Teaching
I am the teaching assistant of 2 courses at Stanford CEE and I enjoy mentoring and supporting students from both undergraduate and graduate programs. The details of my teaching responsibilities are summarized below.
This course introduces practical applications of data analytics and machine learning from understanding sensor data to extracting information and decision making in the context of sensed physical systems. In this course, students work with real-world data to learn about challenges in analyzing data, applications of statistical analysis and machine learning techniques using MATLAB, and limitations of the outcomes in domain-specific contexts. Topics include data visualization, noise cleansing, frequency domain analysis, forward and inverse modeling, feature extraction, machine learning, and error analysis.
Assignments Design and Grading
I prepared 4 MATLAB programming assignments for the entire course and designed a rubric for consistent grading. With feedback from the students, the assignments are improving year by year.
Sessions and Office Hours
I held 2 office hours weekly and instructed coding and reviewing sessions for students to prepare for assignments and projects.
Project Mentoring
I mentored all student groups for their projects. I met with them bi-weekly and provided timely and specific suggestions for their proposals, presentations, and final reports.
Introduction to structural monitoring systems that enable us to understand the states of structures and excitations. Theoretical background on linear time-invariant systems, time-series modeling, frequency analysis, and features extractions in the context of structural systems. Damage diagnosis algorithms and excitation characterization using both physics- and data-based methods for civil structures. Emphasis on the underlying physical interpretations and their practical usage.
Project Design and Mentoring
I designed 4-6 research projects for each different year of this course according to the state-of-the-art trend in my field. Each year I mentored 5-10 students in these open-ended projects in areas that include but are not limited to: research problem formulation, research challenge identification, literature review, data collection and analysis, paper writing, and presentation skills.
Sessions and Office Hours
I held 2 office hours weekly and led special sessions for students to prepare for assignments and projects.
Assignment Improvement and Grading
I improved 4 research-oriented assignments for the entire course over the years and designed a rubric for consistent grading.