Projects
Predicting the Unpredictable: Machine Learning for Lead Time Forecasting in Supply Chains with Extreme Delivery Deviations
⭐ Created prediction models for the supply chain of a large manufacturing company. Utilized machine learning methods as well as deep learning to give confident predictions on part orders timeliness.
⭐ Presented research poster at 2025 INFORMS Analytics+ National Conference.
issnresolver - Python package
⭐ Created a Python package that gives user easy capability to look up or look down across ISSN variations (ISSN-L, ISSN, eISSN) from ISSN portal.
⭐ Built as a solo project in 2 days, published on PyPi
OnTheWay: AI-powered road trip planner
⭐ Created a webapp for road trip planning using Streamlit and Google's Gemini API. The app generates a personalized itinerary based on user preferences and travel constraints.
⭐ Built as a solo project in a total of 13 days.
Leveraging Web Scraping to Build Purdue’s Highly Prestigious Awards Historical Database
⭐ Utilized web scraping methods in Python to scrape award websites of winners and their metadata. As well as implementing various APIs to check institutional connection and data standardization. Resulted in 90,000+ award records and multiple Purdue University faculty/staff awards findings,
⭐ Presented to Association of American Universities (AAU) in Fall 2024, at Indiana Association for Institutional Research (INAIR) 2025 Conference, and at Association for Institutional Research 2025 National Conference.
Using Machine Learning to Map Grief Stages and Optimize Support for Military Survivors
⭐ Collaborated with Tragedy Assistance Program for Survivors (TAPS) to use machine learning classification models to predict grief stages based on survey responses. Achieved classification accuracy of 89%.
⭐ Presented research poster at Purdue Fall 2024 Undergraduate Research Conference.