Teaching
MAE 207: Safety for Autonomous Systems
Guest Lectures
Jason Choi (UC Berkeley) -- Introduction to Control Lyapunov Functions and Control Barrier Functions
Zachary Sunberg (CU Boulder) - Safety and Efficiency through POMDP Planning
Shreyas Kousik (Georgia Tech) - Reachability-based Trajectory Design (RTD)
Somil Bansal (USC) - DeepReach: Learning for High-Dimensional Reachability Problems
Lukas Hewing (ETH Zurich) - Model Predictive Control and Predictive Safety Filters
Robert Hawkins (UCSD) - Cognitive Models of Decision-Making in Social Contexts
Jame Fernandez-Fisac (Princeton) -- Safe Human-Centered Robotics
Felix Berkenkamp (Bosch) - Exploration and Safety in Model-Based Reinforcement Learning
Angela Schoellig (Toronto) - Safe Learning
Nikolay Atanasov (UCSD) - Control Barrier Functions
Karen Leung (UW) - Safe Learning & Formal Methods
Marcelo Mattar (NYU) - Cognitive Models of Human Decision-Making
Alonso Marco (Berkeley) - Safe Bayesian Optimization
Stanley Bak (Stonybrook) - Zonotope-based reachability
Changliu Liu (CMU) - Safe Human-Robot Interaction
Steven Brunton (UW) - Data-driven modeling
EECS 127: Optimization Models in Engineering
Mixed Undergrad/Graduate Course, Spring 2019, UC Berkeley
I acted as the head Graduate Student Instructor (GSI) with a team of 6 other TAs and 2 professors teaching a convex optimization course to 200+ graduate students and undergraduate students. My duties were to ensure the smooth operation of the lectures, discussion sections, office hours, exams, grading through Gradescope, and email/piazza. Additionally, I taught two 1-hour discussion sections on the fundamentals of convex optimization, as well as guest lecturing to the entire class when the professors were traveling. My average rating from student course evaluations was a 4.86/5; official evaluations are here.
Example Lecture: Linear Programs
Below is a video recording of a guest lecture I gave on linear programs. My notes can be accessed here and the slides that I used for visualizations are here.
Anonymous Student Quotes:
“I really like how she summarizes the concepts in the beginning of the session. I really learned a lot from the lectures she gave. I also like how she shares her interpretation on certain concepts (ex the relationship of nullspace and column space). That really helps me a lot. Thank you very much.”
“I love Sylvia’s teaching style and her use of graphs and drawings to illustrate concepts and solve problems. She is also very friendly and genuinely care about the students. Best GSI I have ever had.”
“She is very good at explaining the concepts in a very easy-to-understand, approachable method. I think her discussion time helps tremendously.”
Very friendly/approachable, not afraid to ask if something is wrong”
“Provides very good intuition and visualization of the problems”
EE 221A: Linear Systems
Graduate Course, Fall 2017, UC Berkeley
The Linear Systems Theory course is one of the common introductory courses for new graduate students, high-achieving undergraduates, and graduate students who are exploring new fields. This diverse range of backgrounds makes the course a fun challenge to teach. As GSI I ran weekly 2-hour discussion sections where I strived to balance enforcing fundamentals while introducing advanced concepts and relevant applications. I additionally graded assignments, held frequent office hours, and developed problems. The students in this course nominated me for the UC Berkeley Outstanding Graduate Student Instructor Award, which I won in May 2018. This is awarded to up to 9% of current GSIs university-wide.
Anonymous Student Quotes:
“Sylvia was one of the best GSI's I have had thus far. It was obvious she spent a lot of time preparing the material and worksheets for discussion sections and was extremely helpful and accessible during office hours. She really helped me understand the material a lot better.”
“Sylvia is very approachable and prepared. Her discussion worksheets are very useful in highlighting what techniques are considered important in the course, and I have loved the inclusion of past qualifying exam questions. I think she truly tries to come up with new resources for students (e.g. her flow charts and diagrams in discussion are great).”
“Sylvia is a great GSI. She really cares that students are actually learning and always tries to answer everything, and discuss with the professor in case a question is outside the scope of the course.”
“GSI is amazing, has and provides tons of resources to learn the material”
“Sylvia was great! Always helpful and very willing to go over the material.” Sylvia was a great GSI! She was always extremely friendly and welcoming towards all our questions, and also very helpful outside of class.
MEM 435: Computer Aided Engineering Design
Undergraduate Course, Fall 2013
I was a TA for a course wherein 33 students were tasked with designing biologically-inspired apparatuses for use in high school physics labs. This required course for mechanical engineering undergrads required students to develop computer-aided design skills, understand design principles and fabrication techniques, and improve presentation skills. My duties were to teach a 3-hour discussion and lab section, as well as to meet with groups regularly to develop their design pitches and to introduce them to fabrication methods in the machine shop. My rating from student course evaluations was 4.8/5.
Anonymous Student Quotes:
“[I] never had a TA who genuinely cared about us learning and succeeding so much.”
“She rocks, best TA ever. [She is] down to earth and straight to the point with everything.”
“Sylvia >> all other TA's. It’s such a relief when you have a TA who actually gives a s***”