IPSJ/IEEE-CS Young Computer Researcher Award

IPSJ/IEEE-Computer Society Young Computer Researcher Award

Name of the Award IPSJ/IEEE-Computer Society Young Computer Researcher Award
About the Award The IPSJ and the Institute of Electrical and Electronics Engineers Computer Society (IEEE-CS) established a joint award in 2018 to honor young researchers in the field of computer science for their outstanding achievements and high expectations of their continuing progress.
Selection Process The awardees should be decided annually by the joint award committee which consists of members from both IPSJ and the IEEE-CS. The decision should be confirmed by both societies.
Selection Criteria The awardees should be young researchers who have outstanding achievements such as research presentations, publications and programming as well as high expectations of further achievements in the field of computer science. The awardees should be the members of the IPSJ and the IEEE-CS.
Conferment The award will be presented at a conference organized or hosted by the IPSJ and the IEEE-CS. The certificates will be given at the award banquet.



Daisuke Sakamoto (Hokkaido University)

Outstanding Research on Designing User Interface and Interaction

Daisuke Sakamoto is an Associate Professor of Human-Computer Interaction lab, Hokkaido University. He received his Ph.D. in Systems Information Science from Future University-Hakodate in 2008. He was an Intern researcher of ATR Intelligent Robotics and Communication Labs (2006-2008). He worked at The University of Tokyo as a Research Fellow of the Japan Society for the Promotion of Science (2008-2010). He joined JST ERATO Igarashi Design Interface Project as a researcher (2010). After that, he backed to The University of Tokyo as an Assistant Professor (2011) and a Project Lecturer (2013-2017). His research interests include Human-Computer Interaction and Human-Robot Interaction, which focused on user interaction with people and interaction design for computing systems.

Dr. Daisuke Sakamoto. has been working on designing user interfaces and interaction to make stateof-the-art computing technology accessible and usable. Specifically, he has led the fields of HumanComputer Interaction (HCI) and Human-Robot Interaction (HRI) by creating enabling technologies that realize novel interaction to make computing technology available for the end-users. His research contributions have been published in 42 journal articles, 41 international full conference papers, 22 international poster presentation and demonstration, and 110+ Japanese domestic papers, including 16 IPSJ Journal articles, 19 IPSJ SIG related venues. Those contributions were awarded 38 times, including Best paper award (IPSJ Interaction symposium 2007, ACM/IEEE HRI2007), IPSJ Outstanding Paper Award (2009), and so on.
He is an IPSJ member since 2004, IEEE/IEEE-CS member since 2020. Regarding activities for IPSJ, he has served as a Program Committee or Organizing Committee member of IPSJ symposiums 24 times, including program chairs 2 times. IPSJ recognized his achievement as new generation planning committee member and gave him IPSJ Activity Contribution Award (2015). Regarding IEEE activities, he had served as special session chair of IEEE GCCE (2013, 2014), and fundraising & exhibitions co-chair of ACM/IEEE HRI (2013, 2015 – 2017). He is appointed as General co-chair of ACM/IEEE HRI2022.


Takuya Azumi (Saitama University)

Outstanding Research on Embedded Real-time Platform

Takuya Azumi received his Ph.D. degree from the Graduate School of Information Science, Nagoya University in 2009. From 2008, he was under the research fellowship for young scientists for Japan Society for the Promotion of Science. From 2010, he was an Assistant Professor at the College of Information Science and Engineering, Ritsumeikan University. From 2014, he was an Assistant Professor at the Graduate School of Engineering Science, Osaka University. From 2018, he is an Associate Professor at the Graduate School of Science and Engineering, Saitama University. He also works as a JST-PRESTO researcher since 2017. His research interests include embedded real-time systems. He received ESS Best Paper Award (2019),  IEEE/ACM DS-RT Best Paper Runner-up Award (2019), IEEE ICESS Outstanding Paper Award (2020), and  IPSJ Yamashita Award (2021). He contributed to the global standardization of IEEE 2804-2019.

Prof. Takuya Azumi has been working on embedded real-time platform. Specifically, he has led the fields of embedded real-time systems. His research contributions have been published in 23 journals, and 61 international conference papers among which 8 journals, 45 international papers (especially, the IEEE ICCPS 2018 paper has been cited 125 times) have been published by IPSJ and IEEE-CS. He received 10 awards from IPSJ and IEEE-CS. He has presented more than 40 invited talks and 2 keynote talks. He has received 176.6M JPY research budget thus far as a principal investigator. He is an IPSJ member since 2004, IEEE member and IEEE-CS member since 2006. Regarding activities for IPSJ, he has been a committee member of SIG-EMB, SIG-OS, and a PC chair of SWEST 15/16/17 which is an IPSJ SIG-EMB workshop, and a PC member of ESS which is an IPSJ SIG-EMB symposium. Regarding activities for IEEE, he has served as a WiP chair and a Publicity co-chair of CPSNA 2013, a Publication Chair of CPSNA 2014 and CPSNA 2015, and a PC member of EUC 2011, ISORC 2014/2015/2016, RTCSA 2015/2020, and COOL chips XIX. In addition, he contributed to making an IEEE standard (IEEE 2804-2019 Published Date:2020-01-24).

Yuichi Sei (the University of Electro-Communications)

Privacy-Preserving Web/IoT Data Analysis

Yuichi Sei received the Ph.D. degree in information science and technology from the University of Tokyo in 2009. From 2009 to 2012, he was with the Mitsubishi Research Institute. He joined the University of Electro-Communications in 2013, and is currently an associate professor in the Graduate School of Informatics and Engineering. He is also a JST PRESTO researcher and a visiting researcher at Mitsubishi Research Institute. His current research interests include privacy-preserving data mining, and agent technologies. He received DICOMO Best Paper Award in 2007 and IPSJ Best Paper Award in 2017. 

Various people and organizations are considering whether to build and spread new services that utilize Web and IoT data across the board. It is expected that systems and infrastructure will be in place to distribute and combine these data in the future. However, it will be difficult to predict from where personal privacy information will leak. Therefore, the construction of a solid common framework to protect privacy is an important issue. The purpose of this study is to protect and share Web/IoT data containing privacy information to enable safe, secure and accurate analysis. He developed the world's first algorithms for data collection, machine learning, and statistical analysis of data containing more than tens of thousands of attributes with errors and missing values, while protecting privacy.
He is collecting IoT data, including privacy information, by having subjects live in an apartment building, and confirming the usefulness of the proposed algorithms for real-world data. The research is being conducted with an eye toward real-world applications, taking into account the combination of unknown data and errors, and has been mathematically rigorously proven to be safe. He is on track to become one of the world's top researchers in both theory and practice.



Fuyuki Ishikawa (National Institute of Informatics)

Research on Intelligence-driven Engineering of Dependable Smart Systems

Fuyuki Ishikawa is Associate Professor, Information Systems Architecture Science Research Division, and Deputy Director, GRACE Center, at National Institute of Informatics. He also serves as a Visiting Associate Professor, Graduate School of Informatics and Engineering, University of Electro-Communications. He received his Ph. D. degree in Information Science and Technology from The University of Tokyo in 2007. He has worked on a range of research topics in Software Engineering and Autonomous, Smart Systems.

Dr. Ishikawa has conducted intensive research crossing the fields of software engineering and smart systems. The excellence of his research lies in novel problem settings for quality and dependability in emerging paradigms, often linked with the industry demands, as well as interdisciplinary technical solutions primarily based on evolutionary computation. His early work focused on the field of services computing. He provided novel technical solutions on automated design for web and cloud systems. He has recently been focusing on quality and dependability of smart cyber-physical systems, especially autonomous driving systems and machine learning-based systems. For the latter, he is leading a new academia-industry community on machine learning systems engineering. His recent key publications were based on industrial problems and appeared in top conferences of software engineering and of evolutional computation.


Ryota Shioya (The University of Tokyo)

Outstanding Achievements on Microprocessor Architecture

Ryota Shioya received his Ph.D. in Information and Communication Engineering from the University of Tokyo in 2011. From 2011, he was an assistant professor at the Graduate School of Engineering, Nagoya University. Since 2018, he has been an associate professor at the Graduate School of Information Science and Technology, the University of Tokyo. His current research interests include computer systems and microprocessors. He received IEEE Computer Society Japan Chapter Young Author Award(2011)and IPSJ Ymashita Award.

Prof. Shioya has outstanding achievements in research on high-performance, low-energy microprocessor architectures. It is well known that microprocessors are key components of computer systems, and their architectural optimizations ate critical challenges. Although microprocessor research itself has a long history, still many vendors and researchers keep trying to develop new technologies. His distinctive contribution is the “innovative front-end design” of microprocessors. Many researchers have focused on “back-end design,” where actual calculations like addition and subtraction are executed. In contrast, Prof. Shioya discovered the significant potential to optimize the front-end (instruction fetching, decoding, and register reading) part, then proposed a new concept to make the front-end more intelligent. This approach changes the design balance of microprocessors, and it has not so far been explored in our community. Based on the new concept, he has proposes innovative ideas that significantly improve the performance-energy efficiency of microprocessors. His three papers have been accepted in a TOP tier computer architecture conference called MICRO (IEEE/ACM International Symposium on Microarchitecture) that has the oldest history in this research area (acceptance rate is around or less than 20%). Prof. Syoya is the only young researcher whose papers were constantly accepted at the top conference.

Kazuya Murao (Ritsumeikan University)

Outstanding Research on Human Activity Recognition for Wearable Computing

Kazuya Murao received Ph.D. in Information Science and Technology in 2010 from Osaka University. From 2010, JSPS Reserch Fellow (PD). From 2011, post-doc researcher at Kobe University. From 2011, assistant professor at Kobe University. From 2014, assistant professor at Ritsumeikan University. From 2017, associate professor at Ritsumeikan University. In 2017, visiting researcher at University of Freiburg, Germany. From 2019, JST PRESTO researcher. He is working on wearable computing and human activity recognition. He received IPSJ DICOMO2012 Best Paper Award, Journal of Information Processing (JIP) Specially Selected Paper (twice), Human interface society 2015 Best Journal Paper Award, ACM ISWC2019 Best Paper, etc. 

Dr. Kazuya Murao is leading research on the field of human activity recognition for human-computer interaction. One of his outstanding research is about context-aware wearable sensor. His proposed system improves the granularity of contexts of a user situation and supplies power based on the optimal sensor combination by reducing energy consumption. In addition, in proportion to the remainder of power resources, the proposed system reduces the number of active sensors within the tolerance of accuracy. His researches are highly evaluated by international research communities including wearable computing, interactive systems, and so on.


Atsushi Shimada

Atsushi Shimada (Kyushu University)

Outstanding Research on Real-time Learning Analytics

Atsushi Shimada received the M.E. and D.E. degrees from Kyushu University in 2007. He is an Associate Professor of Faculty of Information Science and Electrical Engineering, Kyushu University. He also works as a JST-PRESTO researcher since 2015. His current research interests include learning analytics, pattern recognition and media processing and image processing. He received MIRU Interactive Presentation Award (2011, 2017), MIRU Demonstration Award (2015), Background Models Challenge 2012 The First Place (2012), PRMU research award (2013), SBM-RGBD Challenge The First Place (2017), ITS Symposium Best Poster Award (2018), JST PRESTO Interest Poster Award (2019). 

Dr. Atsushi Shimada is leading research on real-time learning analytics, which is a combination of learning analytics with real-time processing. Much attention has been paid to learning analytics, which aims at optimization of learning and teaching through analysis of educational big data. He has contributed to develop a digital learning environment containing an e-learning systems and an e-book system for collecting educational big data from onsite lectures, so as to accelerate effective feedback in students’ active learning and teachers’ adaptive teaching. His major contributions are the development of a real-time learning analytics platform and various applications such as learning pattern mining, prediction of academic performance, and recommendation of learning materials. The outstanding achievements are 1) automatic summarization of lecture materials for enhanced preview, 2) stream analytics of educational big data for supporting on-site lectures, and 3) activity analytics of individual students from event stream data.

Takuya Maekawa

Takuya Maekawa (Osaka University)

Outstanding Research on Zero-shot and Few-shot Unobtrusive Context Recognition for Pervasive Computing

Graduate School of Information Science and Technology, Osaka University. Takuya Maekawa received the B.E., M.E., and Ph.D. degrees from Osaka University, Osaka, Japan in 2002, 2003, and 2005, respectively. He joined NTT Communication Science Laboratories in 2006. He is currently an associate professor at Osaka University, Japan. His research interests include ubiquitous computing and wearable sensing. 

Dr. Takuya Maekawa has studied on sensor-based context recognition techniques. Specifically he focuses on human activity recognition and indoor positioning techniques that can be easily applied to an environment of interest with small costs. He has developed practical context recognition techniques with a small number of unobtrusive sensors and machine learning. His major achievements are summarized into three topics, 1) object-based activity recognition with wrist-worn heterogeneous sensors, 2) constructing activity recognition models with small costs using physical characteristics information, and 3) unsupervised factory activity recognition. His research achievements enabling pervasive computing with low costs are highly evaluated by international research community.



Yutaka Arakawa

Yutaka Arakawa (Nara Institute of Science and Technology)

Outstanding Research on Human Behavior Change by Information Technology

Akira Kawai

Akira Kawai (Shiga University)

Outstanding Research on Intelligent Car Navigation System for Multilevel Parking Facilities


Yukihiko Shigesada

Yukihiko Shigesada (Hosei University)

Outstanding Achievements on International AI Programming Contest "SamurAI Coding"

Press release (Japanese)