Teaching & Mentoring
Guest Lecturer | Thesis Supervisor | Research Mentor | Teaching Assistant
My Teaching Philosophy
Advanced personalized learning was listed at the top of the fourteen Grand Challenges in the 21st century by the National Academy of Engineering. The scientific reason behind it is that learning styles, speeds, and interests all vary from individual to individual. This challenge is particularly significant for engineering – students are trained to define a problem from a real-world observation, identify the underlying physics, simplify and solve the problem, and explain the observation using the solution (DISSE for short) – each of these actions can be performed in numerous correct ways which will depend on student preference and personality. Therefore, the core of my teaching philosophy is student-oriented instruction to realize personalized learning. I will use three pillars to support this core.
Being student-centered does not necessarily mean marginalizing the instructor, because students and the instructor can mutually inspire each other. I believe that the deepest learning of a subject is to teach it. Looking at the history of engineering, most of the successful researchers are, above all, excellent teachers – Stephen Timoshenko, Theodore von Karman, Ascher H. Shapiro, to name a few. It is my goal to follow these giants.
Teaching & mentoring Experiences
Course: 2.081J Plates and Shells (Graduate-level), 2020 Spring
Guest Lecture on "Advanced Topics on Plate Buckling"
LT Chris Reynolds. “Generating a large experimental databank of the coupled electrochemical and mechanical effects of Li-ion cells for potential data-driven prognostic application.” Expected in 2021
Tobias Sedlatschek. “Characterization of the plasticity and fracture behavior of lithium under various stress states with particular emphasis on its microstructural evolution.” 2020
Marco Miguel Koch. “Testing and modeling the mechanical behavior of lithium-ion pouch cells under in-plane compression.” 2019
Zachery W Kutschke. “Modeling the internal short circuit of lithium-ion battery cells with physics-informed neural network algorithms.” 2020
Three visiting PhD students
Zhexin Pan, Tsinghua University, 2019-2020
Wei Li, Tsinghua University, 2017-2018
Hailing Luo, 2017-2018
Two Master students
LT Nathaniel J. Byrd, Course 2N Master student @ MIT, 2017-2018
Zihao Qin, Master student, Tsinghua University, 2014-2017
One undergraduate student
Rui Luo, Summer Intern @ MIT, 2018
Massive Open Online Course (MOOC): Fundamentals of Automotive Crash Safety, 2015 Spring
Role: Captioning lecture videos
Course: Impact Dynamics, 2013 Fall