Collaborated with a team on developing and maintaining supervised learning models to predict the duration of maintenance periods for U.S. Navy ships utilizing XGBoost, stonesoup, pandas, joblib, sphinx and sklearn python libraries Developed and optimized a supervised machine learning pipeline using Python (scipy, cvxpy, pandas, and control) to integrate real-time aircraft geolocation data, enabling accurate classification of aircraft by ID and prediction of future positions Responsibilities include data preprocessing, feature engineering, and model performance evaluation to enhance real-time geolocation accuracy and classification reliability

I am responsible for proctoring exams, running a lab section, hosting office hours, and grading homeworks and exams for CSE 2050: Data Structures and Algorithms in Python. I work ~10 hours per week. The topics covered include OOP, introduction to algorithmic complexity, searching and sorting, dynamic programming, and rudimentary data structures such as linked lists, graphs, trees, and hash tables.

Facilitated comprehensive tutoring sessions, dedicating ~8 hours weekly to subjects spanning Precalculus, Calculus I + II, Multivariable & Vector Calculus, Elementary Differential Equations, Physics I + II, & Linear Algebra Recognized as tutor of the week after four weeks of employment, commended for positive attitude & friendly demeanor that fosters a supportive learning environment