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

Teaching

Course notes and lecture slides in deep learning, kinematics and machine dynamics, 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

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Undergraduate courses

Kinematics and Machine Dynamics

Analyze the motion of interconnected rigid bodies and the forces that drive machines, from linkages to gears and cams.

13 slide decks · Mechanisms, kinematics, dynamics, gears, and cams

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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

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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

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Other courses taught

Graduate: Robotics; Optimization.

Undergraduate: Mechatronics.

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