Interview: Prof. Tohsato from Ritsumeikan University
Original Language: Japanese | 日本語はこちら
We interviewed Prof. Yukako Tohsato from Ritsumeikan University, who has been using Kiara for long now.
About Prof. Yukako Tohsato
Prof. Tohsato’s research focuses on the development of information processing technologies to understand and predict biological phenomena as systems. As a science-phobic author, I can briefly explain that she is a great professor working in an advanced biotechnology laboratory!
What problems were you experiencing before Kiara?
As we have a partnership with a Chinese university, international students who have learnt a little Japanese are regularly assigned to our laboratory, but I felt that it was difficult to make intuitive decisions when sharing information in Japanese, and that the content was not sufficiently communicated.
How exactly does Kiara solve this?
Kiara is very helpful for us to be able to convert our announcements in Japanese into Chinese immediately. The international students also feel more comfortable using Slack than talking orally, which I think is thanks to Kiara’s features.
If you were to recommend Kiara to a friend, who would be the right team?
I think it is suitable for Japanese universities because they accept a certain number of international students, especially from Asia. English can be managed at school level, but I think it is an essential tool for a mixed team including people whose mother tongue is not learned as a language.
Thank you very much, Prof. Tohsato!
You can find the summary of Prof. Tohsato’s research in the following.
■Research summary
Computational Analysis and Modeling for Biological Dynamics Data.Recent advances of measuring and manipulating technologies in life sciences are generating biological experimental data including spatiotemporal dynamics within and between molecules, cells, tissues and entire organisms. Computational approaches for such large-scale multi-dimensional data have the potential to improve our understanding of biological phenomena such as development, aging and disease causation – toward a data-driven science. We are therefore pursuing research and development of algorithms, methods, and software tools that will enable comprehensive interpretation of such data; for example, image processing and data analysis methods using statistics, machine learning, and artificial intelligence techniques, and mathematical modeling methods based on physical and chemical laws. Our aim is to understand biological phenomena and to predict how it will be regulated under various perturbations.
■Present specialized field
Statistical Science, Software, Biological/Living Body Informatics, Biofunction/Bioprocess (Keyword：Computational Biology, Bioinfomatics, Bioimageinformatics, Systems Biology, Data Science)*This is excerpt from Ritsumeikan University Researcher Database
