teaching
Materials for courses you taught. Replace this text with your description.
Courses Taught
🏛 Graduate Courses
Computational Biomechanics
- Year: 2024
- Role: Instructor
- Level: Graduate
- Enrollment: ~30 students
- Topics: Finite element methods, hemodynamics simulations, Python-based modeling
- Teaching Methods: Interactive Jupyter Notebooks, live coding, group projects
- Student Achievements: One student published a journal paper based on their final project
Machine Learning for Bioengineering
- Year: 2023
- Role: Teaching Assistant (TA)
- Level: Graduate
- Enrollment: ~50 students
- Topics: Convolutional Neural Networks (CNNs), medical image analysis, deep learning
- Teaching Methods: Hands-on coding sessions, PyTorch tutorials, project-based learning
- Notes: Led weekly discussions and graded final projects
🎓 Undergraduate Courses
Introduction to Biomechanics
- Year: 2022
- Role: Teaching Assistant (TA)
- Level: Undergraduate
- Enrollment: ~100 students
- Topics: Mechanics of materials, biofluid dynamics, MATLAB simulations
- Teaching Methods: Recitation sessions, problem-solving workshops
- Notes: Designed practice exams and held office hours
📊 Summary Table
| Course | Year | Role | Level | Topics | Notes |
|---|---|---|---|---|---|
| Computational Biomechanics | 2024 | Instructor | Graduate | FEM, Hemodynamics | Student published paper |
| Machine Learning for Bioengineering | 2023 | TA | Graduate | CNNs, Medical Imaging | Led hands-on coding sessions |
| Introduction to Biomechanics | 2022 | TA | Undergraduate | Biofluid Dynamics, MATLAB | Created practice exams |
🌟 Additional Contributions
- Developed interactive coding exercises in Python & MATLAB
- Provided mentorship to students, one of whom won conference awards & got into a PhD program
- Designed innovative teaching materials for machine learning & biomechanics