جست‌وجوی استاد و پژوهشگر

Synge Todoمشاهده پروفایل

استاد

• Quantum Many-Body Physics
• Computational Physics
• Quantum Computing
• +۵ مورد دیگر

Synge Todo is a Professor in the Department of Physics, Graduate School of Science at the University of Tokyo , with joint appointments at the Mathematics and Informatics Center , Institute for Solid State Physics , Institute for Physics of Intelligence , Quantum Software Project , and Next-Generation AI Research Center . Born in 1968, he earned his B.Sc. and Ph.D. from the University of Tokyo and subsequently held post-doctoral positions at ETH Zürich. Education Ph.D. (Science), University of Tokyo, 1996 B.Sc. (Physics), University of Tokyo, 1991 Research Interests Todo’s research integrates quantum many-body physics , computational physics , and quantum computing . He develops advanced Monte-Carlo algorithms , tensor-network techniques , and renormalization group methods to study strongly correlated electron systems , lattice QCD , quantum phase transitions , and machine-learning applications in physics . His recent work explores fault-tolerant quantum computing architectures , non-variational quantum ground-state preparation , and universal scaling laws in deep neural networks . Scientific Awards Prizes for Science and Technology, The Commendation for Science and Technology by MEXT Japan (April 2019) Grants & Collaborations He currently leads several JSPS KAKENHI projects, including “ Quantum-circuit design for computational materials science ” (2023-26) and “ Enhancement of detailed-balance-violating MCMC methods ” (2020-24). He also co-leads interdisciplinary teams focusing on data assimilation for materials discovery and scalable high-performance computing . Laboratories & Software Todo heads research activities in the HΦ quantum lattice model solver and the MateriApps portal, providing open-source tools for large-scale simulations in condensed-matter and materials science.

• Speech Science
• Spoken Dialogue Systems
• Human-Agent / Human-Robot Interaction
• +۷ مورد دیگر

Hideaki Kikuchi is a Professor at Waseda University’s Faculty of Human Sciences, Japan, holding a Ph.D. in Information Science from the same university. He specializes in speech science, spoken dialogue systems, and human-agent interaction, with extensive work on prosody, infant-directed speech, and real-time MRI articulatory analysis. Education: Ph.D. (Information Science), Waseda University Research Interests: His research spans Speech Science , Spoken Dialogue Systems , Human-Agent Interaction , Kansei Informatics , Intelligent Informatics , and Language Acquisition . He investigates empathic dialogue generation, prosodic entrainment, infant speech development, and multimodal communication robots. Publications Trend: Recent articles focus on user empathy toward dialogue systems, linguistic alignment in chat-oriented robots, real-time MRI visualization of articulation, and developmental phonetic studies in Japanese children, indicating a strong emphasis on both technological innovation and cognitive speech science. Awards: Information Processing Society of Japan, 53rd National Convention Excellence Award (1996) Grants & Projects: JSPS KAKENHI "Real-time MRI database of articulatory movements of Japanese" (2020-2024) JSPS KAKENHI "Development of protocol of effective social work interview for older adults with dementia" (2019-2022) VR orality factors project (2017-2020) Labs & Teams: He leads the Speech & Interaction Research Group within Waseda’s Faculty of Human Sciences, collaborating with interdisciplinary members on spoken corpora, dialogue systems, and multimodal interaction experiments.

• Sentiment Analysis
• Emotion Detection
• Digital Humanities
• +۱۰ مورد دیگر

Emily Ohman is an Associate Professor at Waseda University's School of International Liberal Studies since April 2025, with additional roles as Title of Docent in Language Technology at the University of Helsinki (2024–) and Visiting/Adjunct Associate Professor at LUT University (2024–2029). Her research bridges Digital Humanities, Computational Linguistics, and Social Science, focusing on emotion detection , sentiment analysis , and machine learning applications across languages like English, Japanese, and Finnish. PhD in Language Technology (University of Helsinki, 2021) MA in English Linguistics (Linnaeus University, 2015) 30 ECTS pedagogy certification (HYPE, 2016) Her scholarly work includes creating foundational tools like the XED multilingual dataset and SELF/FEIL Finnish lexicons , alongside pioneering research on emotion dynamics in literature, politics, and social media. Recent projects explore AI ethics , cross-cultural emotional semantics , and hate speech moderation . Key publications span 15+ years in emotion detection, gamified annotation, and computational literary studies Awarded for pedagogical innovation (Waseda e-Teaching Award, 2023) Active in curriculum development for computational methods in humanities Peer review/editorial roles for Digital Humanities Quarterly , IEEE Transactions on Affective Computing , and conference committees

• Educational technology
• Second Language Acquisition
• Artificial Intelligence in Education
• +۴ مورد دیگر

John Maurice Gayed is an Associate Professor at the Global Education Center of Waseda University . Holding a PhD from Tokyo Institute of Technology (2023) , he specializes in Educational Technology , focusing on AI-driven tools for language learning and metacognitive strategies. Research Themes : AI writing assistants, equity in educational technology, cognitive load reduction for EFL learners. Grants : Japan Society for the Promotion of Science (JSPS) Grant (2022.04–2025.03) for AI-based writing assistant studies. Courses Taught : Academic Writing and Discussion in English (Alpha/Beta) for undergraduate and retaker students. His publications (9+3) span Computer Science , Linguistics , and Education , with key trends including: AI-based writing tools (e.g., AI KAKU, Grammarly) for EFL learners. Metacognitive training in online learning environments. Equity implications of educational technology (Matthew effect in CALL). Twine for nonlinear educational storytelling. Climate risk mitigation tools for elderly populations. MOOCs and blended learning in cross-cultural contexts. Grant Details : His JSPS-funded project investigates AI writing assistants' long-term impact on EFL writing proficiency. Collaboration with May Kristine Jonson Carlon and Jeffrey S. Cross is frequent, with tools like AI KAKU and metacognitive tutors being central to his work.

• Public Health
• Social Welfare
• Hygiene and Public Health
• +۶ مورد دیگر

Atsushi OGIHARA is a Professor at Waseda University's School of Human Sciences, specializing in public health, social welfare, and health data analysis. With a Doctor of Medicine from Juntendo University, his research spans multiple domains including traditional Chinese medicine, disaster recovery, vaccination studies, and mental health. His educational background includes: Graduate School of Medicine, Juntendo University - Department of Social Medicine University of Tsukuba Graduate School of Health and Sport Sciences - Master's Program in Health Education Tokyo University of Science School of Science and Engineering - Department of Applied Biological Science Professor OGIHARA's research interests focus on the intersection of public health, social welfare, and data-driven approaches to healthcare. He has made significant contributions to understanding health risk factors through advanced data analysis techniques, particularly in the context of wearable devices and traditional medicine systems. His work on social capital and mental health, especially in post-disaster contexts like the Fukushima nuclear accident, has provided valuable insights for community recovery efforts. He has also conducted extensive research on HPV vaccination communication and cervical cancer education in Japan. His scholarly output shows a clear trajectory toward integrating technology with public health practice, with recent work focusing on AI-driven health analytics, decentralized health data systems, and precision healthcare approaches. This evolution reflects the growing importance of data science in addressing complex public health challenges. Among his notable recognitions is the United Nations University Akino Memorial Research Fellowship awarded in 2004, highlighting early recognition of his research potential. Professor OGIHARA has been actively involved in community service, including serving as: Member of Tokorozawa City Planning Basic Policy Revision Committee (since 2018) Vice Chairman of Tokorozawa City Health, Medical and Welfare Planning Promotion Committee (since 2016) He is affiliated with multiple professional organizations including the Japanese Home Education Society, Japan Society for Community Welfare Studies, Japanese Association of Public Health, Central Eurasia studies society, Japanese Society of Social Medicine, and Japan Society for the Study of Social Welfare.

• Applied mathematics
• Statistics
• Information theory
• +۸ مورد دیگر

Toshiyasu Matsushima is a Professor at Waseda University's Faculty of Science and Engineering, School of Fundamental Science and Engineering. He holds a Doctor of Engineering degree from Waseda University and has maintained an active research career spanning several decades. His educational background includes: 1991: Graduate School, Division of Science and Engineering, Waseda University 1978: Faculty of Science and Engineering, Waseda University Professor Matsushima's research spans multiple disciplines in applied mathematics and information science. His primary research interests include information theory, coding theory, statistical science, learning theory, intelligent informatics, data science, and information security. His work bridges theoretical foundations with practical applications in data compression, machine learning, privacy-preserving technologies, and communication systems. His recent publications demonstrate consistent innovation in Bayesian decision theory, context tree modeling, private information retrieval systems, decision tree algorithms, and image processing techniques. The research shows a clear trajectory toward optimizing algorithms for data analysis while addressing contemporary challenges in privacy-utility trade-offs and handling noisy data environments. Professor Matsushima is an active member of numerous professional societies including the Japanese Society for Industrial and Applied Mathematics, Applied Statistics Society, Operations Research Society of Japan, Quality Control Society, Artificial Intelligence Society, Information Processing Society, Information Theory and its Applications Society, IEEE, and the Institute of Electronics, Information and Communication Engineers. With over 190 publications and a Scopus h-index of 10, his scholarly contributions have established him as a significant figure in information theory and its applications. His research continues to influence both theoretical developments and practical implementations in data science and information engineering.

• Intelligent informatics
• Safety engineering
• Social systems engineering
• +۸ مورد دیگر

Reiko HishiYama is a Professor at WASEDA University's Faculty of Science and Engineering, School of Creative Science and Engineering. With a Doctor of Informatics from Kyoto University (2005), she has established herself as a leading researcher in intelligent informatics, safety engineering, social systems engineering, and educational technology. Her educational background includes: Doctor of Informatics from Kyoto University (2005) HishiYama's research spans multiple interdisciplinary fields with a strong focus on the intersection of technology and society. Her primary research interests include artificial intelligence, social informatics, business informatics, communication design, computer vision, mobile computing, and IoT (Internet of Things). She particularly focuses on how these technologies can be applied to community management, tourism development, and cultural preservation through innovative approaches such as augmented reality and network analysis. Analysis of her recent publications reveals a consistent focus on applying network motif analysis to diverse domains including tourism, luxury goods markets, and community management. Her work increasingly integrates augmented reality technologies with traditional cultural experiences and demonstrates a strong commitment to practical applications that address real-world community challenges, particularly in low-digitalized environments. Her scientific achievements have been recognized with numerous prestigious awards: The 12th FOST Award (2019) The 6th WASEDA e-Teaching Award (2018) The 7th Career Development Essay Contest for Young Professionals and Women Engineers (2015) The 4th FOST Award (2011) Pacific Rim International Workshop on Multi‐Agents PRIMA Runner Up Paper Prize (2004) The 1st KK-MAS Competition Grand Prize (2001) As an educator and researcher, Professor HishiYama has been instrumental in developing innovative teaching methods, particularly in AI ethics education using the case method. Her professional engagements extend beyond academia through various committee memberships including SoftBank Corp. External Director, HAYAO NAKAYAMA Foundation for Science & Technology and Culture Planning Committee, and ASAHI INTELLIGENCE SERVICE CO., LTD. External Director. She maintains active roles in numerous professional societies including IEICE, IEEE, and ACM. Her research laboratory (HishiYama Lab) focuses on developing social support systems through the designable evaluation network framework, with applications in community management, tourism development, and multilingual communication. The lab has produced numerous publications and practical applications that bridge theoretical research with real-world implementation.

• polymer materials
• biophysics
• chemical physics
• +۱۲ مورد دیگر

Sadaki Samitsu is a Professor (non-tenure-track) at Waseda University's Graduate School of Advanced Science and Engineering and Faculty of Science and Engineering (Department of Nanoscience and Nanoengineering). Additionally, he serves as a Principal Researcher at Japan's National Institute for Materials Science in the Data-driven Polymer Design Group , with prior roles at Kyoto University and NIMS. Education : PhD in Applied Physics (2006.03), Graduate School of Engineering, The University of Tokyo MS in Advanced Materials Science (2003.04), Graduate School of Frontier Sciences, The University of Tokyo BS in Applied Physics (2001.04), School of Engineering, The University of Tokyo His research bridges polymer materials and soft matter physics , focusing on materials informatics , porous materials , and phase separation mechanisms. Key applications include thermal insulation , sound absorption , and photonic devices leveraging X-ray CT and refractive index engineering . Recent work highlights machine learning-driven inverse design of auxetic metamaterials, self-healing polymer gels via physical entanglements, and photocatalytic nanofiber membranes for wastewater treatment. His publications demonstrate expertise in combining structural color , nano-crystallization , and adhesive fracture mechanics . Scientific Awards : SPSJ Publicity Committee Award (2018) Young Scientist Lecture Award (2017) Poster Presentation Award (2016) NIMS President Award for Young Scientists (2015) He mentors researchers in polymer hybrid materials , with contributions to epoxy adhesive toughening via polyrotaxane dispersion, durable superhydrophobic composites , and active learning frameworks for optimizing adhesive formulations from small datasets.

• Combinatorial Algorithms
• Decision Diagrams
• Blockchain Technology
• +۴ مورد دیگر

KAWAHARA Jun is an Associate Professor at the Department of Communications and Computers Engineering, Graduate School of Informatics, Kyoto University. He leads research in combinatorial algorithms and decision diagram applications. Research focuses on combinatorial reconfiguration, network reliability, and blockchain algorithm design Key technical contributions include ZDD-based enumeration frameworks His recent publications (2020-2025) span: Graph enumeration techniques using decision diagrams Reconfiguration problem algorithms Blockchain network optimizations Combinatorial optimization applications Notable awards include: 2024 Japan Society for Artificial Intelligence Best Presentation Award 2022 LA/EATCS-Japan Presentation Award 2019 Japanese Society for Computation and Statistics Award 2008 COMP-NHC Best Paper Award Current grants include multiple JSPS-funded projects in combinatorial algorithms and blockchain research. He collaborates with researchers like Shin-ichi Minato and Masaharu Kasahara on graph theory and network security applications.

• Theory of Informatics
• Computer Systems
• Distributed Algorithms
• +۲ مورد دیگر

Professor in the Department of Information Engineering, Graduate School of Engineering, specializing in distributed algorithms and autonomous mobile robotics. Research focuses on self-stabilizing systems for luminous robots, fault tolerance, and grid-based coordination with applications in dynamic network environments. Degrees: Doctor (Engineering) and Master (Engineering) from Osaka University Professional Memberships: ACM, IEEE Computer Society, Information Processing Society of Japan (IPSJ), Institute of Electronics, Information and Communication Engineers (IEICE) Research centers on theoretical informatics and computer systems, particularly self-stabilizing distributed algorithms for robot swarms. Key areas include visibility problems in luminous robots, Byzantine fault tolerance, and uniform deployment in bipartite graphs. Recent work addresses defected-view models and st-edge-ordering via ear decomposition, emphasizing algorithmic solvability under asynchronous conditions. Publications since 2022 reveal strong trends in mobile robotics (70% of output) and distributed computing (30%), with subfield emphasis on fault tolerance (25%), grid networks (20%), and self-stabilization (15%). International collaborations with Israeli and Japanese researchers dominate recent work. Information and System Society Contribution Award (2024) - For editorial contributions to English-language journals 13th Telecommunications Advancement Foundation Award (1998) - For student research in telecom systems Secured multiple competitive grants including JSPS KAKENHI projects (2020–2025) as co-PI on $$\text{JP20KK0232}$$ ($$\text{\$18.72M JPY}$$) for sustainable autonomous systems, and JST SICORP funding (2018–2022) for low-functionality robot swarms. Previously led NTT DoCoMo collaborations on fault-tolerant routing (2007–2008) and sensor networks (2004–2006). Serves as advisor to researchers like Yonghwan Kim and Masahiro Shibata through co-authored publications. Leads the Center for Research and Development in Higher Engineering-Education while chairing major symposia including the 26th International Symposium on Stabilization, Safety, and Security of Distributed Systems (SSS 2024). Organizes the Information Science Workshop series as committee chair and participates in program committees for CANDAR and IEEE conferences.

• Distributed Systems
• Network Systems
• Operating Systems
• +۳ مورد دیگر

Hiroshi Matsuo is a Professor in the Department of Information Engineering at Nagoya Institute of Technology's Faculty of Engineering, with additional affiliations in the Graduate School of Engineering (Network Program) and Information Technology Center. His research focuses on distributed systems, network architecture, and operating systems with practical applications in cloud infrastructure. Education: Doctor of Engineering, Nagoya Institute of Technology (1989) Master of Engineering, Nagoya Institute of Technology Bachelor of Engineering, Nagoya Institute of Technology (1983) Matsuo's research centers on performance optimization in virtualized environments, particularly addressing bottlenecks in network I/O, distributed databases, and cloud-native applications. His work bridges theoretical informatics with practical system implementations, emphasizing real-world scalability and efficiency in high-throughput computing environments. Key contributions include novel caching mechanisms, transaction processing acceleration, and resource contention solutions for virtual network functions. Recent publications demonstrate consistent focus on network function virtualization and distributed systems, with increasing emphasis on hardware-aware optimizations and transparent proxy architectures. His team's work shows strong progression from foundational operating system research toward cloud-native infrastructure solutions, maintaining relevance in both academic and industrial contexts. Awards: IEEE NFV-SDN 2018 Best Paper Award 12th IEICE Communications Society Paper Award (2017) 2022 IEICE Information and Communication Management Research Award 1st International Conference on Networking and Computing Best Paper Award (2010) JAWS2010 Excellent Paper Award Matsuo has supervised numerous graduate students evident through co-authorship patterns in publications, particularly in network systems and distributed computing. His research has been supported by institutional projects on distributed processing frameworks, though specific grant details aren't publicly documented. He maintains active industry collaborations through his work on Microsoft Defender integration and enterprise networking solutions. His laboratory within Nagoya Institute of Technology's Network Field focuses on practical systems research, combining DPDK-based implementations with theoretical performance modeling. Current work emphasizes cache optimization for virtualized network functions and transaction processing acceleration in distributed databases, maintaining strong ties to industry partners through the Information Technology Center.

• Medical Imaging
• Pathology
• Artificial Intelligence
• +۳ مورد دیگر

Kunihiro Inai is a Professor at the University of Fukui , specializing in medical imaging, pathology, and artificial intelligence applications. He holds a Doctor of Medicine from Fukui Medical University (1997) and has a long academic career spanning over three decades. Education: Graduated from Fukui Medical University Faculty of Medicine (1988), completed doctoral course at Fukui Medical University Graduate School (1997). Research Focus: Medical imaging AI, postmortem CT analysis, pancreatic tissue mechanics, sepsis diagnostics, and computational anatomy. Publication Trends: Recent work emphasizes AI-driven image analysis for thyroid/pancreatic/lung diagnostics, super-resolution CT techniques, and postmortem imaging-pathology correlation. Collaborative studies span radiology, pathology, and biomedical engineering. Academic Leadership: Principal investigator for multiple JSPS grants (total >48 million yen) and industry collaborations (e.g., Panasonic). Active in Japan Society of Medical Imaging Technology program committees and peer review. Teaching: Taught pathology, immunology, and medical diagnostics at institutions including University of Fukui, Nagoya Institute of Technology, and Tokyo University of Agriculture and Technology.

Hirokazu Takahashiمشاهده پروفایل

استاد

• Neuroscience
• Neural engineering
• Electrophysiology
• +۱۳ مورد دیگر

Hirokazu Takahashi is a Professor and Principal Investigator at the Department of Mechano-Informatics, Graduate School of Information Science and Technology, University of Tokyo. He leads the Bio-Intelligence Systems Lab, where his team approaches neuroscience from a mechanical engineering perspective. His research spans multiple scales of neural networks, from dissociated neuronal cultures to rodent and human brains. Born in Sendai, Japan (1975) B.S., M.S., Ph.D. in Mechanical Engineering from University of Tokyo (1998, 2000, 2003) Assistant Professor at Department of Mechano-Informatics (2004) Associate Professor (2019) Professor (2023) His research focuses on reverse engineering the brain to understand neural computation in the cerebral cortex. His lab develops novel experimental methods including high-density microelectrode arrays to obtain large-scale neural data, which is then analyzed using machine learning and AI techniques. Key research areas include emergent computing with dissociated neuronal cultures, auditory system processing in rodents, and epilepsy research in both animal models and humans. The lab investigates how intelligence, consciousness, and fine arts emerge from neural networks at various scales. His recent publications demonstrate significant advancements in understanding spontaneous beat synchronization in rats, physical reservoir computing with living neuronal cultures, and vagus nerve stimulation effects on cortical responses. His work bridges engineering, neuroscience, and informatics to extract design principles of brain function. Engineering Department Head Award (Research) for student Kiki Mamiya Professor Takahashi has supervised numerous students through graduation theses, master's theses, and doctoral research. His lab maintains extensive collaborations with institutions including ETH Zurich, Maxwell Biosystems, Monash University, and NTT. His research is funded through various grants supporting interdisciplinary work at the intersection of mechanical engineering and neuroscience. The Bio-Intelligence Systems Lab operates at the cutting edge of neural engineering, developing technologies such as high-density CMOS arrays with 10,000 recording sites and creating bio-silicon hybrid sensors. The team investigates neural representation with functional maps, learning-induced plasticity, auditory streaming, and mismatch negativity. Current projects include studying the effects of music on brain activity, developing seizure detection algorithms, and exploring the mechanisms of vagus nerve stimulation.

Hiroshi Suitoمشاهده پروفایل

استاد

• Mathematical modeling
• Numerical simulation
• Fluid-structure interaction
• +۵ مورد دیگر

Hiroshi Suito is a full Professor and Principal Investigator at Tohoku University's Advanced Institute for Materials Research (AIMR), leading the Suito Hiroshi Laboratory at the Katahira Campus. His research bridges mathematical sciences with clinical medicine and materials science through advanced computational modeling. He directs the Mathematics Collaboration Group and serves as the Tohoku University liaison for the Fujitsu x Tohoku University Discovery Intelligence Co-Creation Laboratory. Professor Suito's research focuses on mathematical modeling of complex systems, particularly in cardiovascular biomechanics and materials science. His work develops novel numerical simulation techniques for fluid-structure interaction problems, with applications ranging from blood flow dynamics in patient-specific aortic models to environmental fluid dynamics. He has pioneered approaches connecting mathematical models with clinical diagnostics, especially in understanding aortic pathological mechanisms. His research integrates traditional numerical methods with emerging machine learning techniques to address challenges in medical imaging and diagnostics. His publication portfolio reveals a strong emphasis on cardiovascular modeling, with recent work focusing on blood flow simulation, arterial geometry analysis, and computational approaches to clinical diagnostics. The research demonstrates consistent integration of mathematical rigor with practical medical applications, particularly in understanding the relationship between vascular geometry and hemodynamics. His team has developed specialized computational tools for patient-specific modeling that have contributed to both theoretical advances and potential clinical applications. Scientific Awards: Minister of Education, Culture, Sports, Science and Technology Award for Science and Technology (2019) for research into the elucidation of aortic pathological mechanisms using mathematics Mimura Prize for Mathematical Science Research Professor Suito has received substantial research funding as Principal Investigator for multiple major projects, including the JST-Moonshot Research and Development Program (since 2020), MEXT projects on nanoparticle process-structure correlation (since 2022), and several JST-CREST and JST-PRESTO projects dating back to 2007. His laboratory actively trains PhD candidates and technical assistants in computational mathematics and its applications. He has established strong interdisciplinary collaborations across Tohoku University, including with the School of Medicine, and maintains international partnerships with institutions including Waseda University, University of Tokyo, University of Electronic Science and Technology of China, and University College London. The Suito Hiroshi Laboratory serves as a hub for mathematical science collaboration, working closely with the Mathematical Science Open Innovation Center established at Tohoku University in December 2019. The laboratory participates in international programs such as the G-RIPS Sendai internship program and maintains active involvement in both theoretical developments and practical applications of mathematical modeling in medicine and materials science.

INUZUKA Nobuhiroمشاهده پروفایل

استاد

• Intelligent Informatics
• Database Systems
• Theoretical Informatics
• +۵ مورد دیگر

Nobuhiro Inuzuka is a Professor in the Department of Information Engineering within the Faculty of Engineering at Nagoya Institute of Technology, specializing in intelligent informatics and data-driven applications. His research integrates theoretical informatics with practical implementations across diverse domains including social networks, robotics, and human behavior analysis. Education: Doctor of Engineering, Nagoya Institute of Technology Master of Engineering, Nagoya Institute of Technology His research focuses on intelligent informatics with emphases on machine learning for social network analysis, safe reinforcement learning, and data mining applications. Key areas include developing algorithms for community behavior modeling, martial arts evaluation systems using sensor data, and recommender systems incorporating social dynamics. His work bridges theoretical computer science with real-world implementations in counseling systems and robotics. Recent publications (2024) demonstrate consistent innovation in applying machine learning to complex human-centric problems, particularly in social network dynamics, safe robotics navigation, and evaluation systems that replicate human judgment. Trends show increasing integration of multi-relational data mining with reinforcement learning frameworks across retail analytics, sports science, and mental health informatics. Scientific Awards: 2019 JSAI National Conference Excellent Award 2013 IPSJ National Conference Student Encouragement Award 2011-2010 Information Science Workshop Awards (multiple) 1996 Tokai Branch Electrical Societies Encouragement Award Professor Inuzuka has secured significant research funding including a 4-year Grant-in-Aid for Scientific Research (C) on human relationship analysis algorithms (2015-2019) and multiple JST programs for data mining applications. His student advisees have received national recognition including the IPSJ Student Encouragement Award. Current projects focus on scientific methodology development for student counseling and knowledge discovery systems. He leads research within Nagoya Institute of Technology's Creative Engineering-Education Promotion Center, directing teams that develop data analysis systems for social networks, martial arts evaluation, and evacuation planning. His laboratory combines theoretical informatics with practical implementations using multi-relational data mining and machine learning frameworks.