• Led the development of an AI-powered tool using large language models (LLM) to support portfolio management for investment advisors at RBC Wealth Management.• Incorporated advanced techniques such as agentic AI and retrieval-augmented generation (RAG) to enhance the efficiency, accuracy, and insights provided by the tool.• Developed a custom anomaly detection algorithm that identified financial trends, leading to more accurate and informed decision-making for portfolio management.• Collaborated with cross-functional teams to integrate the AI tool with existing systems, resulting in a solution that is estimated to increase advisor efficiency by at least 20% and save over 200,000 hours of time year-over-year across all advisors

• Developed a web application using R Shiny to visualize, analyze, and navigate through single-cell transcriptomic data (ISNAP: Integrated Single-cell NAvigation Portal)• Performed single-cell transcriptomic and network analysis on cardiomyocyte scRNA-seq data using R packages such as SCENIC and Seurat to discover novel transcription factor co-expression networks

• Developed a custom server-side automated pipeline to analyze and visualize genomic and transcriptomic data using R and Python• Collaborated with researchers in other labs to help set up various bioinformatics pipelines on high-performance computing systems

Undergraduate Teaching Assistant for UBC's introductory computer science course on systematic programming design (achieved 99% final grade in the course)

• Developed interactive lab tutorials for graduate bioinformatics course STAT540 (Statistical Methods for High Dimensional Biology) using R and Jupyter• Expanded lecture slides using updated data visualization packages (‘dplyr’ and ‘ggplot2’) and reorganized content to improve code consistency and formatting using ‘xaringan’ in R Markdown• Lecture topics focused on statistical inference such as: two-groups comparisons, linear regression, ANOVA, and linear models using ‘limma’

• Developed automated pipelines for high-throughput biological data using R and Python for differential gene expression analysis, pathway and network analysis, and data visualization• Improved bash scripts to automate RNA-seq workflow and set up cloud computing capabilities on AWS to improve task efficiency• Collaborated with bioinformaticians to implement novel bioinformatics infrastructure using Git for file management and version control on local servers

• Collected genomic data from databases to study evolution of imprinted genes• Examined genetic lineage of imprinted genes in plants using sequence alignment programs such as MUSCLE and RAxML• Compiled data into phylogenetic tree analyses and compared sequence homology among several plant species