Teaching

My interactions with those I considered great teachers and professors have led me to inherently develop a few teaching principles:

1. Good mentors have regular, meaningful interaction with their students.
2. Be adaptable to particular students’ needs/difficulties.
3. Demonstrate enthusiasm that goes beyond the classroom.
4. Maintain a working knowledge of advances in the field.

I enjoy teaching others and learning from others, whether they are peers and colleagues or they are students in classes where I act as teaching assistant. Over my time in undergraduate and graduate studies, I’ve had many opportunities to be in a teaching position. Each of these are listed below.

Current Teaching and Mentoring Roles

• High School Mentorship through JSHS platforms (since Oct 2023)
  • As of March 2025, I am mentoring three high school students across various topics that range from AI applied to segmentation in medical imaging and time-series classification.

Experience

• Junior Science and Humanities Symposium
  • Mentor (virtual): Mar - Dec 2023
    • Helped a student in Pennsylvania prepare for the ISEF 2023 competition, a DECA competition, and various college applications.
    • They were accepted to UPenn and MIT’s programs.
• Supervised Teaching, UF
  • Fundamentals of Machine Learning: Spring 2024
• Teaching Assistant, UF
  • Fundamentals of Machine Learning: Fall 2024
  • Applied ML Systems: Fall 2023
  • Machine Learning for Time Series: Spring 2021
  • Neural Networks & Deep Learning: Fall 2021
• Graduate Teaching Associate, Cal Poly SLO
  • Electric Circuits II Lab: Spring 2019
  • Microelectronics Lab: Winter 2019
  • Introduction to EE Lab: Fall 2018
• Teaching Assistant, Cal Poly SLO
  • Microprocessors: Spring 2018 and Fall 2017
  • Statistics for Engineers: Fall 2016
  • Digital Design: Spring 2015, Fall 2015, and Winter 2016