【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.

On March 5, 2022, the Ohsawa-Hayashi Laboratory received the Yokohama City Open Data Special Achievement Award

 

〈Name of award and short explanation about the award〉

Award name: Yokohama City Open Data Special Achievement Award

The City of Yokohama has organized the Yokohama Open Data Development Committee to promote voluntary activities by citizens to share and utilize open data not only for academic purposes but also for various businesses and the improvement of daily life. This is a cutting-edge activity in Japan in the sense that it is centered on voluntary activities by citizens aiming for innovation in various contexts in their daily lives and businesses, with strong support from the city government and universities. This award came to be presented by the Yokohama Open Data Development Committee, which is coming to a developmental conclusion after 10 years of activity in the city of Yokohama, to three organizations that have made significant contributions over the past 10 years.

 

〈About awarded research〉

From the early stages of Yokohama City’s open data activities, Ohsawa-Hayashi-Laboratory has contributed to the cataloging and value creation of Yokohama City’s open data by providing data co-creation support technologies, such as the originally developed Data Jacket. The laboratory has also led to the creation of businesses by conducting numerous workshops using its proprietary technology with many citizens, and has developed a data utilization process that enables people who do not have the technology to directly access data to promote it. As a result, the award was presented by the Yokohama Open Data Solution Development Committee, in the event of International Open Data Day of Yokohama, supported by the Yokohama City Policy Bureau and the Yokohama City Digital Headquarters.

 

Your impression & future plan〉

There are many data utilization projects that have resulted from our various data co-creation support technologies and co-creation activities based on the “data jacket” concept. However, what has tended to remain hidden in the recent focus on big data and AI technologies is the effectiveness of data-related communication in “creating new human connections.” By combining knowledge about various events before they were digitized, and also connecting models of their dynamics, we can grasp new phenomena, and in the process, we can respect the knowledge of others, form relationships, and create a materially and spiritually rich society. The connection of the minds of Yokohama citizens was the driving force that enabled to take advantage of data-federative innovation, and we will continue our activities to further develop a widely-useful literacy to create connections and create values for all people and spread it throughout the entire nation and the world.

 

On November 11th, 2021, Takuya Matsunaga (Research Associate), Koshizuka-labo, Department of Systems Innovation, received Certificate of Merit for Best Presentation for his presentation at the 34th Annual Meeting of the Computational Mechanics Division (CMD2021), JSME.

 

〈Name of award and short explanation about the award〉
Certificate of Merit for Best Presentation

〈About awarded research〉
Numerical stabilization of LSMPS method and application to free-surface flow

 

〈Your impression & future plan〉
It is an honor to receive this award. I’ll continue to conduct innovative research in this area.

【Awards and Commendations】Prof. Yukio Ohsawa received the Research Award from KES International (Headquarters: Selby, UK).

〈Name of award and short explanation about the award〉

“Research Award” KES (Knowledge-Based and Intelligent Information & Engineering Systems) International, headquartered in Selby, UK, is a professional society providing community, networking, research and publication opportunities for all those involved in knowledge-intensive topics and knowledge transfer. Its community has approximately 5000 researchers, engineers, and practitioners, and has been organizing conferences in the field of intelligent systems for over 20 years. This award was presented by KES International to Prof. Ohsawa for his long-term academic contributions.

 

〈About awarded research〉

This award has been addressed to the research on Chance Discovery, its extensions, and the contribution of these works to the communities relevant to KES international. Around 1999-2004, we were in the AI Cambrian era when not only mature machine learning technologies but also other technologies for analysis and visualization of data with high interpretability for humans were being created every day. Workers in various business domains were learning the methodology of data mining, which uses these technologies to acquire knowledge to be used by humans, and were buying expensive tools for data mining.  In data mining, however, the interactions that occur between people should include steps to reflect their interests on generating data and incorporating the data into their own intellectual activities, rather than leaving the steps to tools on machines. The importance of human eyes, ears, hands, mouths, and feet has been well recognized since when users noticed the risk of the overconfidence of machine learning. Chance Discovery is an in-depth study of the role of human hands and minds in helping people get information from data to help themselves make decisions, and the ways in which people communicate to reach chance discovery. The results have now evolved into creative data market design and other studies that support the work of many companies, municipalities, and healthcare providers.

 

〈Your impression & future plan〉

I thought that the “boom” would be overwhelming and that it would be difficult to gain recognition, but I am glad that people continue to pay attention to my work, and I believe that it is beneficial to society. From April, we will establish “Data Collaboration Innovation Literacy” as a social collaboration program, that is an extension of chance discovery and its extensions. We promote this program with the support and participation of four companies from different industries. We aim to in a way that show unexpected value creations to the academic and industrial communities.

【Awards and Commendations】Name: Yukio Ohsawa, Professor, Department of Systems Innovation,

 

Professor Yukio Ohsawa  received Innovative Research Award at the joint conference of 7 conferences organized by — Intelligent Systems Design and Applications (ISDA) , Hybrid Intelligent Systems (HIS’21), Information Assurance and Security (IAS), Soft Computing and Pattern Recognition (SoCPaR), Innovations in Bio-Inspired Computing and Applications (IBICA), Nature and Biologically Inspired Computing (NaBIC) ,Information and Communication Technologies (WICT).

 

〈Name of award and short explanation about the award〉

Innovative Research Award

This award is presented by the Machine Intelligence Research Labs (Washington, U.S.A.) to researchers whose research achievements contribute to innovation in both academia and industry. Yukio Ohsawa came to be the first recipient of this award.

 

〈About awarded research〉

Reason for the award: Technical contributions in the Innovators Marketplace on Data Jackets and outstanding long-term services to the community through editorial and conference related activities.

 

Title of the keynote for the award: Elicitation of Feature Concepts as Data Federative Innovation Literacy

Abstract: Since 2000, the speaker has initiated and embodied Chance Discovery, a subdomain of data science, meaning to detect and explain a chance, a piece of high-utility information as part of data about events meaningful for decision-making. At that time, he thought a network of networks can be the essential model for representing the latent dynamics where an edge between networks is linked to a chance. Then, he extended the methods of chance discovery for explaining the utility of datasets, via the analogy between an event as the base and the metadata of a dataset as the target. As well as the base problem of chance discovery, that is to explain the utility of information about an event considering its relation to other events, the utility of a dataset as the target goal could be explained in its relation to other datasets. However, he found information obtained from a dataset created by a combination of different but connectable (sharing attributes and/or purpose of using) datasets is essentially hard to interpret because the same analysis models as of the original datasets cannot be applied directly due to the difference in the requirements of data user(s). Thus, it comes to be an important problem to elicit a new “feature concept” for target data. A feature concept is a model of the concept to be retrieved from data that cannot be represented by a simple feature such as a single variable but can be by a conceptual illustration. Decision trees, clusters, and even deep neural networks can be positioned as examples of feature concepts. A useful feature concept for satisfying a requirement of a data user has been elicited via creative communication using Data Jackets among data providers, data users, and other stakeholders in the market of data. In this keynote, the history of chance discovery and data-jacket-based design of creative communication is reviewed with some cases of application — marketing, detection of earthquake precursors, suppression of COVID-19 spreading risk, etc., cases and highlight the feature factors elicited and used in these examples. An essential message here is that sharing and using/reusing feature concepts is literacy for data-federative innovations.

 

〈Your impression & future plan〉

The keynote speech at the time of the award was attended by many people from all over the world who are involved in artificial intelligence research, and I feel that my slogan of “data and innovation by people, for people”, breaking away from the stereotype of machine learning and automation, attracted a lot of attention. I don’t have to say it, but I believe that this interest is where the world’s diverse disciplines are clamoring and storing huge amounts of energy at the “knowledge plate boundary. In April, we will establish “Data Collaboration Innovation Literacy” as a social collaboration course, and promote it with the support and participation of four companies from different industries. We aim to develop in a way that show unexpected value creations to the academic and industrial communities.

 

 

 

 

 

【Awards】One-two finish at the Student Bridge Contest Japan Tournament!

On December 3, 2021, two teams from Takahashi Lab won the first and second place in IHI/SAMPE Japan Student Bridge Contest. The winning team will participate in the World Championships in North Carolina, USA in May 2022 as a representative of Japan.

 

<About the award>

The bridges made of carbon fiber reinforced plastics that can withstand the design load (7,200lbf ≒ 3,266kgf) are ranked in order of light weight. The winning team was a bridge weighing only 670g and withstanded a load of 8,486lbf. This is a good result that medals are expected at the world championships.

 

<About the winning teams>

Winning team name: Cool Dock

Members: Ruochen Xu (Leader, D1), Zihao Zhao (D1), Weizhao Huang (D1), Yota Nakamura (M2), Kota Yokomizo (4 years)

Maximum load capacity: 8,486lbf

Bridge weight: 670g

2nd place team name: Road to 7200lbf

Members: Xiaohang Tong (Leader, D1), Qian Gao (D2), Tsukasa Yamazaki (M1), Yuxuan Hu (M1), Tomotaka Suzuki (4th year)

Maximum load capacity: 8,307lbf

Bridge weight: 725g

〈Your impression & future plan〉

Ruochen Xu：
We are honored to be the winner of the IHI / SAMPE Japanese Student Bridge Tournament. I sincerely thank everyone in the team for winning the award. I would like to continue working hard on my research.

Xiaohang Tong：
We have done a good job winning a second-place finish in the contest. It is a pleasure that the efforts of all the teammates are rewarded. We also want to express our sincere gratitude to our supervisor professor Takahashi who has given us valuable advice and to all the lab members who have offered their enormous help. For the coming world tournament of this contest, we will spare no efforts to improve the design and technique and try our best.

Xu et al Winner of Category B

 

Tong et al Second Prize of Category B

【Awards】Mr. Xiaohang Tong (D1) of Takahashi Laboratory received the Best Student Presentation Award and Mr. Ruochen Xu (D1) received the Student Presentation Award at the 17th Japan International SAMPE Symposium and Exhibition on December 3, 2021.

〈About awarded research〉

Title of the Best Student Presentation Award:
Preload relaxation in bolted carbon fiber reinforced thermoplastics joints

Outline of the research:
Research on efficiently manufacturing lightweight and low-cost structures using multi-materials is accelerating due to the electrification and automatic operation of mobile objects. This research clarified the phenomenon of decrease in bonding force, which is a problem when bolt-bonding CFRTP to metal materials, through experiments and simulations.

Title of the Student Presentation Award:
Prediction of tensile strength distribution of CFRTP-SMC by Monte Carlo simulation

Outline of the research:
Continuous fiber CFRP has been successful in small-scale production of large structures such as aircraft, but CFRP made of discontinuous carbon fiber and thermoplastics is indispensable for mass production of small semi-complex structures such as passenger cars, robots and drones. In this study, we clarified the cause of variation on the strength by Monte Carlo simulation, and clarified the manufacturing method of the structure with higher strength and less variation by eliminating the low strength factor.

 

〈Your impression & future plan〉

Xiaohang Tong：It is an honor to receive this award, and I would like to express my appreciation to professor Takahashi and all the lab members who are involved in this research for their kind support. In the future, I will continue to work hard on the research and try to do my best.

Ruochen Xu：I am honored to receive this Student Presentation Award. I would like to thank all the people who supported me in this research. I hope to devote myself to my research in the future.

 

Xiaohang Tong：Bset Student Presentation Award


Ruochen Xu：Student Presentation Award