Born in Ajara Vetho, Badagry, Lagos State, Nigeria. Obtained BTech (2010) & MTech (2014) Industrial Mathematics from the Federal University of Technology, Akure (FUTA), Ondo State, Nigeria as well as PhD (2020) Mathematical Biology from Tohoku University. Emerged as the Valedictorian, Fall 2020 Commencement Ceremony, Graduate School of Information Sciences (GSIS), Tohoku University. Awarded the Japanese Government MEXT Postgraduate Scholarship (April 2017-September 2020). Loves seeing the math in everything and exploring the latest technologies to optimize productivity.
助教 DANSU EMMANUEL JESUYON
キャンパス | 青葉山 キャンパス |
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所属研究室 |
統合生態
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連絡先 | 022-795-6696 |
dansu.emmanuel.jesuyon.a2@tohoku.ac.jp | |
ホームページ | https://www.linkedin.com/in/emmanuel-jesuyon-dansu-80937b5b/ |
経歴 |
Jun 2023 to Present - Assistant Professor, Graduate School of Life Sciences, Tohoku University, Sendai, Japan
Dec 2022 to May 2023 - Postdoctoral Researcher, Graduate School of Life Sciences, Tohoku University, Sendai, Japan Oct 2020 to Nov 2022 - Lecturer, Federal University of Technology, Akure, Ondo State, Nigeria Apr 2017 to Sep 2020 - Doctoral Researcher, Graduate School of Information Sciences, Tohoku University, Sendai, Japan Dec 2014 to Mar 2017 - Assistant Lecturer, Federal University of Technology, Akure, Ondo State, Nigeria Apr 2012 to Dec 2014 - Graduate Assistant, Federal University of Technology, Akure, Ondo State, Nigeria |
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著書・論文 |
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所属学会 |
Black in Mathematics Association (BMA), South Africa
European Mathematical Society (EMS), Finland Japanese Society for Mathematical Biology (JSMB), Japan Nigerian Mathematical Society (NMS), Nigeria Sigma Xi, The Scientific Research Honor Society, USA Society for Mathematical Biology (SMB), USA |
担当講義 |
Mathematics in the Life Sciences
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最近の研究について
My enduring interest lies in mathematical modeling of population dynamics, spanning ecological, epidemiological, and social systems. Lately, I have been exploring the synergy of data science and machine learning with these domains, aiming to harness their potential to enhance our understanding of complex interactions and patterns within these systems.