digitize the Beaty Museum’s botanical sample dataset. My work involves extracting traits and insights using deep learning-based computer vision methodologies.
Selected Projects
Visualizing Neural Network Feature Transformations ✖️➕
Takes some time to load. Made with TensorFlow JS.