جستجوی استاد راهنمای دانشگاهی

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.

• Time Series Analysis
• Big Data Analytics
• Predictive Modeling
• +۳ مورد دیگر

Naoki Yoshinaga is a tenured Associate Professor at the Institute of Industrial Science, The University of Tokyo, with extensive experience in natural language processing and computational linguistics. He has held academic positions since 2008 and currently leads research on pragmatic NLP models and multilingual systems. PhD in Computer Science, The University of Tokyo (2005-2008) MSc in Information Science (2000-2002) BSc in Information Science (1996-2000) His research focuses on mechanistic interpretability in NLP models, multilingual/multimodal NLP , and efficient model design using trie structures and conjunctive features. He also investigates knowledge acquisition from social data and evaluation metrics for language generation . Recent publications include work on neuron empirical gradient analysis (ACL-25), multilingual knowledge representation (EACL-24), and compact embedding methods (CoNLL-24). His research has been funded by multiple grants, including the University of Tokyo Excellent Young Researcher program and JSPS fellowships. Committee Special Award, Association for NLP (2023) JSAI SIG Research Award (2022) Best Interactive Award, DEIM Forum (2019, 2016) He developed widely-adopted NLP tools like pecco (fast classification library), RenTAL (LTAG-to-HPSG grammar converter), and J.DepP (Japanese dependency parser). His lab emphasizes strong equivalence in formalism comparisons and pragmatic model design .

• Natural Language Processing
• Computational Linguistics
• Multilingual and Multimodal NLP
• +۴ مورد دیگر

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.

• Data science
• Machine learning
• Business analytics
• +۱۰ مورد دیگر

Hayato Yamana serves as Professor at Waseda University's Faculty of Science and Engineering and concurrently holds the position of Vice President for IT Promotion and Chief Information Officer since October 2020. His academic journey began with a Dr. Eng. degree from Waseda University in 1993, followed by positions at the Electrotechnical Laboratory of MITI, before joining Waseda University as Associate Professor in 2000 and becoming full Professor in 2005. He has held significant leadership roles including Director of the Database Society of Japan and the Information Processing Society of Japan, as well as Vice Chair of IEICE's Information and Communication Society. Waseda University, Faculty of Science and Engineering (2005-Present) National Institute of Informatics, Visiting Professor (2005-Present) Waseda University, Vice President for IT Promotion (2020-Present) Deputy Chief Information Officer (2015-2020) His research spans homomorphic encryption, big data analysis, and computer architecture, with notable contributions in privacy-preserving computation, recommender systems, and secure data processing. His work bridges theoretical cryptography with practical applications in smart cities, healthcare, and e-commerce security. Recent publications demonstrate strong focus on accelerating homomorphic encryption operations, improving recommendation system diversity, and developing novel authentication mechanisms. Analysis of his 15 most recent publications reveals consistent emphasis on privacy-preserving technologies (particularly homomorphic encryption applications), innovative recommender system architectures, and biometric security solutions. His research group produces highly cited work at the intersection of cryptography, machine learning, and systems security, with practical implementations in real-world scenarios including smart grids, e-commerce, and healthcare. Fellow, Information Processing Society of Japan (IPSJ), 2020 Golden Core Award, IEEE Computer Society, 2018 Fellow, Institute of Electronics, Information and Communication Engineers (IEICE), 2018 IBM Faculty Award, 2009 Multiple Best Paper Awards from IEICE, IPSJ, and ITE Yamana has secured substantial research funding for projects in homomorphic encryption, smart city infrastructure, and privacy-preserving systems. His leadership extends to advising numerous doctoral students and directing major research initiatives including the Smart Systems and Services Innovative Professional Education Program. He maintains active collaborations with industry partners through projects involving secure computation and data analytics. His research group operates at the forefront of secure computing, with specialized laboratories focused on homomorphic encryption acceleration, privacy-preserving machine learning, and secure mobile authentication. The team actively develops practical implementations of cryptographic protocols for real-world applications in healthcare, finance, and smart city infrastructure, bridging theoretical cryptography with deployable security solutions.

• Homomorphic Encryption
• Big Data Analysis
• Database Systems
• +۶ مورد دیگر

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.

• Intellectual Property Law
• Copyright Law
• Information Law
• +۳ مورد دیگر

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.

• Neural Networks
• Genetic Algorithms
• System Identification and Control
• +۷ مورد دیگر

Takuya Taniguchi is an Associate Professor at the Center for Data Science, Waseda University, where he has been employed since 2019, first as an Assistant Professor (2019-2021) before promotion to his current non-tenure track position. His interdisciplinary research bridges organic chemistry, materials science, and data science, with a focus on developing and analyzing functional organic materials, particularly photo-responsive molecular crystals. He maintains active collaborations with research groups including Hideko Koshima and Toru Asahi, and serves on professional committees such as the Manufacturing Industry AI Promotion Association. Education Doctor of Engineering, Waseda University (2019) Graduate studies at Waseda University's Graduate School of Advanced Science and Engineering Undergraduate studies at Waseda University's School of Advanced Science and Engineering, Department of Life Science and Medical Bioscience Research Focus Professor Taniguchi's work centers on structural organic chemistry and physical organic chemistry , with particular emphasis on organic functional materials and the application of materials informatics to crystal engineering. His research investigates how molecular structure influences macroscopic mechanical properties, especially photo-mechanical behaviors in organic crystals. He has pioneered the use of machine learning techniques to predict crystal properties, optimize materials performance, and design novel functional materials with applications in soft robotics and energy conversion. His recent work demonstrates a clear progression from fundamental studies of photo-mechanical crystals toward increasingly sophisticated applications of machine learning in materials science. The 15 most recent publications reveal a strong focus on neural network potentials for crystal property prediction, optimization of photo-actuated materials, and exploration of phase transitions in molecular crystals. This research trajectory shows consistent innovation in combining experimental chemistry with advanced computational methods. Awards and Recognition Inoue Research Encouragement Prize (2019) Ono Azusa Memorial Award from Waseda University (2019) Student Presentation Award at Japan Chemical Society 99th Spring Annual Meeting (2019) Poster Presentation Award at Chirality 2017 Multiple poster and presentation awards at international crystallography conferences Research Leadership Dr. Taniguchi leads multiple research projects funded by JSPS, JST, and industry partners including ENEOS Corporation and Sumitomo Foundation. His current projects include 'Efficient crystal structure prediction for organic porous materials,' 'Machine learning simulation of HOF material stability,' and 'Machine learning application for organic solid-phase transition.' He has successfully secured competitive funding including JST ACT-X and JSPS Early-Career Scientist grants. His work has received significant media attention, with coverage in Nikkan Kogyo Shimbun and Kagaku Kogyo Nippo highlighting breakthroughs in light-driven organic crystals with 3.7x improved output force. Academic Contributions Beyond research, Professor Taniguchi teaches extensively in Waseda's Global Education Center, offering courses in data science, statistical analysis with R, and statistics literacy across multiple academic quarters. He has contributed chapters to technical publications on process informatics, Bayesian optimization, and crystallization process design. His scholarly impact is evidenced by an h-index of 11 (Google Scholar) with 581 total citations, demonstrating significant influence in the emerging field of materials informatics for organic crystals.

• Organic Functional Materials
• Materials Informatics
• Structural Organic Chemistry
• +۴ مورد دیگر

Dr. Yuko Fukuyama is an Associate Professor at Waseda University's School of International Liberal Studies since 2022, with additional appointments at Università degli Studi di Firenze (2023). Her research focuses on Ancient Roman History and Cultural Memory in Mediterranean and Japanese contexts.

• Ancient Roman History
• Cultural Memory
• Epigraphy
• +۴ مورد دیگر

Professor Tomoji Kishi is a distinguished faculty member at Waseda University's School of Creative Science and Engineering, where he has been serving since 2009. Previously, he held academic positions at Japan Advanced Institute of Science and Technology (2003-2009) following a 21-year career at NEC Corporation (1982-2003). He earned his Ph.D. in Information Science from Japan Advanced Institute of Science and Technology in 2002, building upon his earlier engineering graduate studies at Kyoto University. Professor Kishi's research focuses on software engineering, particularly in software product line development, model checking, formal verification, and aspect-oriented modeling. His work bridges theoretical formal methods with practical applications in embedded systems, automotive software, and IoT technologies. He has made significant contributions to scalability challenges in model checking for configurable systems and has pioneered approaches to variability management and approximate modeling techniques. His publication record demonstrates remarkable consistency and evolution, with 42 papers and 153 citations according to Scopus data (h-index: 7), spanning from foundational work in software architecture in the 1990s to cutting-edge research on AI-enhanced verification methods in 2025. His recent work shows increasing application of machine learning techniques to traditional formal methods problems, particularly in the context of highly configurable systems and IoT applications. ITS Standardization Activity Merit Prize (2022) from Society of Automotive Engineers of Japan IPSJ/ITSCJ Standardization Contribution Award (2017) IPSJ/ITSCJ Project Editor Award (2016 and 2013) Information Processing Society of Japan Society Activity Contribution Award (2010) IPA/SEC Journal Best Paper Award (2007) Information Processing Society of Japan Yamashita Memorial Research Award (1998) Professor Kishi has led multiple JSPS-funded research projects, including recent work on 'variability management methods prioritizing usability through variability mining' (2020-2023) and 'utility-first modeling method' (2017-2020). His industry collaborations, particularly with automotive systems developers, demonstrate the practical impact of his research. He maintains active membership in major professional societies including IEEE Computer Society, ACM, and the Information Processing Society of Japan.

• Software Engineering
• Model Checking
• Formal Verification
• +۴ مورد دیگر

Kenichi Oyaizu is a Professor in the Department of Applied Chemistry at Waseda University's School of Advanced Science and Engineering. With over 30 years of academic career, he has established himself as a leading researcher in polymer chemistry, with particular expertise in functional polymers for energy applications. His research group has produced over 300 publications with more than 12,000 citations, demonstrating significant impact in the field. Professor Oyaizu received his education entirely at Waseda University, completing his undergraduate studies in the Department of Applied Chemistry (1986-1990), followed by graduate work in the same department where he earned his PhD in Engineering (1990-1995). His academic journey progressed from JSPS Research Associate to his current position as Professor, with appointments at Tokyo University of Science along the way. Oyaizu's research focuses on polymer synthesis and functional polymers, with particular emphasis on energy storage materials, hydrogen storage systems, high refractive index polymers, and organic battery technologies. His work bridges fundamental polymer chemistry with practical applications in sustainable energy, demonstrating strong interdisciplinary approach that combines materials science, electrochemistry, and informatics. Analysis of his recent publications reveals a strong trend toward developing advanced polymer materials for energy applications, with particular focus on high refractive index polymers for optoelectronics and robust organic materials for batteries. His research increasingly incorporates materials informatics approaches, as evidenced by several publications applying AI and machine learning to polymer design and property prediction. Yamazaki Sho Award (2022) - Polymers for Reversible Hydrogen Storage Society of Polymer Science Japan Award (2022) - Functional Polymers for Energy Storage Minister of Education Science and Technology Prize (2013) Oleo Science Award (2007) Chemical Society of Japan Young Chemists Award (2002) Professor Oyaizu maintains active leadership roles in the academic community, serving on editorial boards and as committee member for multiple professional societies including the Society of Polymer Science Japan and Chemical Society of Japan. His research is supported by significant grants that enable his team to pursue innovative projects at the intersection of polymer science and sustainable energy technologies. The Oyaizu laboratory operates as a dynamic research environment where fundamental polymer chemistry meets practical energy applications, with particular emphasis on developing materials that address global energy challenges.

• Polymer Chemistry
• Functional Polymers
• Energy Storage Materials
• +۵ مورد دیگر

Satoru Hayamizu is a Professor at Waseda University 's Green Computing Systems Research Organization , with a career spanning over four decades. His research focuses on Audio-Visual Speech Recognition , Machine Learning , and Medical Informatics , as evidenced by 126 publications and an h-index of 18. Education: The University of Tokyo (PhD in Mechanical Engineering) Prior affiliations: Gifu University (2002-), National Institute of Advanced Industrial Science and Technology (1981-2001) Research Interests include: Audio-visual speech recognition with sparse representation and DNN techniques Development of low-cost CNN-based road condition detection systems Swallowing function evaluation using acoustic and image processing Human behavior analysis for service operation estimation Research Trends reveal consistent work in multimodal signal processing (2006-2024), deep learning applications (2012-2024), and medical diagnostic systems (2006-2017). His publications show integration of sparsity modeling (2012-2021), industrial equipment diagnostics (2018-2021), and social impact technologies (2013-2024). Research Projects funded by Japan Society for the Promotion of Science include: Swallowing timing estimation (2018-2021) Multimodal silent speech recognition (2016-2020) ICT-based piano learning systems (2013-2016) Keyword display mechanisms (2010-2012) Labs & Collaborations include partnerships with Satoshi Tamura (co-author on 12+ papers), Hidekazu Fukai , and Chiyomi Miyajima . His work bridges academic research and industrial applications , particularly in manufacturing AI (2024 book) and Timor-Leste infrastructure monitoring.

• Audio-Visual Speech Recognition
• Machine Learning
• Signal Processing
• +۹ مورد دیگر

Kusumoto Noriaki is a Professor at Waseda University's School of Education within the Faculty of Education and Integrated Arts and Sciences. With a Doctor of Science degree from Waseda University, he maintains an active research profile with teaching responsibilities for 2025 including Seminar in Cultural Sciences, Introduction to Information Processing, Cultural Sciences: Maps, Information Society/Information Ethics, and Application of Information Technology and Career courses. His academic work bridges educational technology and biological sciences, reflecting a unique interdisciplinary approach. Professor Kusumoto's research interests focus on educational technology and science education, particularly e-learning and Web-Based Training (WBT) systems. His work demonstrates significant contributions to language learning technologies, including mobile learning applications for English vocabulary acquisition, learning history analysis for personalized instruction, and corpus development for language proficiency assessment. He has also maintained a parallel research line in photosynthetic reaction centers of green sulfur bacteria, with publications dating back to the 1990s that examine electron transfer mechanisms and ferredoxin interactions. His publication record shows a clear evolution from biological research toward educational technology applications, with recent work (2003-2008) predominantly focused on language learning systems, data infrastructure for educational research (VALIS project), and information ethics. The 15 most recent publications reveal a strong emphasis on practical applications of technology in language education, with particular attention to mobile learning, learning analytics, and networked systems for language data collection and analysis. His work consistently addresses the intersection of technology, pedagogy, and practical implementation challenges. Professor Kusumoto has been involved in numerous research projects funded by the Japan Society for the Promotion of Science, including 'Data Collection and Annotation of Relatively Spontaneous Utterances by Japanese Learners of English' (2009-2013) and 'English learning with handheld devices' (2007-2009). His professional memberships include the Biophysical Society of Japan, Japanese Society for Biology Education, Japan Society for Educational Technology, and Information Processing Society of Japan, reflecting his dual expertise in both biological sciences and educational technology. As a concurrent researcher at the Waseda Research Institute for Science and Engineering and affiliated with the Global Education Center (2024-2026), Professor Kusumoto maintains an active research presence. His work on information ethics, particularly in educational contexts, demonstrates his commitment to addressing the social and ethical dimensions of technology in learning environments. His early research on photosynthetic reaction centers continues to inform his approach to science education methodology and biological curriculum development.

• Educational technology
• Science education
• e-learning
• +۴ مورد دیگر

Masato Uchida is a Professor at the School of Fundamental Science and Engineering, Waseda University, with a focus on information security and network systems. His career spans roles at Chiba Institute of Technology and Kyushu Institute of Technology, and he holds degrees in Engineering from Hokkaido University. Education: Master of Engineering (Hokkaido University, 2001), Doctor of Philosophy (Hokkaido University, 2005) His research interests include network security, peer-to-peer systems, machine learning for cybersecurity, and traffic analysis. His work addresses anomaly detection, malware classification, and resource allocation fairness in networks. Recent publications analyze adversarial machine learning, cloud service abuse, and domain parking security. Uchida's articles demonstrate expertise in cybersecurity, network modeling, and data science. He has received multiple awards for research excellence, including IEEE Outstanding Paper Awards and IEICE Communications Society honors. His leadership in committees like the Ministry of Internal Affairs and Communications' technical task forces highlights his policy influence. Scientific Awards: Outstanding Paper Award, IEEE International Conference on Teaching, Assessment, and Learning for Engineering (2020) MWS Outstanding Paper Award, Computer Security Symposium (CSS 2020) IEICE Activity Contribution Award (2016) Best Poster Award, SCIS & ISIS (2014) IEICE Network Systems Research Award (2012) He advises students in cybersecurity and collaborates on projects involving traffic load balancing, Android malware analysis, and cloud security. His professional memberships include IEEE, ACM, and the Information Processing Society of Japan.

• Information Security
• Network Security
• Peer-to-Peer Systems
• +۳ مورد دیگر

Professor Yuichiro Kawaguchi is a distinguished faculty member at Waseda University's Faculty of Commerce and Graduate School of Business and Finance, where he serves as a Professor specializing in Real Estate Economics and Financial Engineering. With decades of academic and professional experience, he has established himself as a leading expert in Japanese and Asian real estate markets, contributing significantly to both theoretical frameworks and practical applications in real estate finance. Education: 1979: National Defense Academy of Japan, Faculty of Engineering Professor Kawaguchi's research primarily focuses on Real Estate Economics and Real Estate Financial Engineering, with particular emphasis on market dynamics, risk management, and valuation methodologies. His work bridges theoretical finance concepts with practical real estate applications, examining how spatial factors, market cycles, and institutional frameworks influence property markets. He has pioneered approaches to real options analysis in real estate development and has extensively studied the Japanese housing market's unique characteristics and challenges, including its prolonged stagnation period and recovery patterns. His research integrates econometric techniques with financial theory to develop more accurate forecasting and valuation models for commercial and residential properties, with recent work incorporating big data analytics and text mining to understand market sentiment and its impact on real estate investment trusts. Analysis of Professor Kawaguchi's extensive publication record reveals a consistent progression from traditional valuation methods toward more sophisticated approaches incorporating spatial analysis, real options theory, and market microstructure considerations. His interdisciplinary research connects economics, finance, urban planning, and data science to address complex questions in real estate investment and policy, with particular focus on the Japanese market context and its implications for other Asian economies. Scientific Awards: Japan Society of Civil Engineers Technology Development Award (Geographic Information System for Urban Railway Planning) - May 2003 Applied Surveying Society Paper Encouragement Award - 1992 First Applied Surveying Paper Best Award - November 1985 Professor Kawaguchi has supervised numerous graduate students through research guidance seminars at Waseda University and has secured significant research funding through multiple Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research projects. His current research projects include 'Social Dynamics of Real Estate Markets' (2014-2017) which applies text mining to analyze the relationship between news sentiment and real estate stock prices, and 'Long-term perspectives on the housing price and financial system in Japan' (2012-2015) which examines the relationship between soaring property prices and investment inhibition in Japan's economic growth context. As Director of the Institute of Real Estate Studies at Waseda University (2022-2026), Professor Kawaguchi bridges academic research with practical applications in the real estate industry, contributing to scholarly knowledge and professional practice through publications, committee work with government agencies including the Cabinet Office and Ministry of Land, Infrastructure, Transport and Tourism, and industry collaborations with major financial institutions.

• Real Estate Economics
• Real Estate Financial Engineering
• Public Economics
• +۳ مورد دیگر

Manabu Kobayashi is a Professor at the Center for Data Science of Waseda University, with previous faculty roles at Shonan Institute of Technology (1998-2014). His research spans data mining, machine learning, and information theory, with a focus on applications in document classification, ECOC frameworks, and latent structural models. Current Affiliation: Waseda University (2018-present) Previous: Shonan Institute of Technology (2002-2014) Research Interests: Specializes in distance metric learning, latent class modeling, and fault diagnosis systems using probabilistic frameworks. Key areas include: ECOC (Error-Correcting Output Codes) optimization Collaborative filtering for recommendation systems Reconfigurable logic circuits using DG-CNTFETs Privacy-preserving distributed linear regression Scientific Awards: PC Conference Best Paper Award (2025) World CIST'18 Best Paper Award IEICE Achievement Award (2017) 74th Information Processing Society of Japan Conference Excellence Award (2012) Article Trends: Recent work focuses on latent structure analysis for relational data (2025), ECOC performance with noisy classifiers (2023), and flipped classroom effectiveness through log-based grouping (2022-2025). Earlier contributions include reconfigurable logic circuits (2013-2014) and probabilistic fault diagnosis (2011-2012).

• Data Mining
• Machine Learning
• Information Theory
• +۴ مورد دیگر