Teaching

I am passionate about preparing students to tackle real-world, interdisciplinary problems through project-based, adaptive, and inclusive instruction. My teaching spans mechanical engineering, AI, and robotics, and I’ve led hands-on labs, guest lectures, and international workshops. I emphasize experiential learning, human-centered design, and mentorship to foster critical thinking and collaborative skills across diverse learners.

Teaching Philosophy

My teaching philosophy centers around three core principles:

  • Experiential learning to connect theory with practice
  • Adaptive instruction to support diverse learners
  • Interdisciplinary integration to foster collaboration and critical thinking

Course Instruction

  • ME 461: Automatic Control (University of Michigan, Winter 2020)
    Teaching Assistant
    • Led hands-on labs and tutorials on feedback control, PWM, encoders, and PID controllers
    • Helped migrate course online during COVID-19 with recorded sessions, annotated slides, and virtual office hours
  • 07-180: Concepts of Artificial Intelligence (Carnegie Mellon University, Spring 2025)
    Guest Lecture – Topic: Decision Trees

  • Human-Robot Interaction (16-867) (Carnegie Mellon University, Fall 2023)
    Guest Lecture – Topic: Intent, Theory of Mind, and Implicit Communication in HRI

  • INFSCI 2300: Human Information Processing (University of Pittsburgh)
    Guest Lectures
    • Spring 2024: Intent, Theory of Mind, and Implicit Communication
    • Fall 2023 & Spring 2023: Theory of Mind for HRI
  • 15-482: Autonomous Agents (CMU, Fall 2023)
    Guest Lecture – Topic: Basics of Machine Learning

  • MAE 2250: Mechanical Synthesis (Cornell University, Spring 2022)
    Guest Lectures – Topics: CNC Machines and Design for X
    • Used 3D-printed mechanical kits to teach gears, pulleys, and mechanical design through interactive exploration