Network Science Laboratory
Network science is a research field about real-world interaction structures, beyond the realm of conventionally treated completely regular or random interactions in traditional statistical physics. Examples encompass numerous types of networks, e.g., power grids, the Internet, social networking services, ecosystems, metabolism and genetic interactions in biological systems. The brain, dubbed as ‘the most complicated system in the universe known to itself,’ is also a network composed of a vast number of neurons. Artificial neural networks, which are widely adopted in machine learning, learn things by simulating signal transmission in the brain. We investigate fundamental problems such as hidden structural properties lurking in networks and dynamical processes on networks for a more comprehensive understanding of networked systems. On the application side, for instance, we try to shed light on more efficient machine learning by systematic approaches to neural network structures based on a variety of tools developed in network science.
- Professor : Sang Hoon Lee
- Subject : network science, machine learning, statistical physics
- Web site : https://sites.google.com/view/netscilab/
