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 Model-Based Evolutionary Genomics Unit The Model-Based Evolutionary Genomics Unit works at the crossroads of computational and evolutionary biology. Our long-term goal is to achieve an integrative understanding of the evolution of Life on Earth and the origins and emergence of complexity across different biological scales, from individual proteins to ecosystems. To move towards this goal, we develop and apply model-driven evolutionary genomics methods to reconstruct the Tree of Life and the major evolutionary transitions that have occurred along its branches. Gergely János Szöllősi 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 Physics and Biology Unit The unit studies natural time series data, from NLP to genome sequences to cephalopod camouflage, with dynamical systems and machine learning methods, letting the data lead the way. Jonathan Miller 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 Sensory and Behavioural Neuroscience Unit We investigate how behavioural contexts tune olfactory information processing in the mouse brain. Methods used include neurophysiology, imaging, circuit analysis, behaviour. Izumi Fukunaga Associate Professor Theory of Quantum Matter Unit The Theory of Quantum Matter (TQM) Unit carries out research into a wide range of problems in condensed matter and statistical physics. Nic Shannon 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
Model-Based Evolutionary Genomics Unit The Model-Based Evolutionary Genomics Unit works at the crossroads of computational and evolutionary biology. Our long-term goal is to achieve an integrative understanding of the evolution of Life on Earth and the origins and emergence of complexity across different biological scales, from individual proteins to ecosystems. To move towards this goal, we develop and apply model-driven evolutionary genomics methods to reconstruct the Tree of Life and the major evolutionary transitions that have occurred along its branches. Gergely János Szöllősi 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
Physics and Biology Unit The unit studies natural time series data, from NLP to genome sequences to cephalopod camouflage, with dynamical systems and machine learning methods, letting the data lead the way. Jonathan Miller 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
Sensory and Behavioural Neuroscience Unit We investigate how behavioural contexts tune olfactory information processing in the mouse brain. Methods used include neurophysiology, imaging, circuit analysis, behaviour. Izumi Fukunaga Associate Professor
Theory of Quantum Matter Unit The Theory of Quantum Matter (TQM) Unit carries out research into a wide range of problems in condensed matter and statistical physics. Nic Shannon Professor