EN.560.652 Scientific Machine Learning for Modeling, Optimization, and Control of Dynamical Systems

Nothing rests; everything moves; everything vibrates.

— Three Initiates, Kybalion

Instructor

Ján Drgoňa
Associate Professor
Department of Civil and Systems Engineering
Ralph S. O’Connor Sustainable Energy Institute (ROSEI)
Department of Electrical and Computer Engineering (secondary appointment)
Data Science and AI Institute (DSAI) (affiliate member)
Johns Hopkins University (JHU)

Overview

This repository contains weekly lecture material and code examples for the SciML course.

• Week 1: Introduction to SciML
• Week 2: Differentiable programming fundamentals
• Week 3: Physics-Informed Neural Networks
• Week 4: Neural Ordinary Differential Equations
• Week 5: Learning to Optimize
• Week 6: Optimal control fundamentals
• Week 7: Learning to Control
• Week 8: Neural Differential Equations with Constraints
• Week 9: Differentiable optimization
• Week 10: Feasibility layers

Environment Installation

Option 1: Conda

conda create -n sciml-course python=3.13 -y
conda activate sciml-course
python -m pip install -r requirements.txt

Option 2: venv

python3 -m venv .venv
source .venv/bin/activate
python -m pip install -r requirements.txt

Option 3: Active environment

python -m pip install -r requirements.txt