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OKUBO Fumiya, Ph.D. / Associate Professor

Division of Physical and Analytical Chemistry

Department of Pharmaceutical Sciences

Research Topics

1. Computation Capability of Biochemical Reactions

2. Educational Data Mining

Our research interests are focused on theoretical computer science, such as automata theory and computation theory. In particular, we are studying a theory on natural computing theory to explore the information processing mechanisms in natural phenomena, and we are exploring chemical reaction automata, which are computational models in chemical reaction systems.
We also conduct a research in the field of educational data mining. Our contributions include a visualization of students’ learning activities and prediction of students’ performances applying machine learning.

Representative Publications

1. Okubo F., Yokomori T., Decomposition and factorization of chemical reaction transducers, Theoretical Computer Science, 777, 431–442 (2019).

2. Okubo F., Yamada M., Oi M., Shimada A., Taniguchi Y., Konomi S., Learning Support Systems Based on Cohesive Learning Analytics, in "Emerging Trends in Learning Analytics: Leveraging the Power of Education Data" (ed. Myint Swe Khine), Brill Publisher, Netherlands, 223–248 (2019).

3. Okubo F., Yokomori T., The computational capability of chemical reaction automata, Natural Computing, 15(2), 215–224 (2016).

4. Okubo F., Kobayashi S., Yokomori T., Reaction automata, Theoretical Computer Science, 429, 247–257 (2012).

5. Okubo F., A note on the descriptional complexity of semi-conditional grammars, Information Processing Letters, 110(1), 36–40 (2009).