جست‌وجوی استاد و پژوهشگر

• Robotics
• Mechatronics
• Humanoid Robots
• +۴ مورد دیگر

Atsuo Takanishi is a distinguished Professor at Waseda University's Faculty of Science and Engineering, School of Creative Science and Engineering, with appointments in both the Department of Bioscience and Biotechnology and the Department of Modern Mechanical Engineering. With over 700 publications, 10,399 citations, and an h-index of 47, Professor Takanishi has established himself as a leading figure in robotics research. His work spans multiple institutions, including visiting positions at Showa University School of Dentistry and KDDI Research, Inc. Professor Takanishi received his Doctor of Engineering degree from Waseda University in 1985, following his undergraduate studies in the Faculty of Science and Engineering at the same institution, which he completed in 1980. His academic journey began with positions as an Assistant at Waseda University (1985-1988), Lecturer (1988-1990), and Associate Professor (1990-1997) before achieving his current Professor status. Professor Takanishi's research interests center around robotics and intelligent systems, with particular expertise in humanoid robotics, surgical dentistry applications, and biomechatronics. His work demonstrates a unique integration of mechanical engineering principles with biological systems, resulting in innovative robotic platforms that mimic human capabilities. Notably, his laboratory has developed the Waseda Anthropomorphic Saxophonist Robot series and various medical training simulators that have significantly advanced the field of human-robot interaction. His research in experimental psychology complements his robotics work, particularly in human-robot interaction studies. Analysis of Professor Takanishi's recent publications reveals a strong focus on practical applications of robotics technology, particularly in assistive devices for elderly mobility, medical training simulators, and agricultural robotics for Synecoculture environments. His work consistently bridges theoretical robotics with real-world implementation, with recent papers emphasizing reinforcement learning approaches, haptic feedback systems, and computer vision techniques for complex environments. The Waseda Anthropomorphic Saxophonist Robot series represents a culmination of decades of research in humanoid robotics and musical expression. IEEE Fellow (2020-present) Robotics Society of Japan Fellow (2012-present) Japan Society of Mechanical Engineers Fellow (2007-present) Multiple Best Paper Awards from IEEE conferences (ICRA, IROS, ROMANSY) BusinessWeek Asia's Stars Bloomberg (2001) IFToMM Award of Merit (2010) Professor Takanishi has maintained extensive collaborations with research institutions worldwide, particularly with Italian institutions through the Italy-Japan Workshop series. His laboratory has secured substantial funding from Japanese government agencies including the Japan Science and Technology Agency, with particular emphasis on projects bridging robotics with medical applications and human-centered technologies. His international recognition is evidenced by his numerous visiting professorships and collaborative projects across continents. Professor Takanishi leads the Takanishi Laboratory at Waseda University, which maintains specialized facilities for humanoid robotics development, medical robotics research, and human-robot interaction studies. The laboratory has developed several notable robotic platforms including the WABIAN series of bipedal humanoid robots, the WASEDA FLUTIST ROBOT, and various medical training simulators used in clinical education settings. His work on the WASEDA SAXOPHONIST ROBOT represents a unique fusion of musical artistry and robotics engineering.

• Perceptual information processing
• Computer Vision
• Artificial Intelligence
• +۳ مورد دیگر

Hiroshi Ishikawa is a Professor in the Department of Computer Science and Engineering at Waseda University's Faculty of Science and Engineering. He also serves as a Visiting Professor at the National Institute of Informatics since 2016. Previously, he held positions at Nagoya City University from 2004-2010 as Assistant Professor, Associate Professor, and Professor. His academic journey includes being a JST PRESTO Researcher from 2009-2013 and an Associate Research Scientist at New York University's Courant Institute of Mathematical Sciences from 2000-2001. Ph.D. in Computer Science, New York University (2000) Master of Science, Kyoto University Bachelor's degree in Mathematics, Kyoto University Faculty of Science (1991) Hiroshi Ishikawa's research spans perceptual information processing, computer vision, artificial intelligence, deep learning, and discrete optimization. His work focuses on developing algorithms for image restoration, segmentation, and understanding, with significant contributions to energy minimization techniques in computer vision. He has pioneered approaches in sketch simplification, medical image segmentation, and higher-order graph cuts. His research bridges theoretical advances in mathematical optimization with practical applications in medical imaging, computer graphics, and consumer electronics. Ishikawa's recent publications demonstrate a strong focus on leveraging deep learning for image enhancement and understanding. His work spans super-resolution techniques, colorization methods, human avatar generation, and medical image analysis. A notable trend is the increasing integration of attention mechanisms and generative models to solve complex vision problems, with growing emphasis on real-world applications in medical imaging and computer graphics. His research group consistently produces high-impact work that appears in top-tier computer vision conferences. 75th Annual IEICE Best Paper Award (2019) Innovative Technologies 2016 Special Prize for Culture (Ministry of Economy, Trade and Industry) MIRU Nagao Award (Best Paper Award) (2009) Young Author Award (IEEE Computer Society Japan Chapter, 2006) MIRU2006 Excellent Paper Award (2006) Harold Grad Memorial Prize (Courant Institute of Mathematical Sciences, NYU, 2000) As a professor at Waseda University, Ishikawa has mentored numerous students who have become active researchers in computer vision, including Yuya Masuda, Edgar Simo-Serra, and Satoshi Iizuka. His research has been supported by various grants, including JST PRESTO funding from 2009-2013. He has served on editorial boards for prestigious journals including IEEE Transactions on Pattern Analysis and Machine Intelligence and has held leadership roles in major computer vision conferences such as ICCV, CVPR, and ACCV. Ishikawa leads a vibrant research group at Waseda University focused on computer vision and image processing. His laboratory collaborates extensively with researchers at Nagoya City University, National Institute of Informatics, and international institutions. The group maintains strong connections with industry partners, particularly in medical imaging and consumer electronics sectors, translating theoretical advances into practical applications.

• Algebraic Geometry
• Symplectic Geometry
• Mathematical Physics
• +۱ مورد دیگر

Kazushi Ueda is an Associate Professor at the Graduate School of Mathematical Sciences, The University of Tokyo, where he has been since April 2015. His research spans algebraic geometry, symplectic geometry, and mathematical physics, with a focus on homological mirror symmetry and its applications to moduli spaces, Calabi-Yau manifolds, and singularities. He previously held academic positions at Osaka University from 2006 to 2015, including roles as Assistant Professor and Associate Professor. Ueda has also had visiting appointments at institutions such as the University of Oxford, Max Planck Institute for Mathematics, and Korea Institute for Advanced Study. Bachelor of Science, Kyoto University (1997-2001) Master of Science, Kyoto University (2001-2003) Doctor of Science, Kyoto University (2003-2006) Ueda's research explores the deep interplay between complex and symplectic geometry through mirror symmetry, particularly in the context of Calabi-Yau varieties, toric degenerations, and dimer models. His work addresses derived categories, stability conditions, and moduli problems, with recent contributions to noncommutative algebraic geometry and applications in mathematical physics. He has collaborated extensively with researchers like Akira Ishii, Masahiro Futaki, and Shinnosuke Okawa. His publications highlight homological mirror symmetry for K3 surfaces, Grassmannians, and singularities, as well as studies on modular forms, cluster transformations, and the Grothendieck ring. Ueda is a member of the Mathematical Society of Japan and has contributed to educational programs, including graduate lectures on mirror symmetry and symplectic geometry.

David Croydonمشاهده پروفایل

دانشیار

• Probability theory
• Diffusions on random fractals
• Scaling limits
• +۵ مورد دیگر

David Croydon is an Associate Professor at the Research Institute for Mathematical Sciences (RIMS), Kyoto University. His research focuses on probability theory, particularly diffusions on random fractals and scaling limits of random walks on random graphs. He also investigates discrete integrable systems with random initial conditions. Dr. Croydon's primary research interests span several areas of probability theory and mathematical physics. His work centers on diffusions on random fractals and how these processes can be constructed as scaling limits of related random walks on random graphs. He has made significant contributions to understanding random walks on critical structures including Galton-Watson trees, uniform spanning trees, and percolation clusters. More recently, he has developed a growing interest in the behavior of discrete integrable systems such as the box-ball system, particularly when started from random initial conditions. His research often bridges theoretical probability with applications in statistical physics and mathematical physics. Dr. Croydon's recent publications demonstrate a dual focus on theoretical probability and mathematical physics. His work on random walks spans various structures including binary trees, critical percolation clusters, and uniform spanning trees. He has made significant contributions to understanding aging phenomena, heat kernel fluctuations, and scaling limits in random media. Simultaneously, his research on discrete integrable systems explores the connections between probability theory and soliton theory, particularly through the lens of the box-ball system and related models. These two research strands converge in his investigations of scaling limits and invariant measures for complex stochastic systems. Dr. Croydon's scientific contributions have been recognized through publications in top-tier journals across probability theory and mathematical physics, though specific awards are not mentioned in the available information. Dr. Croydon has supervised several doctoral students to completion, including Adam Bowditch (2017), George Andriopoulos (2019), Eleanor Archer (2020), and Takumu Ooi (2024). He has also served in advisory roles for other students including John Sylvester (2017). His collaborative research spans multiple international institutions, suggesting involvement in various research grants supporting his work in probability theory and mathematical physics. While specific lab names aren't mentioned, Dr. Croydon is part of the vibrant probability theory research group at the Research Institute for Mathematical Sciences (RIMS) at Kyoto University. His extensive collaborations with researchers worldwide, particularly in the UK, France, and Japan, indicate active participation in international research networks focused on stochastic processes, random media, and discrete integrable systems.

• integrated system design
• quantum computation
• information security
• +۴ مورد دیگر

Nozomu Togawa is a Professor at Waseda University's Faculty of Science and Engineering, School of Fundamental Science and Engineering, specializing in Computer Science. He has held this position since 2009 and also serves as Chief Scientific Officer (CSO) of Quanmatic Inc. since 2022. With a PhD in Engineering from Waseda University (1997), his academic journey includes positions at Waseda University and the University of Kitakyushu before his current professorship. His research interests focus on integrated system design , quantum computation , and information security . Togawa has published extensively with over 368 papers and significant citation metrics (Scopus h-index: 23, Google Scholar h-index: 28). His work bridges theoretical quantum computing with practical security applications, particularly in hardware security and IoT systems. Togawa's research demonstrates a clear progression from traditional hardware security toward quantum-inspired computing solutions. His recent publications focus on Ising machines, quantum annealing, and hardware Trojan detection, showing how quantum approaches can solve complex optimization problems in security contexts. He has made significant contributions to applying quantum computing techniques to practical problems like course selection optimization, travel planning, and hardware security verification. Among his notable recognitions are the Minister of Education, Culture, Sports, Science and Technology Award for Science and Technology (2018), SCOPE Results Development Promotion Award (2022), and multiple Best Paper Awards. He serves on important committees including the Ministry of Internal Affairs and Communications Cyber Security Task Force and the Institute of Electronics, Information and Communication Engineers' VLSI Design Technology Research Committee. Togawa actively mentors students who frequently appear as co-authors on his publications. His research group produces high-impact work in quantum computing applications and hardware security, with strong industry connections through his CSO role at Quanmatic Inc. He has received substantial research funding supporting his innovative work at the intersection of quantum computing and security.

• Multimedia Signal Processing
• Computer Networks
• Communication Engineering
• +۳ مورد دیگر

Jiro Katto is a Professor at Waseda University's School of Fundamental Science and Engineering, where he has been conducting research and teaching since 1999. He received his Ph.D. from the University of Tokyo and has established himself as a leading researcher in multimedia signal processing and computer networks. His academic journey includes positions as Associate Professor (1999-2004), Professor (2004-present), and Director at NEDO (2004-2008), along with research experience at NEC C&C Laboratories (1992-1999) and a Visiting Scholar position at Princeton University (1996-1997). Professor Katto's research interests focus on Multimedia Signal Processing and Computer Networks, with particular expertise in video compression, 5G network performance, and learned image compression techniques. His work bridges theoretical advancements with practical implementations, as evidenced by his extensive publications in top-tier conferences and journals. His research group has made significant contributions to point cloud compression, latency compensation in remote systems, and hardware-accelerated video encoding for UHD streaming. His publication record is impressive, with 276 papers cited 3,323 times in Scopus and 6,169 times in Google Scholar, reflecting his substantial impact in the field. His recent work shows a strong trend toward applying deep learning techniques to traditional signal processing problems, particularly in the areas of image and video compression, where his team has developed novel approaches to improve compression efficiency while reducing computational complexity. Electric Telecommunications Promotion Foundation Telecommunications System Technology Award (2023) Takayanagi Kenjiro Foundation Takayanagi Kenjiro Achievement Award (2020) Institute of Image Information and Television Engineers Fellow (2020) Institute of Electronics, Information and Communication Engineers Fellow (2015) IEICE Communications Society Activity Contribution Award (2006) IEICE Academic Encouragement Award (1995) SPIE VCIP 1991, Best Student Paper Award (1991) Professor Katto has served on numerous prestigious committees including IEEE ComSoC Tech News Editorial Board, IEEE Technical Program Committees for major conferences (Globecom, ICC, ICIP), and editorial boards for several academic journals. His leadership in the academic community extends to chairing conferences like IWAIT 2011 and serving as Editor-in-Chief for journals in his field. His research has practical applications in commercial 5G networks, video streaming services, and remote monitoring systems, demonstrating the real-world impact of his work.

• Data science
• Machine learning
• Business analytics
• +۱۰ 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.

• Artificial Intelligence
• Multi-agent systems
• Machine learning
• +۵ مورد دیگر

Toshiharu Sugawara is a Professor in the Department of Computer Science and Engineering at Waseda University's Faculty of Science and Engineering, School of Fundamental Science and Engineering, a position he has held since April 2007. With a Ph.D. in Engineering from Waseda University, his research spans multiple domains in artificial intelligence and multi-agent systems, maintaining active collaborations across international institutions and contributing significantly to the field through numerous publications and awards. Dr. Sugawara received his BS and MS degrees in Mathematics from Waseda University in 1980 and 1982, respectively, followed by his Ph.D. in 1992. Before joining Waseda University as faculty, he worked as a Research Scientist at NTT Laboratories from 1982 to 2007, with a visiting researcher position at the University of Massachusetts at Amherst in 1992-1993. He also held part-time lecturer positions at University of Electro-Communications (2003-2007), Waseda University (2004-2006), and Tokyo University of Agriculture and Technology (1990-1991). His research interests focus on artificial intelligence with particular expertise in multi-agent systems, machine learning, cooperation and coordination mechanisms, soft computing, computational social science, and social informatics. His work bridges theoretical foundations with practical applications in network management and information systems. Recent publications demonstrate a strong trajectory toward interpretable multi-agent reinforcement learning, efficient path planning algorithms, and modeling social behaviors in complex networks. His research group has made significant contributions to multi-agent path finding, cooperative task execution, and understanding virtual economies in social media platforms. Dr. Sugawara has received numerous prestigious awards including multiple Best Paper Awards at JAWS conferences (2014, 2015, 2018), ACM SAC 2015, and various research paper awards from Japanese academic societies. His work on multi-agent systems has been consistently recognized for its theoretical rigor and practical impact. As an advisor, Dr. Sugawara has mentored numerous students who have become prominent researchers in their own right, with many co-authoring papers that have received awards. His laboratory maintains strong collaborations with industry partners, particularly in the areas of network management and intelligent systems. Current research directions include developing interpretable multi-agent reinforcement learning frameworks, optimizing multi-agent coordination in constrained environments, and analyzing social dynamics in virtual economies.

• Synthetic Organic Chemistry
• Pharmaceutical Chemistry
• Drug Development Sciences
• +۵ مورد دیگر

Masahisa Nakada is a Professor at Waseda University's Faculty of Science and Engineering, School of Advanced Science and Engineering, Department of Chemistry. With a Ph.D. in Pharmaceutical Sciences from the University of Tokyo, he leads a research group focused on synthetic organic chemistry methodologies and natural product synthesis. His research interests span Synthetic Organic Chemistry, Pharmaceutical Chemistry, Drug Development Sciences, Bioorganic Chemistry, Structural Organic Chemistry, Physical Organic Chemistry, Chemical Pharmacology, and Molecular Pharmacology. Nakada's work emphasizes developing novel asymmetric catalytic methods, particularly gold-catalyzed cycloisomerizations, intramolecular cyclopropanations, and cascade reactions for constructing complex natural product scaffolds. Analysis of his recent publications reveals a strong focus on stereoselective synthesis of bioactive natural products with complex architectures, including terpenoids, diterpenoids, and polycyclic polyprenylated acylphloroglucinols. His group has pioneered methodologies involving gold catalysis, N-heterocyclic carbene ligands, and copper-catalyzed asymmetric reactions, with applications to the synthesis of taxol, platensimycin, and various medicinally relevant compounds. Scientific Awards: Astellas Pharma Bioorganic Chemistry Award from the Society of Synthetic Organic Chemistry (2008) Society of Synthetic Organic Chemistry Pharmaceutical Society of Japan Encouragement Award (2008) Pharmaceutical Society of Japan Encouragement Award (1997) Professor Nakada's research program has resulted in over 155 publications with more than 4290 citations and an h-index of 39 (as of September 2025), demonstrating significant impact in the field of organic synthesis. His work involves extensive collaboration with students and researchers, as evidenced by the numerous co-authored publications across various synthetic methodologies and natural product syntheses. Nakada's laboratory appears to specialize in the development of chiral catalysts, particularly N-heterocyclic carbene-gold complexes, and their application to challenging asymmetric transformations essential for the synthesis of complex natural products with pharmaceutical relevance.

• Neural Networks
• Genetic Algorithms
• System Identification and Control
• +۷ 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.

• Supply Chain Management
• Complex Networks
• Agent-based Modeling
• +۷ مورد دیگر

Tomomi Kito is a Professor (non-tenure-track) at the Faculty of Science and Engineering, Graduate School of Creative Science and Engineering, Waseda University. She previously held positions as Associate Professor at Waseda University (2018-2023), Assistant Professor at University of Tsukuba (2015-2018), Senior Research Fellow at University of Oxford's Cabdyn Complexity Center (2013-2015), and Assistant Professor at The University of Tokyo (2012-2015). Dr. Kito earned her Ph.D. in Engineering from The University of Tokyo. Her academic journey includes research positions at prestigious institutions including University of Oxford's Saïd Business School (2008-2011) and The University of Tokyo's Research into Artifacts, Center for Engineering (2008). Dr. Kito's research focuses on the intersection of complex systems, supply chain management, and business strategy. Her work employs network science and agent-based modeling to understand the emergent properties of industrial ecosystems, particularly in the automotive sector. She investigates how firm strategies, product characteristics, and geographic factors shape supply network structures and their resilience. Her current research explores the heterogeneity of supply networks, corporate portfolio strategies, and urban transportation networks using big data analytics and network science approaches. Her extensive publication record demonstrates a consistent focus on understanding supply network complexity through empirical analysis of real-world data. Dr. Kito's work bridges theoretical network science with practical business applications, particularly in manufacturing and automotive industries. She has developed methodologies for analyzing industrial clusters, supply network resilience, and firm interdependencies using complex network theory. Dr. Kito has secured multiple research grants from Japanese funding agencies including the Japan Society for the Promotion of Science and Ministry of Education, Culture, Sports, Science and Technology. Her current projects include 'Modeling and empirical analysis of emergent principles of diversity and heterogeneity in social networks' and 'Development of a general-purpose dynamic model of supply networks and its verification by simulation.' She actively supervises graduate students through various seminars and thesis guidance in Strategic Management for Value Creation and Management Design at Waseda University's Graduate School of Creative Science and Engineering. Her teaching portfolio includes courses on Production Management, Global Production Systems, and Business Design.

• Applied Probability
• Operations Research
• Computational Biology
• +۴ مورد دیگر

Hiroshi Toyoizumi is a Professor at Waseda University's Faculty of Commerce and Graduate School of Accountancy, with a Ph.D. in Mathematical Physics from Waseda University. His work bridges Applied Probability , Operations Research , and Computational Biology , focusing on stochastic modeling across biological and network systems. Research Interests Stochastic Models in Biology : Analyzing social queues in hover wasps and meiotic DSB regulation using quasi-birth-death processes and survival analysis. Network Security : Modeling computer virus spread on scale-free networks and proposing active defense strategies. Queueing Theory : Developing analytical frameworks for on-demand streaming, quantum merging, and blockchain-based systems. Article Trends Recent work (2020-2024) explores nonlocal diffusion , quantum queueing , and swarm behavior in financial markets . Mid-2010s studies focus on cooperative breeding and DNA recombination dynamics . Early papers (pre-2010) examine computer virus ecology , secure group communication , and deterministic queue analysis . Scientific Awards Biotechno 2013 Best Paper Award IEICE Switching Workshop SSE Research Award (1999) IEICE Young Research Engineer Award (1997) Teaching Activities Graduate-level courses in Operations Research and Financial Engineering . Undergraduate and graduate seminars in Applied Mathematics and Probabilistic Models .

• Software Engineering
• Information Security
• Computer Systems
• +۵ مورد دیگر

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.

• Mathematical Logic
• Computer Science
• Proof Theory
• +۵ مورد دیگر

Kazushige Terui is an Associate Professor at the Research Institute for Mathematical Sciences (RIMS), Kyoto University. His research focuses on mathematical logic and its applications to computer science, particularly proof theory, computational complexity, and nonclassical logics. He investigates proof normalization complexity, algebraic reformulations of proof-theoretic techniques, and logical foundations of computation. Terui maintains an active research group at RIMS and teaches courses including Mathematical Logic and Computer Science Fundamentals. Research Interests: Terui's work spans: Proof-theoretic aspects of nonclassical logics (linear logic, substructural logics) Computational complexity of proof normalization in lambda calculus Algebraic reformulation of logical techniques (cut-elimination, interpolation) Denotational semantics approaches to complexity characterization Effective proof discovery methods based on programming language theory Publications: His recent articles primarily explore proof theory, computational complexity, and logical foundations, with frequent focus on lambda calculus, linear logic, and type systems. Works frequently bridge theoretical computer science and mathematical logic. Education & Outreach: Authored the book Can Computers Become Mathematicians? (2015) for general audiences and maintains extensive lecture materials on mathematical logic and computer science foundations.

• Acoustic Signal Processing
• Blind Source Separation
• Digital Signal Processing
• +۶ مورد دیگر

Shoji Makino is a Professor at Waseda University's Graduate School of Information, Production and Systems. He has held academic and research positions at institutions such as the University of Tsukuba and NTT Communication Science Laboratories. His work spans acoustic signal processing, blind source separation, and adaptive filtering. Education: Ph.D., Tohoku University (1993.03) Mechanical Engineering, Tohoku University Graduate School of Engineering (1979.04–1981.03) Engineering, Tohoku University Faculty of Engineering (1975.04–1979.03) Research Interests: His research focuses on acoustic signal processing for speech and audio, including blind source separation (BSS) , beamforming , and adaptive filtering . He pioneered methods for solving permutation alignment in frequency-domain BSS and developed geometrically constrained ICA techniques. Scientific Awards: Hoko Award (2018.10, Hattori Hokokai Foundation) Outstanding Contribution Award of the Institute of Electronics, Information, and Communication Engineers (2018.06) IEEE Signal Processing Society Best Paper Award (2014.01) IEEE Fellow (2004.01) IEICE Achievement Award (1997.05) Committee Memberships: He has served as Chair of the IEEE CAS Society's Blind Signal Processing TC, General Chair of IEEE WASPAA2007, and Associate Editor of IEEE Trans. SAP. He is actively involved in EURASIP, APSIPA, and the Acoustical Society of Japan.