I am a Statistician and Game Developer with a strong focus on applied data analysis, machine learning, and interactive tools.
I have a Bachelor of Science in Statistics degree from the University of Illinois Urbana-Champaign, and I am currently pursuing a Master's degree in Statistics and Analytics at the same university.
I specialize in R and Python, but I also work with Unity and C# for game development.
I enjoy building end-to-end projects, from data preparation and modeling to interactive tools and video games.
You can find some of my projects below.
- Analyzed CS:GO match and team-level data to study economy-driven decision-making across rounds.
- Merged and transformed match datasets to track transitions between eco, force, and full-buy rounds, and visualized their relationship to round outcomes using interactive plots.
- Developed a content-based recommender system to help indie developers identify potential publishers based on historical catalog similarity.
- Matched game concepts—defined by Steam tags and target price point—to publishers with comparable releases, and surfaces concrete examples to support discovery and outreach.
- Built text-based classification models to predict the geographic region of tweets using textual features. I focused on TF-IDF representations, class imbalance mitigation, and random forest modeling to improve predictive performance.
- The broader project also explored logistic regression baselines and BiLSTM models for sequential text patterns, implemented by other team members.