I am a neuroscientist in the Center for Cognition and Sociality at the Institute for Basic Science, South Korea.
I am interested in how physical building blocks of neural systems work together, broadly speaking. The main focus of my research is uncovering how biophysical mechanisms in neurons and neural networks determine their functions. A neural system typically has a vast repertoire of those interacting with each other. Such complexity somehow enables the whole system to perform information processing in specific yet adaptive ways. This phenomenon raises many questions, such as how we can characterize computations by neural systems, how we can uncover what cellular mechanisms are responsible, etc.
To address those issues, I extensively use computational modeling, a powerful tool that allows us to explore systems often far beyond the regime accessible to available experiments, thereby efficiently generating experimentally testable hypotheses. While building those models based on experimental data is rarely a simple task, ideas from statistical learning theory have proven useful for overcoming difficulties in model building. I have endeavored to bring together the approaches to this whole range of problems and contribute to our understanding of the physical basis of neural information processing.
To find out more, please check out the full list of publications.
I have developed the following computer models and data analysis packages:
I have been teaching how to build computational models of neural systems. Here are some materials and codes for the classes