A Data Enthusiast's Portfolio


Sea Otter

Toxic Behavior Classifier in Gaming

Scraped data from Twitter, Twitch, and Discord and built classification models to identify toxic behavior in gaming communities.

Keywords: Web Scraping, NLP, LSTM, BERT
Cat and Dog

Cats and Dogs Classification

Compared different combinations of feature extraction methods and machine learning models to classify images of cats and dogs.

Keywords: Random Forest, SVM, CNN, XGBoost

Bike Share Demand Forecasting

Forecasted hourly bike share demand after selecting and engineering features.

Keywords: Time Series, Random Forest, XGBoost

Recommender Systems

Developed model-based and memory-based recommender systems using implicit and explicit voting datasets.

Keywords: Collaborative Filtering

Horror Authors Comparison

Studied similarities and differences among horror authors by performing exploratory data analysis techniques such as sentiment and tf-idf analyses.

Keywords: NLP, Sentiment Analysis, Tf-Idf Analysis

About Me

After working at Morgan Stanley for two years, I'm now a Master of Engineering Student at UC Berkeley studying Operations Research. I'm currently working with Glooko to predict worsening symptoms for patients with diabetes and with GGWP to identify toxic behavior in gaming communities.

I enjoy telling data-driven stories by creating pretty visualizations and weaving compelling narratives. As a lifetime student, I'm always on the lookout for challenging projects!

I'm currently looking for Data Scientist and Machine Learning Roles that start after I graduate in May 2021. If you would like to reach out to talk about any of my projects or experience, I'd be more than happy to chat!