Lab 6. Ryohei Hisano
Mathematics and Informatics Center, Graduate School of Information Science and Technology, The University of Tokyo
Room 214B, Engineering Bldg. 12, 2-5-37, Ikenohata, Taito-ku, Tokyo 110-0008
|March 2007||Bachelor degree from Department of Economics, Keio University|
|March 2010||Master’s degree from Graduate School of Economics, Hitotsubashi University|
|August 2013||D-MTEC (Dr. Sc. ETH Zürich) from ETH Zürich||Sept. 2013||Postdoctoral researcher, ETH Zürich, D-MTEC||Oct. 2013||Postdoctoral researcher, The National Institute of Informatics|
|April 2014||JSPS Research Fellow, Graduate School of Economics, The University of Tokyo|
|December 2015||Specially Appointed Research Associate, Graduate School of Information Science and Technology, The University of Tokyo|
|April 2020||Lecturer, Mathematics and Informatics Center, Graduate School of Information Science and Technology, The University of Tokyo|
My research interests lie in both empirical research and statistical model building of social and economic big data. On the empirical research side, my research has mainly focused on analyzing datasets primarily in finance and macroeconomics domain (financial markets, blockchain, news text, financial statements, firm networks, sales of products), but this does not mean that I am solely interested in economics. For the statistical modeling side, my focus is on developing models that take into account various characteristics and empirical regularities found in the economy and utilizing information from multiple sources in the form of a heterogeneous information network. For the latter model building research, I mainly develop network mining (simple, temporal, heterogeneous information network) and text mining methods. By combining the two research topics, my goal is to model complex issues in society (e.g., propagation and mitigation of shocks, hidden industrial block structure, aggregate fluctuation, matching among firms, network formation, bubbles, crashes, financial statements, systemic risks, the velocity of money, news events and reliability of information) to not only contribute to academic research but better understand risks and accelerate evidence-based policymaking.
- Ryohei Hisano, Didier Sornette, Takayuki Mizuno , “Prediction of ESG compliance using a heterogeneous information network”, Journal of Big Data 7, 22, 2020.
- Ryohei Hisano, “Learning Topic Models by Neighborhood Aggregation”, IJCAI 2019, Macao, China, Aug 10 -16, 2019.
- Ryohei Hisano, “Semi-supervised Graph Embedding Approach to Dynamic Link Prediction”, Complenet 2018, Northeastern University, Boston, Match 4-8, 2018. In: Sean Cornelius, Kate Coronges, Bruno Gonçalves, Roberta Sinatra, Alessandro Vespignani (Eds.), Complex Networks IX. Springer Proceedings in Complexity, page 109-121, 2018.
- Ryohei Hisano, Tsutomu Watanabe, Takayuki Mizuno, Takaaki Ohnishi, Didier Sornette, “The gradual evolution of buyer-seller networks and their role in aggregate fluctuations”, Applied Network Science, Vol 2, 9, 2017.
- Ryohei Hisano, “A new approach to building the interindustry input-output table using block estimation techniques”, 2016 IEEE International Conference on Big Data (Big Data), Workshop Application of Big Data for Computational Social Science, 5-8 Dec. 2016.