Resume

Education

California Polytechnic State University, San Luis Obispo

M.S. Statistics, Minor in Data Science

Graduated: June 2025

GPA: 3.8 / 4.0

Department of Statistics Cal Poly San Luis Obispo

April 2025 - June 2025

Provided statistical guidance to university faculty and students on complex research designs and data analysis challenges
Collaborated with clients and other consultants to define research questions, determine plausible analytical approaches, and interpret findings
Conducted in-depth data analysis, addressing issues such as high numbers of zeros and non-normal data distributions
Communicated complex statistical methodologies and results effectively to non-statistical audiences, translating data into actionable knowledge

Cal Poly San Luis Obispo

February 2023 - June 2025

Perform exploratory data analysis on thousands of search and rescue missions
Investigate machine learning and deep learning methodologies to enhance training and evaluation of a multimodal model
Develop scripts using R and Python to perform data cleaning while documenting modifications and findings using Quarto and Jupyter notebooks

Department of Statistics Cal Poly San Luis Obispo

January 2022 - August 2022

Developed the largest national database of sexual misconduct cases (20k records) between K-12 educators through data collection and database merging
Computed descriptive statistics and visualizations using Python and R for research paper
Cleaned collected and outside data, then merged 6 databases together while avoiding duplicate observations

September 2024 - June 2025

Frequent Itemset Mining with tidyclust in R

Contributed implementations for Apriori and ECLAT algorithms to the tidyclust package in R, expanding the package to include frequent itemset mining
Integrated a novel clustering approach that groups column variables based on their “dominant” frequent itemsets
Designed and implemented a new prediction methodology framed as a recommender system to predict missing items in transactional datasets, utilizing confidence from frequent itemsets
Created new functions, extract_predictions() and augment_itemset_predict(), to standardize and prepare frequent itemset prediction outputs for user-friendly analysis and evaluation within the tidymodels framework

September 2023 - Present

Utilized Riot Games API to scrape and clean 10,000+ TFT match histories, implementing custom Python functions for efficient data extraction and preprocessing
Designed a relational database using SQLAlchemy and Supabase to store and query match data
Applied multilevel modeling in R to analyze player performance trends, identifying key factors correlated with win rates
Built a Shiny web app to recommend data-driven strategies based on player inputs

Student Consultant

January 2024 - June 2024

Developed and compared two classification methods: a rule-based keyword approach and machine learning models (BERT, LLAMA, BART)
Implemented filtering and aggregation methods to track project progress and measure impact on broadband connectivity across countries
Proposed a hybrid classification model combining TF-IDF and contextual embeddings for enhanced accuracy

May 2023

March 2022