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University of North Carolina at Charlotte

• Bachelor of Science in Computer Science (AI Concentration), Bachelor of Science in Data Science.
• Honors: Levine Scholar (Premier Merit Scholarship), Chancellor's List — Fall 2023 - Spring 2025.
• GPA: 4.0/4.0

Tampere University

• Exchange Studies.

Incoming Fulbright Canada MITACS Globalink Research Intern

Teaching Assistant

• Develop and grade hands-on data mining exercises on clustering, classification, and regression, providing detailed feedback that enhances student comprehension and problem-solving skills.
• Lead student code review and office hours for a Data Mining course of 70+ students, guiding them through classical machine learning techniques.

E3 Technical Fellow

• Mentor 20+ students in computer science and interview preparation, increasing technical interview confidence and results through 1:1 guidance.
• Facilitate mock technical interviews, helping students improve problem-solving efficiency and coding quality through targeted feedback and debugging support.

Ignite Fellow

• Taught middle school students key mathematical topics, increasing engagement, comprehension, and performance via tailored tutoring sessions.

Data Science and Analytics Intern

• Pioneered a hybrid, ensemble-based recommendation engine using matrix factorization and deep learning collaborative filtering algorithms to drive a projected $3M in sales and increase user engagement by 30%.
• Designed a complementary retrieval-augmented generation (RAG) system leveraging AWS Bedrock Agents and Lambda to query Redshift and generate contextualized responses from enterprise data, increasing recommendation effectiveness by 60%.
• Engineered custom metrics to measure recommendation quality by analyzing business impact via transaction patterns, customer overlap, and item taxonomy that prioritizes more relevant and grounded recommendations.
• Performed customer segmentation using K-Means clustering to support a waterfall pricing strategy, improving customer spend and optimizing discount thresholds.

SPOA Research Assistant

• Developed intuitive spreadsheets and databases to provide Charlotte Athletics administrators and coaches with clear financial insights, enabling informed decision-making across 17 varsity sports.
• Architected and implemented a tracking system to manage NIL and performance-based bonus payments, streamlining financial operations within Charlotte Athletics' annual $35M budget.

Data Collector

• Collected player participation data for FCS and FBS teams during the 2024-2025 season, tracking personnel and position data across 60–70 plays per game.
• Tracked over 120 data points per play with a 98.5% accuracy rate, enabling timely and accurate delivery of game data to clients and improving the quality of downstream analyses.

Editor-in-Chief & Web Developer and Media Editor

• Re-established the Undergraduate Research Journal at UNC Charlotte, spearheading administrative and student outreach efforts behind the university's premier journal for undergraduate research.
• Develop the website and curate the digital version of the journal using WordPress and Bricks Builder, implementing SEO and accessibility best practices.
• Review student submissions and provide editorial feedback to improve clarity, structure, and impact across a variety of disciplines.

AI & HPC Researcher

• Analyze the performance of large language models for interpreting complex high-performance computing (HPC) logs via a scientific paper-based RAG system, reducing hallucination rates.
• Enhance the performance of language models for I/O trace log analysis, increasing the consistency and accuracy of results by 80% through prompt engineering and evaluation techniques.
• Utilize LLM evaluation frameworks to benchmark system improvements and guide modifications to the RAG pipeline, increasing development speed and impact.

Data Science and AI Engineer Intern

• Developed a custom AI assistant and chatbot, improving model performance by 70% through advanced RAG techniques such as HyDE and hybrid retrieval and custom data preprocessing.
• Analyzed labor market data using Python and statistical tools to uncover key labor trends and growth opportunities in Mecklenburg County, leading to actionable suggestions for economic development.

ML Research Assistant

• Improved the efficiency of machine learning-based learned indexes in high-write environments through an optimized retraining model, reducing accuracy degradation by 60%.
• Presented the capabilities of learned indexes at the NCSSM Mentorship Research Symposium to a diverse audience.