Teaching

Teaching has been an important part of my academic life. I have served as an instructor, teaching fellow, teaching associate, and teaching assistant for courses ranging from undergraduate to graduate levels, including accelerated proof-based courses for mathematics and statistics majors, general data science courses for non-STEM students, and management decision-making courses for business and engineering Master's and MBA students.

My teaching is guided by the belief that mathematics, statistics, and machine learning are best understood through their underlying structure, rather than as collections of isolated techniques. I aim to help students understand not only how to apply methods, but also why they work, when assumptions matter and how ideas are connected. Since students often enter a course with different levels of mathematical preparation, I try to present concepts at multiple levels, combining intuition, visual explanation, concrete examples, and rigorous reasoning.

I enjoy communicating with students, sharing knowledge, helping them work through questions, and guiding them through material they find challenging. From my own experience, learning mathematics and STEM more broadly is rewarding but often difficult; it requires practice, patience, and confidence built over time. In my labs, discussion sessions, and office hours, whether in person or virtual, I encourage active interaction. I try to make sure students feel comfortable asking questions or making comments, including those that are not yet fully formulated. Often, the process of articulating a blurry question is itself an important step toward understanding.

Beyond classroom teaching, I also value mentoring as a more individualized and research-oriented form of guidance. In working with students, I hope to help them identify their mathematical interests, build confidence with challenging material, and gradually develop independence. More broadly, my goal as a teacher and mentor is to help students develop mathematical judgment: the ability to recognize structure, reason carefully about assumptions, and apply rigorous ideas creatively to new problems.   

Mentor'd(-ing)

  • For Ph.D. students with background in mathematics, statistics, computer science, and information sciences: London Geometry and Machine Learning Summer School 2025, 2026.

  • For Undergraduate and Master's students: Institute of Pure and Applied Mathematics, summer 2025; UCLA Statistics Club, 2021-24.

Courses Instruct'd

  • Fall 2023: Prep Camp for Master in Applied Statistics and Data Science Program, lead instructor

  • Fall 2022: Prep Camp for Master in Applied Statistics Program, lead instructor

  • Fall 2021: Prep Camp for Master in Applied Statistics Program, joint with Dr. Sam Baugh

Courses TA'd

  • Fall 2023: ENGR 205 Model-Based Systems Engineering, with Dr. M. Hecht

  • Summer 2022: ENGR 116 Statistics for Management Decisions, with Dr. A. Mehrnia

  • Spring 2022: ENGR 202 Reliability, Maintainability & Supportability, with Dr. M. Hecht

  • Winter 2022: ENGR 200 Engineering Management, with Prof. L. Lackman and Dr. J. Chanceteac

  • Fall 2021: ENGR 205 Model-Based Systems Engineering, with Dr. M. Hecht

  • Summer 2021: STATS 13 Intro to Statistical Methods for Life & Health Sciences, with Dr. G. Wu

  • Spring 2021: ENGR 202 Reliability, Maintainability & Supportability, with Dr. M. Hecht

  • Winter 2021: ENGR 200 Engineering Management, with Prof. L. Lackman and Prof. V. Mangal

  • Fall 2020: ENGR 205 Model-Based Systems Engineering, with Dr. M. Hecht

  • Summer 2020: ENGR 116 Statistics for Management Decisions, with Prof. L. Dolecek and Prof. H. Mamani

  • Spring 2020: ENGR 202 Reliability, Maintainability & Supportability, with Dr. M. Hecht

  • Winter 2020: ENGR 200 Engineering Management, with Prof. L. Lackman and Dr. V. Mangal

Reviews from instruction program reports

  • I appreciate the responsiveness and willingness to help students over email. Thank you very much!

  • Jiayi was an amazing TA, she would always be available for office hours and would help answer any questions students may have. Very knowledgeable

  • Jiayi was an excellent TA who cared about students. Her response was fast and precise. She was one of the best TAs I have ever had.

  • TA is super nice, very knowledgeable and very helpful in homework and big case projects.

  • She was a great TA that responded quick to emails and questions with thorough responses.

  • "Jiayi was a great TA that made sure that her students had time to go over the homework and the coding that was required of them. She also took time out of her time to stay after class to help us figure out our errors and other questions when there was not enough time in class, which was appreciated.

  • “I enjoyed this Ta, she was really knowledgeable and nice!”

  • “Jiayi was an overall great TA. She was very patient and thorough with her explanations. She was also very good at breaking down the labs, which made them less daunting.”

  • “She explained the concepts very well and made the labs very easy to understand. She was also very approachable and patient, I felt comfortable asking her for help/ additional explanation. She also integrated office hours when students asked which were very helpful for trouble shooting labs and double checking difficult homework problems. Overall great TA.”

  • “TA Li was hands down one of the best TAs I've ever had. I was nervous about the class at the beginning because of the coding labs, but she was really helpful and the coding turned out to be somewhat easier than I expected. She was really helpful in explaining any homework problems and it was clear that she knew exactly how to answer any confusion or mistakes in both labs and homework assignments.”

  • “This TA was very helpful with both labs and homework during our discussion sections.”

  • “Jiayi was an amazing TA, as she was very thorough in clarifying questions of students. She allowed students to share their screens on Zoom when they ran into an error and walked them through the process of fixing it, which was helpful because it taught us how to debug our own code…”

  • "Jiayi was very knowledgeable of the course material and always willing to help when I was confused. I’m addition, she was easy to approach and I commend for instructing a zoom class with so little engagement from students cause their cameras were off.

  • “This TA is very kind and concerned with student learning. She moved slow enough so that everyone could follow along.”

  • “This teaching assistant was amazing as they always explained lecture and lab material in a very clear manner that was easy to understand and the teaching assistant was always eager to help the students. This teaching assistant really had no real weaknesses in this course.”