•Developing a machine learning model leveraging Temporal Graph Neural Networks (TGNN) to create real-time clinical recommendations by analyzing patient characteristics and historical data.•Building a robust data pipeline with pandas for data preprocessing, cleaning, and feature engineering.•Integrating PyTorch to train the TGNN model, using time-series data to improve accuracy/performance.

• Leading 10 undergraduate students in planning monthly events to promote student collegiate growth• Holding bi-weekly office hours to aid freshman engineers in their curricular decisions and pursuits• Working with a 20-member executive team to make decisions on behalf of the entire organization.

• Coordinated sessions on resumes, interviews, and professional preparation for engineering freshmen.• Compiled a bank of 25+ upperclassmen resumes and a resume resource list of 280+ items for freshmen.• Hosted a gameshow for 60+ engineering students to spark excitement for career development

• Taught weekly sections with 50 students about object-oriented programming, looping/branching, procedural/data abstraction, and program modularity through Python.• Graded and identified algorithm errors in varying programming exams, projects, and homework.• Prepared review material and presentations on programming fundamentals for ~500 students.