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Networks and Brain Networks

Covers the basics of networks, focusing on brain networks, historical breakthroughs, small-world and scale-free network discoveries, and the importance of the human connectome.

Networks: Structure and Properties

Explores the structure and properties of networks, including dating and protein networks, small-world effect, hubs, and scale-free property.

Introduction to Networks and Brain Networks

Introduces the fundamentals of network science, focusing on brain networks and their historical breakthroughs.

Graph Coloring: Theory and Applications

Explores graph coloring theory, spectral clustering, community detection, and network structures.

Statistical analysis of network data

Covers stochastic properties, network structures, models, statistics, centrality measures, and sampling methods in network data analysis.

Social and Information Networks: Structure

Explores the structure of social and information networks, focusing on giant components, clustering, tie formation, and network connectivity.

Graph Machine Learning

Delves into graph-enhanced machine learning, focusing on fraud detection, malware detection, and recommendation systems.

Introduction to Networked Control Systems

Covers classic feedback control, modeling implications, challenges, and opportunities in Networked Control Systems.

General Physics: Quantum - Part 1

Covers combined interference, diffraction, network properties, and resolving power in networks.

General Physics: Quantum - Resolving Power and Diffraction Gratings

Covers the resolving power of networks and properties of diffraction gratings.