Program: Master of Science in Computer Science
Institution: University of California, Irvine
Duration: September 2025 - June 2027
Graduate GPA: TBD

Relevant Coursework

Machine Learning, Systems and ML, Computer and Communication Networks, Deep Generative Models

Graduate Thesis

TBD in 2026

Program: Bachelor of Science in Statistics
Institution: University of California, Davis
Duration: September 2021 - June 2025
Undergraduate GPA: 3.90/4.00
Minors: Mathematics and Computer Science

Awards & Honors

• Graduated with Highest Honors
• CRA Outstanding Undergraduate Researcher (Honorable Mention)
• UC Davis Statistics Outstanding Performance Citation
• Dean's Honor List (multiple quarters)

Relevant Coursework

Data Structures & Algorithms, Probability Theory, Applied Linear Algebra, Multivariate Data Analysis, Real Analysis, High-Performance Statistical Computing, Statistical Learning, Machine Learning

Honors Thesis

TowerDebias: A Novel Debiasing Method Based on the Tower Property

Program: Non-Degree Seeking; Dual Enrollment Coursework
Institution: Foothill College, United States
Duration: August 2019 - April 2021

Relevant Coursework

Object-oriented Programming in Java (A-), Object-oriented Programming in Python (A+)

Position: Undergraduate Research Assistant
Department: Statistics and Computer Science
Institution: UC Davis
Location: Davis, CA
Duration: June 2023 – June 2025

Key Responsibilities

• Designed and implemented TowerDebias, a new post-processing algorithm to reduce bias in black-box ML classifiers; evaluated fairness–accuracy trade-offs across multiple tabular datasets.
• Developed a parallelized R pipeline to run cross-validated sweeps, compute fairness metrics (statistical parity difference, equalized odds, correlation), and cut experiment runtime by over 50%.
• Authored a journal submission and maintained reproducible code, figures, and experiment logs for replicability

Position: Undergraduate Research Assistant
Department: Computer Science
Institution: UC Davis
Location: Davis, CA
Duration: June 2024 – September 2024

Key Responsibilities

• Built an end-to-end pipeline combining LLM-based relation extraction with GNN link prediction to generate knowledge graphs from hardware-security datasets (weaknesses, vulnerabilities, attack patterns).

Position: Undergraduate Reader
Department: Statistics
Institution: UC Davis
Location: Davis, CA
Duration: January 2023 – June 2023

Key Responsibilities

Grading and Assistance: Graded homework, exams, and projects, providing feedback to enhance course content and improve student learning outcomes.
Course graded: STA 103: Applied Statistics for Business; STA 106: Analysis of Variance; STA 137: Applied Time Series Analysis

Position: Software Developer (R Package)
Institution: UC Davis
Location: Davis, California, United States
Duration: June 2023 - December 2023

Key Responsibilities

• Developed a package in R (with Python interfaces) called "DSLD: Data Science Looks at Discrimination."
• Created an R package for discrimination analysis with automated EDA templates, bias diagnostics, and fair predictive modeling workflows.
• Implemented fairness metrics (statistical parity difference, equalized odds) and post-processing methods with cross-validation for linear/logistic models.

Position: Business Analyst Intern
Company: Cisco
Team: Data, Insights, and Analytics Team
Location: San Jose, CA
Duration: June 2023 – September 2023

Key Responsibilities

• Designed interactive, scalable Power BI dashboards used in Quarterly Business Reviews to track supply-chain performance and key KPIs.
• Automated data extraction and transformation with Python scripts and Microsoft tools, reducing manual reporting time by 40%.

Position: Business Analyst Intern
Company: Cisco
Team: Global Trade Compliance Team
Location: San Jose, CA
Duration: June 2022 – September 2022

Key Responsibilities

• Engineered a centralized support system in Smartsheet, reducing licensing costs by $25,000 annually.
• Led global UAT with cross-functional teams to ensure compliance and a smooth rollout; produced SOPs and training materials.

Languages

Python, R, SQL, C/C++, MATLAB, HTML/CSS, Java

ML Libraries

PyTorch, TensorFlow, NumPy, Pandas, Scikit-learn, R libraries (tidyverse, caret, ggplot2)

Tech Tools & Software

Microsoft 365, Power BI, Tableau, Smartsheet, Git, GitHub, VS Code, Jupyter Notebooks, RStudio