University of Alberta

The University of British Columbia

• Played a key role in the development of an AI-powered tool leveraging Large Language Model (LLM) technology, incorporating Agentic AI and Retrieval-Augmented Generation (RAG) techniques to enhance portfolio management for investment advisors
• Designed and implemented a custom anomaly detection algorithm to identify trends and patterns, producing actionable insights that transformed the advisor experience
• 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

Data Engineer, Amplify Program

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

CPSC 110 Teaching Assistant

• 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

School of Biomedical Engineering at UBC

Bioinformatics Software Developer

• 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

Next-Generation Sequencing (NGS) Bioinformatics WorkLearn Student

• 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’

Undergraduate Researcher - Department of Statistics

• 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

adMare BioInnovations

Bioinformatics Co-op Student

• 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

David Guo