Christopher
Lynn
Vudtiwat Ngampruetikorn
I am interested in understanding the complexities of human cognition and behavior across scales, from neurons and brain regions interacting to support cognition, to individual humans learning and representing complex systems in the world around them, to entire groups of humans communicating to generate collective behaviors. To uncover the mechanisms underlying human behavior, my research combines ideas from information theory, statistical mechanics, network science, and cognitive neuroscience.
My research aims to shed light on how biological systems and artificial neural networks learn. I use tools and concepts from statistical physics and information theory to study a wide range of problems: from understanding information processing in cells to designing physics-inspired deep learning techniques.
Daniel
Schubring
I am a high-energy theorist working with quantum and statistical field theories that straddle the border between condensed matter and high-energy physics. I am interested in a wide variety of topics in non-perturbative QFT, such as resurgence, integrability and integrability breaking, and all manner of topological defects.