$$ % Define your custom commands here \newcommand{\bmat}[1]{\begin{bmatrix}#1\end{bmatrix}} \newcommand{\E}{\mathbb{E}} \newcommand{\P}{\mathbb{P}} \newcommand{\S}{\mathbb{S}} \newcommand{\R}{\mathbb{R}} \newcommand{\S}{\mathbb{S}} \newcommand{\norm}[2]{\|{#1}\|_{{}_{#2}}} \newcommand{\pd}[2]{\frac{\partial #1}{\partial #2}} \newcommand{\pdd}[2]{\frac{\partial^2 #1}{\partial #2^2}} \newcommand{\vectornorm}[1]{\left|\left|#1\right|\right|} \newcommand{\abs}[1]{\left|{#1}\right|} \newcommand{\mbf}[1]{\mathbf{#1}} \newcommand{\mc}[1]{\mathcal{#1}} \newcommand{\bm}[1]{\boldsymbol{#1}} \newcommand{\nicefrac}[2]{{}^{#1}\!/_{\!#2}} \newcommand{\argmin}{\operatorname*{arg\,min}} \newcommand{\argmax}{\operatorname*{arg\,max}} \newcommand{\dd}{\operatorname{d}\!} $$

Teaching

Course notes and lecture slides in deep learning, system modeling and control, and systems architecture.

Explore course notes and lecture slides in learning, dynamics, control, and systems engineering.

Graduate courses

Deep Learning

From optimization and neural networks to generative models and reinforcement learning, with theory and computational examples.

14 notes · Interactive examples

Explore Deep Learning →

Undergraduate courses

System Modeling and Control

Model physical systems, analyze their responses, and design feedback controllers using classical and state-space methods.

16 slide decks · Chapters 2–17

Explore System Modeling and Control →

Systems Architecture

Explore complex systems, connect function to form, and reason about architectural decisions and tradeoffs.

18 slide decks · Complex systems and Chapters 1–16

Explore Systems Architecture →

Other courses taught

Graduate: Robotics; Optimization.

Undergraduate: Kinematics and Machine Dynamics; Mechatronics.

Materials for these courses will be made available as time constraints allow.