
【Awards and Commendations】Naoki Kosuge, a graduated student of Dept. of Systems Innovation in March 2022 won “OCDI Takeuchi Yoshio Logistics Award” at the 9th International Conference on Transportation and Logistics (TLOG 2022).

Awards and Commendations
On 05/07/2022, Masanori HIRANO (D2, Izumi lab), Department of Systems Innovation, received Best Paper Award in IIAI International Congress on Advanced Applied Informatics 2022
〈Name of award and short explanation about the award〉
Best Paper Award in IIAI International Congress on Advanced Applied Informatics 2022
https://iaiai.org/conference/aai2022/
〈About awarded research〉
Title:
Analysis of Demand Response Scenarios by Industrial Consumers Using
Artificial Electric Power Market Simulations
Introduction:
In this study, we focused on the actual electricity usage in a Japanese factory and analyzed the effect of demand response.
Demand response is not only a solution for tight supply-demand balance but also beneficial for CO2 and cost reduction.
Therefore, we utilized multi-agent simulations for this analysis and get some suggestions for applying demand response for the real electricity usages.
〈Your impression & future plan〉
I want to thank Mr. Wakasugi, one of the co-author, for his great contribution to this paper. I couldn’t get this award without his contribution. Moreover, I’ll keep doing my best.
【Awards and Commendations】On 22/6/2022, Yukio Ohsawa, Professor, Department of Systems Innovation, won the JSAI Achievement Award at The Japanese Society on Artificial Intelligence.
〈Name of award and short explanation about the award〉
The Japanese Society for Artificial Intelligence (JSAI) awards the JSAI Achievement Award to individuals who have made significant achievements in the science of artificial intelligence or its applications, and to encourage the further development of science and its applications. The award is presented to individuals who are members of the society. The selection method is based on nominations by regular members, officers, etc., and the selection committee (consisting of one chairperson: a predecessor vice president, two secretaries: a director in charge of general affairs, and 21 committee members in total this time) selects the recipients. The criteria for awarding are academic achievements in the field of artificial intelligence or its applications, their contributions and ripple effects, with particular emphasis on originality and usefulness.
This year, just one recipient was selected following this process strictly. The award ceremony was held on June 22 (after the General Meeting of Members), and the recipient was presented with a certificate and a commemorative medal. This is the second recipient of the award at the University of Tokyo and the first in the field of engineering.
〈About awarded research〉
Yukio Ohsawa has focused on the interaction between data owners (experts of the target domain) and data analysts (data scientists) in data analysis and has pursued the essence of the process. First, in 1998, he presented the KeyGraph algorithm and applied it to data on earthquakes, business, medicine, etc. He reported that not only the network of co-occurrence but also the peripheral domains extracted from the graph structure by this method induce innovation by experts. This process of discovery came to be named the “chance discovery process” and he further proposed and implemented various concepts in data science. By then deepening the discussion, he found that data analysis itself is an interactive process where data scientists and domain experts join to refine knowledge and value, via the interaction between knowledge and data where data are designed based on the discovery of latent structures of experts’ knowledge on visualized latent structures of available data.
In 2013, Ohsawa proposed a process, Innovators’ Marketplace on Data Jacket (IMDJ), on which various technologies came to be developed to promote innovation creation by experts. He also extended IMDJ to a multilayered information space where not only single fields but also heterogeneous data are distributed, and is currently conducting an R&D to explain the interactions among data in a creative data marketplace consisting of larger heterogeneous data networks. The methodology in IMDJ was applied not only to business domains, but also to the Cabinet Secretariat’s COVID-19 project on epidemic forecasting, where he discovered
the principle that the distribution of people, especially “contact with unknown people” is essential information i.e., Stay with Your Community published in 2020. With this achievement, we are now able to make useful recommendations to policy makers about recommendable social life style of people.
In summary, Ohsawa has not only pursued the essence of data-driven innovation and developed various algorithms, but has also applied them to various areas and obtained significantly new and useful results. His consistent research results on the essence of data analysis over a quarter of a century deserve the Achievement Award of the Japanese Society for Artificial Intelligence.
〈Your impression & future plan〉
I am truly honored to be the first recipient of this award since 2016 in this academic society, and the second at our university since Dr. Junichi Tsujii of this university, who received the award in 2007. Artificial Intelligence is not synonymous with machine learning, but is a much larger field, and I believe that Japanese artificial intelligence studies are the best in the world in terms of development and fascination to pursue the dream and essence of this vast field. It is a great honor for me to have been chosen over my seniors, contemporaries, and younger colleagues in the field of artificial intelligence.
I would like to continue to share with you the content and direction of development of our research, as simply accepting the award is too limited to benefit human society, which is essentially what engineering is pursuing. I am deeply grateful to the Dean of the Graduate School of Engineering and various other people for their congratulatory speeches at the commemorative lecture by the DFIL Social Cooperation Chair. We hope to continue to contribute to the development of engineering and 3D collaboration (industry-government-academia X international X interdisciplinary) to foster knowledge systems.
【Awards and Commendations】
On 21/5/2022, Teruaki Hayashi, Ohsawa-Hayashi Lab., Department of Systems Innovation, received Funai Information Technology Award for Young Researchers.
〈Name of award and short explanation about the award〉
Funai Information Technology Award for Young Researchers
https://funaifoundation.jp/grantees/young_awardees_up_to_now_21.html
〈About awarded research〉
This award is given to young researchers who have made outstanding research achievements in a wide range of science and engineering fields, particularly in the fields of information science and technology.
〈Your impression & future plan〉
I am very honored to receive this award. Data constitute the very human activities of observing, recording, and communicating with the world. I believe that elucidation of the mechanisms behind how our society works with data and its associated technological development will substantially contribute to the coming data-driven society. In the future, I intend to further focus on creating research communities in Japan and overseas to disseminate the appeal of this field of research.
On 05/25/2022, Qian Gao(D2), Xiaohang Tong(D1), Zihao Zhao(D1), Ruochen Xu(D1) of Takahashi-Wan Laboratory, Department of Systems Innovation, won the first prize in the “2022 SAMPE Student Bridge Contest World Championship”
〈Name of award and short explanation about the award〉
Society for the Advancement Material and Process Engineering (SAMPE) Student Bridge Contest World Championship is an annual competition for lightweight bridges made of fiber-reinforced composites, and is divided into eight categories based on the type of reinforcing fiber and bridge shape. The University of Tokyo team won the 2022 competition in Category B (hollow rectangular cross section bridge using carbon fiber).
〈About awarded research〉
The winning team of the Japan competition is sent to this world competition as the representative of Japan. Takahashi-Wan laboratory had won the Japan competition for the past three consecutive years, but it had been three years since the world competition was held due to Covid-19. After the optimal structural design by FEM utilizing the anisotropic properties of carbon fiber, we repeated the molding and evaluation tests by hand many times and entered the world competition with our best bridge, which was estimated to have the smallest strength variation based on appearance and sound diagnosis.
〈Your impression & future plan〉
We are very honored to receive this award. We would like to express our deepest gratitude to the members of our laboratory for making it possible for us to receive this award. We did the best we could do at the moment, but we feel fortunate to have won against world-class universities such as the University of Washington and UCLA, which are regular winners of this award. We gained valuable insights and advice from the interaction with these universities, and we will continue to improve our design and molding techniques to pass them on to the younger members in our laboratory.
On 04/03/2022, Naoki Kosuge (M2, Shibasaki lab), Department of Systems Innovation, received Logistics Research Encouragement Award at the Japan Logistics Society
〈Name of award and short explanation about the award〉
The Logistics Research Encouragement Award, awarded by the Japan Logistics Society, is given to outstanding young logistics researchers who have achieved particularly outstanding results enrolled in educational and research institutions to which at least three regular members of the Japan Logistics Society belong.
〈About awarded research〉
Title: Extension of Global Logistics Intermodal Network Simulation (GLINS) Model to include Dry Bulk Cargo
Abstract: This study develops a more comprehensive GLINS model by adding the dry bulk cargo shipping network in the existing model which focused on only the container cargo shipping. Concretely, I select 76 iron ore ports and 130 coal ports based on maritime shipping record extracted from AIS data, develop the vessel size selection model between export and import ports, and develop a cargo assignment model (route choice model) by integrating the dry bulk maritime shipping network with the existing global intermodal transport network which shares the capacity of land transport with container transport.
〈Your impression & future plan〉
First of all, I would like to express my deepest gratitude to Prof. Shibasaki and those who supported me in receiving this award. I am very proud to receive such a prestigious award. In Shibasaki Laboratory, I had very diverse, unique, and fruitful experiences, such as daily research activities, seminars, submitting papers to journals, presentations at international conferences, and fieldwork in overseas. Although I will be leaving the university, I will continue to make efforts to contribute to society by making the most of the experience I have gained through my research activities.