Faculty and Research Units OIST research units take a cross-disciplinary approach to research, and the PhD program encourages students to explore the intersections of disparate fields of science and technology. Find the research unit of your interest below. Faculty and Research Units Discover Research Specialties Browse research disciplines and specialities. Discover more Find a Faculty Member or Research Unit Research Unit | Faculty Member Biology Chemistry (-) Computer Science Ecology and Evolution Engineering and Applied Sciences Marine Sciences Mathematics Neuroscience Physics Facet Research Discipline Artificial intelligence Bioinformatics Computer sciences Cyber Security (-) Deep learning Informatics Machine learning Theoretical sciences Facet Specialty Clear filters Machine Learning and Data Science Unit In the machine learning and data science (MLDS) unit, we focus on developing fundamental machine learning algorithms and solving important scientific problems using machine learning. We are currently interested in statistical modeling for high-dimensional data including kernel and deep learning models and geometric machine learning algorithms, including graph neural networks (GNN) and optimal transport problems. In addition to developing ML models, we focus on developing new machine learning methods to automatically find a new scientific discoveries from data. Makoto Yamada Associate Professor Neural Computation Unit The Neural Computation Unit develops algorithms that elucidate the brain’s mechanisms for robust and flexible learning. The unit focuses on how the brain processes reinforcement learning, in... Kenji Doya Professor Quantum Machines Unit We study in theory and experiments the engineering of quantum devices built from different subsystems that can collectively perform beyond the individual capabilities of their parts. Jason Twamley Professor Annual Reports A yearly report from each research unit Visit the page
Machine Learning and Data Science Unit In the machine learning and data science (MLDS) unit, we focus on developing fundamental machine learning algorithms and solving important scientific problems using machine learning. We are currently interested in statistical modeling for high-dimensional data including kernel and deep learning models and geometric machine learning algorithms, including graph neural networks (GNN) and optimal transport problems. In addition to developing ML models, we focus on developing new machine learning methods to automatically find a new scientific discoveries from data. Makoto Yamada Associate Professor
Neural Computation Unit The Neural Computation Unit develops algorithms that elucidate the brain’s mechanisms for robust and flexible learning. The unit focuses on how the brain processes reinforcement learning, in... Kenji Doya Professor
Quantum Machines Unit We study in theory and experiments the engineering of quantum devices built from different subsystems that can collectively perform beyond the individual capabilities of their parts. Jason Twamley Professor