Find Academic Supervisors

• Cognitive Robotics
• Developmental Robotics
• Human-Robot Interaction
• +5 more

Tetsuya Ogata is a Professor at the Faculty of Science and Engineering, School of Fundamental Science and Engineering at Waseda University. He also holds joint appointments as a Fellow at the Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology (AIST), and as a visiting professor at the National Institute of Informatics (NII). Professor Ogata serves as director of the Institute of AI and Robotics at Waseda University, chairperson of the AI Robot Association (AIRoA), and research supervisor of JST CREST "Fundamentals and Core Technologies for Embodied AI" since 2025. Professor Ogata received his B.S., M.S., and D.E. degrees in mechanical engineering from Waseda University in 1993, 1995, and 2000, respectively. He began his academic career as a Research Associate at Waseda University (1999-2001), followed by positions as a Research Scientist at RIKEN Brain Science Institute (2001-2003), Lecturer (2003-2005) and Associate Professor (2005-2012) at Kyoto University's Graduate School of Informatics, before becoming a Professor at Waseda University in 2012. He was also a JST PRESTO Researcher from 2009 to 2015. Professor Ogata's research focuses on cognitive developmental robotics, deep predictive learning, and the integration of vision, language, and action (VLA) for human-robot interaction. His work explores how robots can learn through experience and interaction with humans and environments, developing models that allow for flexible behavior generation and adaptation. His research has significant implications for creating robots that can understand human intentions, collaborate effectively in real-world settings, and continuously learn from their experiences. The integration of multimodal information processing with predictive models forms the core of his approach to embodied artificial intelligence. Analysis of Professor Ogata's recent publications reveals a strong focus on deep predictive learning frameworks that enable robots to anticipate future states and generate appropriate actions. His research spans multiple domains including soft object manipulation, bimanual coordination, transparent object grasping, and integration of large language models with robotic systems. A notable trend is the increasing emphasis on multimodal integration, combining visual, tactile, and linguistic information to create more robust and adaptable robotic systems. His recent work also shows growing interest in the application of foundation models to robotics, aiming to create more general-purpose robotic capabilities. Best Paper Award, Advanced Robotics, The Robotics Society of Japan (2024) Best paper award Nomination Finalist, IEEE/SICE International Symposium on System Integration (2024) Frontiers of Science Awards, The International Congress for Basic Science (2023) Minister of Education, Culture, Sports, Science and Technology Award (2023) Fellow, Japan Society of Mechanical Engineering (2023) Fellow, The Society of Instrument and Control Engineers (2022) Fellow, The Robotics Society of Japan (2022) IBM Academic Awards (2017) Professor Ogata has been instrumental in establishing collaborative research frameworks between academia and industry, serving in leadership roles for multiple professional organizations including the Robotics Society of Japan, Japanese Society for Artificial Intelligence, and Japan Deep Learning Association. His research has been supported by significant grants including JST CREST funding for "Fundamentals and Core Technologies for Embodied AI." He has mentored numerous researchers who have gone on to contribute to the field of robotics and AI, with many of his former students now holding positions in leading academic and industrial research institutions. Professor Ogata directs the Ogata Laboratory at Waseda University, which focuses on cognitive developmental robotics and deep predictive learning. The lab maintains strong collaborations with industry partners including major robotics companies and technology firms. In 2025, he played a key role in establishing the AI Robot Association (AIRoA), which brings together companies like Toyota, Nissan, and KDDI to advance the development of practical AI robotics technologies. His research group is known for its interdisciplinary approach, combining insights from neuroscience, cognitive science, and engineering to create more human-like robotic capabilities.

• Time Series Analysis
• Big Data Analytics
• Predictive Modeling
• +3 more

Yasushi Sakurai is a Professor in the Department of Translational Datability at Osaka University's Institute of Scientific and Industrial Research, co-leading the Sakurai and Matsubara Laboratory within the Center for Industrial Science and AI. His research mission focuses on transforming society through real-time prediction of natural and social phenomena using large-scale data analytics, with emphasis on practical technological implementation. His research spans time-series big data analysis, dynamic learning systems, and real-time information provision. Key areas include tensor stream mining, EEG-based healthcare applications, cybersecurity anomaly detection, and multi-omics cancer subtyping. The lab specializes in developing deployable technologies that optimize social activities through predictive modeling of evolving data streams. Recent publications (2023-2025) reveal concentrated innovation in time-series data stream processing, with dominant themes in tensor analytics, frequency-domain forecasting, and causal modeling. His team produces high-impact work accepted at premier AI venues (ICLR, AAAI, KDD, WWW), consistently featuring oral presentations that highlight technical novelty and societal relevance. Scientific Awards: FY2024 Minister of Education, Culture, Sports, Science and Technology Award for Science and Technology (Research Category) for dynamic learning and real-time data stream analysis Professor Sakurai mentors graduate students including Naoki Chihara (DEIM2024 Outstanding Paper Award winner), Yuka Tamura (DEIM2024 Student Presentation Award winner), and Ren Fujiwara. His lab maintains active industry-academia partnerships focused on practical technology deployment, with research directly addressing real-world challenges in healthcare monitoring and cybersecurity. The Sakurai and Matsubara Laboratory operates as a dynamic research unit within Osaka University's Center for Industrial Science and AI, structured around specialized teams for tensor stream analysis, medical data mining, and network dynamics. Current projects emphasize real-time prediction systems with immediate societal applications, supported by strong industry collaboration frameworks.

• Digital Well-being
• Human-Microbe Interaction
• Neo-cybernetics
• +7 more

Dominique Chen is a Professor at Waseda University's School of Culture, Media and Society since 2022, previously serving as Associate Professor from 2017-2022. A French national born in 1981, he holds a Ph.D. in Interdisciplinary Informatics from the University of Tokyo (2013). His work bridges technology, art, and human experience with a focus on digital well-being and more-than-human relationships. Chen's research interests include human-microbe interaction, neo-cybernetics, and the design of systems that foster mutual care between humans and non-human entities. His work with the Nukabot project exemplifies this interdisciplinary approach, exploring how fermentation processes can serve as metaphors for communication and relationship building. He leads the Ferment Media Research group, investigating how fermentation principles apply to digital cultures and communication systems. His recent publications reveal a consistent focus on designing for well-being in digital societies, with particular attention to translation processes, human-microbe relationships, and the creation of systems that support co-adaptive interaction. The Nukabot research series demonstrates how traditional fermentation practices can inform novel interaction paradigms that acknowledge and incorporate more-than-human perspectives. Best Paper Honorable Mention (2024) - ACM Synlogue with Aizuchi-bot ACM SIGGRAPH Special Prize (2023) - Nukabot Best of AppStore 2015/2016 - Picsee/Syncle applications Good Design Award (2008) - Creative Commons Japan Super Creator certification (2009) - IPA Exploratory IT Program Chen has advised numerous projects through his leadership of Ferment Media Research and has served on various committees including the Good Design Award jury (2016-), Yomiuri Shimbun Reading Committee, and advisory boards for art and design institutions. His work extends beyond academia through his founding of Divideal Inc. (acquired by Smart News in 2018) and Creative Commons Japan (now Commonsphere). His laboratory, Ferment Media Research, explores interdisciplinary connections between fermentation processes, digital systems, and human relationships, creating installations like Nukabot that facilitate human-microbe interaction and Last Words/TypeTrace that examines writing processes and communication.

• Information Security
• Privacy
• Autonomous Driving
• +5 more

Dr. Tatsuya Mori is a Professor at the Department of Computer Science and Communication Engineering , Faculty of Science and Engineering, Waseda University . He also holds visiting researcher positions at RIKEN Center for Advanced Intelligence Project (since 2018) and National Institute of Information and Communications Technology (since 2019). Education: Ph.D. in Information Science (2005), Waseda University Research Interests: Spanning information security and privacy across emerging technologies like autonomous driving , AI , 3D sensing , VR , biometric measurement , and Web3 . His work focuses on offensive security and interdisciplinary research , including physical-layer attacks on sensors and behavioral studies on phishing detection. Scientific Awards: Recipient of multiple prestigious awards, including the Distinguished Paper Award Runners-Up at IEEE EuroS&P 2024 , IPSJ Outstanding Paper Award 2024 , and CSS2024 Concept Research Prize . His research has been recognized in top conferences like USENIX Security , NDSS , and ACM CCS . Professional Leadership: Active in academic governance as Chief Investigator for NISC Working Groups and Committee Member for JST Research Areas . He serves on program committees for NDSS , IMC , and ACM CCS .

• Data science
• Machine learning
• Business analytics
• +10 more

Masayuki Goto is a Professor in the Department of Industrial Systems Engineering, School of Creative Science and Engineering at Waseda University, Japan, where he has served since 2011. He earned his Doctor of Engineering from Waseda University and leads research integrating statistical science, machine learning, information theory and management engineering to solve business-analytics, marketing, AI ethics and industrial optimisation problems. Education: Doctor of Engineering, Waseda University Research Interests: His work spans data science, machine learning, business analytics, statistical learning theory, generative AI, deep neural networks, natural language processing, network analysis and information theory, with recent emphasis on trustworthy AI and synthetic data generation. Publication Trends: Over 2024-2025 his group has published extensively on deep learning for tabular data, vision-language models, recommender systems, causal inference and ethical AI, demonstrating a shift toward generative-AI-driven business analytics and interpretable models. Scientific Awards: Best Paper Award, CIE51 2024 Outstanding Paper Award, APIEMS 2023 Best Paper Award, APIEMS 2022 Best Paper Award, 20th ANQ Congress 2022 2022 PC Conference Best Paper Award Best Paper Award, JASMIN 2021 Best Paper Award, 19th ANQ Congress 2021 Encouragement Award, AAMSA 2021 IDR User Forum 2020 Enterprise & DBSJ Special Awards Best Paper Award, APIEMS 2019 Best Paper Award, ANQ Congress 2018 World CIST'18 Best Paper Award Best Paper Award, ANQ Congress 2017 JSPS Grant Review Commendation 2016 JIMA Distinguished Research Award 2015 Best Paper Award, Journal of JIMA 2015 IPSJ National Convention Best Paper Awards (2015 & 2012) Advising & Grants: He has mentored a large cohort of graduate students evidenced by co-authorship on over 100 recent papers. He has served as PI on numerous JSPS KAKENHI grants and industry projects focused on data-driven management, AI marketing and ethical AI frameworks. Labs & Teams: He heads the Goto Laboratory within the Waseda Institute for Advanced Study, leading interdisciplinary projects on business AI, data-ethics education and industrial optimisation.

• Intellectual Property Law
• Copyright Law
• Information Law
• +3 more

Tatsuhiro Ueno serves as Professor at Waseda University's Faculty of Law and School of Law, specializing in Intellectual Property Law, Copyright Law, and Information Law. He currently holds leadership positions as Director of the Institute of Comparative Law (since 2024) and President of SARLIB (Society for Administration of Remuneration for Public Transmission by Libraries or Similar Facilities). With extensive international experience including visiting scholar positions at Ludwig Maximilian University of Munich and the Max Planck Institute for Intellectual Property and Competition Law, Professor Ueno has established himself as a leading authority in copyright law reform and international intellectual property matters. Professor Ueno earned his Master of Law from Kyoto University following undergraduate and graduate studies there. His academic career includes teaching positions at Rikkyo University College of Law and Politics and Seijo University Faculty of Law before joining Waseda University in 2013, where he now contributes to shaping Japan's legal education landscape. His research focuses on the critical intersection of intellectual property law with emerging technologies, particularly artificial intelligence systems and digital platforms. Professor Ueno has pioneered work on text and data mining exceptions, copyright limitations in digital environments, and creator-oriented copyright frameworks. His scholarship bridges theoretical analysis with practical policy development, influencing both domestic legislation and international copyright discourse. His recent publications demonstrate a concentrated focus on AI and copyright law, with numerous articles examining the legal challenges posed by generative AI systems, text and data mining exceptions, and the evolving landscape of copyright protection in the digital era. Professor Ueno's work consistently addresses the balance between protecting creators' rights and ensuring public access to knowledge. KDDI Foundation Book Publishing Grant (January 2025) for "Creator-Oriented Copyright System" Professor Ueno actively participates in numerous government committees shaping Japan's copyright law, including serving as Chairman of the Law and Computers Society and as a longstanding member of the Copyright Subcommittee of the Council for Cultural Affairs. His research is supported by multiple grants from the Japan Society for the Promotion of Science, including ongoing projects examining human portraits and voices in the AI age (2025-2029) and AI and intellectual property rights systems (2024-2029). He regularly presents at international forums including WIPO Summer Schools, ATRIP conferences, and copyright forums worldwide, establishing his reputation as a key thought leader in global copyright policy development.

• Neural Networks
• Genetic Algorithms
• System Identification and Control
• +7 more

FURUZUKI, Takayuki is a Professor at Waseda University's Faculty of Science and Engineering, Graduate School of Information, Production, and Systems. He holds a PhD from Kyushu Institute of Technology and maintains the NCLab research group (http://nclab.w.waseda.jp/nclab/). His professional memberships include the Institute of Electronics, Information and Communication Engineers, Institute of Electrical Engineers of Japan, Society of Instrument and Control Engineers, and IEEE. His educational background includes a PhD in Information Science from Kyushu Institute of Technology (1994-1997), a Master's degree in Electronics Engineering from Sun Yat-Sen University (1983-1986), and a Bachelor's degree in Electrical & Electronic Systems Engineering from Sun Yat-Sen University (1979-1983). Professor FURUZUKI's research spans neural networks, genetic algorithms, system identification and control, complex systems, bioinformatics, and combinatorial optimization. His work integrates soft computing techniques with medical informatics and control systems engineering, developing innovative approaches for problems ranging from brain tumor segmentation to music information retrieval. His research methodology often combines theoretical foundations with practical applications in healthcare, energy systems, and intelligent transportation. His recent publication record shows a strong focus on sequential recommendation systems, graph neural networks for medical imaging, music information retrieval, and power systems analysis. The consistent thread across his work is the application of advanced machine learning techniques to solve complex, real-world problems across diverse domains, with particular emphasis on handling missing data, improving model efficiency, and enhancing prediction accuracy. His scientific achievements have been recognized with several prestigious awards: ISCIIA2008 Excellent Paper Award (2008) Institute of Electrical Engineers of Japan Excellent Paper Award (2001) Guangdong Province Higher Education Science and Technology Progress Second Prize (1991) Guangdong Province Higher Education Science and Technology Progress Second Prize (1989) Chinese Ministry of Education Scientific and Technological Achievements Second Prize (1986) Professor FURUZUKI has maintained continuous research activity since joining Waseda University in 2003, with significant contributions to multiple research projects spanning neural computation, soft computing, and system engineering. His work demonstrates strong international collaboration, with publications involving researchers from various institutions worldwide. His research output includes over 410 papers with 3,623 citations and an h-index of 23 according to Scopus data. The NCLab research group, which he leads, focuses on neural computation and related areas, providing a platform for interdisciplinary research that bridges theoretical foundations with practical applications in healthcare, energy systems, and intelligent transportation. His laboratory environment fosters innovation in machine learning algorithms and their application to real-world problems, with particular emphasis on developing efficient, robust solutions for complex data analysis tasks.

• Smart Communities
• Next-generation Mobility Systems
• Unused Biomass Utilization Technologies
• +6 more

Hiroshi Onoda is a Professor at the Faculty of Science and Engineering and Graduate School of Environment and Energy Engineering , Waseda University. His work focuses on environmentally friendly design , LCA , resource recycling , renewable energy systems , and smart communities . He holds a Doctor of Engineering from Waseda University and has held various leadership roles, including Dean of the Graduate School of Environment and Energy since 2022. Education : PhD in Mechanical Engineering (Waseda University, 2006) Professional Leadership : Environment Energy Advisor (Saitama Prefecture, 2010–2015), Director of Waseda Environmental Institute Co., Ltd. (2011–2017) Research Themes : Onoda’s research spans smart waste management , EV integration , CO2 reduction , and renewable energy deployment . He emphasizes AI and IoT applications in waste systems, decentralized energy solutions for developing nations, and decarbonization strategies for urban and industrial contexts. Publication Trends : His recent work addresses AI-driven recycling optimization , community-level GHG inventories , and DAC-based fertilizer systems , reflecting his commitment to circular economy and low-carbon mobility . Key sub-fields include robotic waste sorting , decentralized energy planning , and plastic recycling economics . Scientific Awards : Environment Minister’s Commendation (2024) Best Paper Award, ICET4SD (2021) JSME Environment Division Award (2014) JSME Research Encouragement Award (2018) Grants and Projects : Onoda has led nationwide evaluations of low-carbon industrial zones , hydrogen utilization , and plastic recycling policies . He contributes to Japan’s decarbonization roadmap through roles in NEDO and Ministry of the Environment committees. Labs and Initiatives : He founded the Waseda Environmental Research Institute, Inc. (2003) and drives innovation through the BRIDGE LIFE Platform for smart communities in Japan.

• Information Access
• Information Retrieval
• Natural Language Processing
• +3 more

Tetsuya Sakai is a Professor at the School of Fundamental Science and Engineering within Waseda University's Faculty of Science and Engineering. His work focuses on information access, retrieval, and natural language processing, with a particular emphasis on evaluation frameworks for search systems. Affiliations: Waseda University (Faculty of Science and Engineering, School of Fundamental Science and Engineering) Academic Rank: Professor Research Interests : Dr. Sakai's research spans four key areas: (1) Information Access —designing systems for direct and immediate information delivery, (2) Search Evaluation —developing metrics like Height-Biased Gain and hierarchical intent-based diversity measures, (3) Fairness in IR —pioneering frameworks for group fairness in conversational search, and (4) Statistical Reform —advocating Bayesian methods and robust experimental design. His work also addresses privacy inconsistencies in mobile apps and cognitive biases in LLMs. Scientific Awards : Notable recognitions include induction into the SIGIR Academy (2023) , ACM Distinguished Member (2018) , ACM Senior Member (2016) , and multiple DEIM/FIT/CSS Best Paper Awards . He has received teaching honors like the Waseda Presidential Teaching Award (2016) and WASEDA e-Teaching Award (2018) . Article Trends : Recent publications highlight: Advancements in LLM-assisted relevance assessments and hallucination diagnostics for tool-augmented models Conversational search fairness through multi-level evaluation frameworks and group diversity metrics Innovations in 3D medical reconstruction from clinical data and multimodal uncertainty modeling Statistical rigor via randomization tests , credible intervals , and topic set design Privacy analysis in mobile app descriptions and cognitive bias studies in search interaction

• Environmental Law
• Administrative Law
• Energy Law
• +4 more

Professor Satoshi Kurokawa is a full Professor of Environmental and Administrative Law in the School of Social Sciences at Waseda University, Japan. Holding Ph.D. and LL.M. degrees from Kyoto University and a B.A. in Political Science from Waseda, he has taught continuously since 1994, first at Tezukayama University and, from 2004 onward, at Waseda, where he served as Associate Professor (2003-2004) before promotion to Professor. Education: Ph.D. (Kyoto University) LL.M. (Kyoto University) Bachelor of Political Science (Waseda University) Research interests revolve around the intersection of public law and sustainability: environmental law, administrative law, energy law, climate-change policy, nuclear-risk regulation, energy justice, and the legal challenges posed by artificial-intelligence in government decision-making. His recent work pays particular attention to achieving Japan’s 2050 carbon-neutrality target through an “energy-justice” lens, examining social acceptance of high-level radioactive-waste disposal, and assessing the rule-of-law implications of algorithmic administration. Grants & projects: He currently leads a JSPS KAKENHI multi-year project (2024-2028) on “Long-Term Disaster Preparedness and Intergenerational Equity in Light of Uncertainty in Predicting Mega-Earthquakes,” and has completed earlier JSPS projects on climate policy under the Trump administration, California’s sub-national leadership, and social acceptance of geological disposal of nuclear waste. Professional memberships: Japan Public Law Association, Environmental Law Policy Association, and Japan-US Law Society. He teaches an extensive range of courses including “Environmental Law in Japan,” “Environmental Issues and Sustainable Society,” “Sustainability Study,” and “Social Science for Energy Innovation” across Waseda’s graduate and undergraduate programmes, and is concurrently affiliated with several interdisciplinary research institutes.

Masatoshi OkutomiView profile

Professor

• Medical Imaging
• Computer Vision
• Deep Learning
• +5 more

Professor Masatoshi Okutomi is affiliated with the Department of Systems and Control Engineering at the School of Engineering, Institute of Science Tokyo. His research focuses on advanced medical imaging techniques, particularly in endoscopy and 3D reconstruction, leveraging deep learning and neural networks. Key interests include virtual chromoendoscopy for cancer detection, image restoration, and stereo matching under challenging conditions. His work bridges computer vision and healthcare, addressing real-world applications such as MRI reconstruction and foggy stereo matching. Notable contributions include developing lightweight medical segmentation networks for edge devices and advancing neural radiance fields (NeRF) for novel view synthesis. His research spans diverse domains: from improving video quality assessment to enhancing object detection in high-dynamic-range images. Collaborative projects emphasize practical solutions for medical diagnostics and robust image processing in adverse environments. Recent articles highlight advancements in temporally-consistent video restoration, few-shot view synthesis, and degraded image classification using knowledge distillation. These innovations underscore his commitment to pushing boundaries in both theoretical computer vision and applied medical technology.

• Human–robot interaction
• Spoken language processing
• Image and audio processing
• +3 more

Tetsunori Kobayashi is a Professor in the School of Fundamental Science and Engineering at Waseda University, Japan, where he has served since 1997. He is renowned for pioneering research in human–robot interaction, spoken language processing, and multimodal conversational systems, leading to over 230 refereed papers and an h-index of 35 (Google Scholar). Education: 1980 B.Eng. in Electrical Engineering, Waseda University 1982 M.Eng. and 1985 Dr.Eng. from Graduate School of Science and Engineering, Waseda University Research Interests: His work spans intelligent robotics , perceptual information processing , pattern recognition , image and audio processing , and conversational AI . He develops algorithms for real-time dialogue systems, multi-party conversation facilitation robots, and non-autoregressive speech recognition leveraging CTC and pre-trained language models. Recent Publication Trends: Since 2020 his group has advanced non-autoregressive end-to-end ASR (Mask-CTC, Intermpl, BECTRA), noise-robust attention , multi-look-ahead conversational ASR , and neural speaker diarization . They integrate BERT-style pre-training with CTC losses to accelerate inference while maintaining accuracy. Parallel work explores vision-and-language topics such as scene-graph generation, video semantic indexing, and personalized summarization for spoken news delivery. Scientific Awards: IEICE Fellow 2023 – for multi-modal multi-party conversation research IPSJ Fellow 2016 – for pioneering robot conversation studies JST Award for Academic Start-ups 2024 Best Paper Awards from IEICE, IEEE BTAS, ACM SIGGRAPH VRCAI, and several IPSJ workshop prizes Advising & Grants: He has mentored dozens of PhD and Master’s students who now lead in academia and industry. Major funded projects include JST CREST on conversational robotics, NEDO and JST-support for AI-based speech interfaces, and industry collaborations with NHK, OKI, and NEC. Labs & Teams: Kobayashi heads the Perceptual Computing Laboratory at Waseda, conducting interdisciplinary research with domestic and international partners such as MIT, ATR, and NHK Science & Technology Labs.

• Renewable Energy
• Statistical Data Analysis
• Energy Management Systems
• +3 more

Yu Fujimoto is a Professor at Waseda University's Advanced Collaborative Research Organization for SmartSociety. Previously, he served as an Associate Professor at Waseda University's Advanced Collaborative Research Organization for Smart Society (2015-2023) and Institute for Nanoscience & Nanotechnology (2012-2015), and as an Assistant Professor at Aoyama Gakuin University's Department of Integrated Information Technology (2009-2012). He holds a Doctorate from Waseda University's Graduate School, Division of Science and Engineering and is a member of IEEE and the Information Processing Society of Japan. His research focuses on statistical science applied to energy systems, with specific interests in renewable energy forecasting, statistical data analysis for energy management systems, and statistical machine learning theory. Fujimoto has published 109 papers with 1,191 citations and maintains an h-index of 16, demonstrating significant impact in his field. His recent publications show a strong trend toward integrating machine learning techniques with power system applications, particularly focusing on renewable energy integration, electric vehicle charging optimization, smart grid technologies, and carbon reduction strategies. His work frequently addresses the challenges of grid stability with high renewable penetration and develops innovative solutions using advanced data analytics. Best Paper Award for Big Earth Data (2025) for wind generation dataset research Best Paper Award in International Conference on Power, Energy and Electrical Engineering (2025) Second Best Paper Award in International Conference on Renewable Energy Research (2024) Top Downloaded Article in IET Smart Cities (2023) Top Downloaded Article in IEEJ Transactions (2022) Fujimoto's research bridges theoretical statistical methods with practical energy system applications, contributing significantly to Japan's efforts in smart grid development and renewable energy integration. His work often involves collaboration with industry partners and government research organizations to address real-world power system challenges.

• Software Engineering
• Information Security
• Computer Systems
• +5 more

Hironori Washizaki is a Professor at Waseda University's School of Fundamental Science and Engineering, Department of Information and Computer Science, and serves as Director of the Global Software Engineering Laboratory. He also holds a visiting professorship at the National Institute of Informatics and serves as outside director at SYSTEM INFORMATION CO.,LTD. and eXmotion Co., Ltd. With a Doctorate in Information and Computer Science from Waseda University (2003), he has established himself as a leading researcher with 384 publications and an h-index of 36 according to Google Scholar. His research spans multiple domains including software engineering methodologies, security patterns, programming education, and the application of machine learning to software development. His work has significantly contributed to the fields of software patterns, quality assurance, and educational tools for programming. With over 20 years of academic experience, his career progressed from Research Associate (2002-2004) to Assistant Professor (2004-2008), Associate Professor (2008-2016), and Professor (2016-present). Washizaki's recent publications demonstrate a strong focus on applying AI and machine learning techniques to software engineering challenges, including prompt engineering patterns, program repair methods, and vulnerability assessment. His work bridges theoretical research with practical applications in both educational and industrial contexts, particularly in B2B software development and programming education for diverse age groups. KDDI Foundation Award (2022) Spirit of the Computer Society Award (2022) Distinguished Contributor, IEEE Computer Society (2022) IEEE Computer Society Golden Core Member (2022) Fellow, International Academy, Research, and Industry Association (2022) Computer Research Contribution Award, APSCIT (2016) Washizaki has served as chair of the IEEE CS Japan Chapter and SEMAT Japan Chapter, director of ACM-ICPC 2014 Asia Regional Tokyo Contest, and Convenor of ISO/IEC/JTC1/SC7/WG20. His editorial work includes positions at IEICE Transactions on Information and Systems and International Journal of Software Engineering and Knowledge Engineering. His leadership extends to programming education initiatives like SamurAI Coding, demonstrating his commitment to developing the next generation of software engineers.

• Electronic Design Automation
• VLSI Design
• Computer Systems
• +7 more

Shinji Kimura is a Professor at Waseda University's Faculty of Science and Engineering, specializing in VLSI design and electronic systems. He holds a Doctor of Engineering from Kyoto University and has been with Waseda since 2002, previously serving as Associate Professor at Nara Institute of Science and Technology (1993–2002) and Assistant Professor at Kobe University (1985–1993). Kimura's research spans low-power circuit design , approximate computing , FPGA optimization , video coding (HEVC) , and hardware acceleration for AI . His work focuses on energy-efficient architectures for applications like neural networks, computer vision, and ultra-high-definition video processing. Recent publications emphasize hardware-efficient multipliers, neural network compression, and 3D-stacked memory systems. Awards include the LSI IP Design Award (2000, 1999) and the Information Processing Society of Japan Encouragement Award (1993). He leads projects on HEVC encoding/decoding, non-volatile memory optimization, and 3D integrated circuits, with VLSI implementations achieving real-time 8K video processing.