Find Academic Supervisors

• Multimedia Signal Processing
• Computer Networks
• Communication Engineering
• +3 more

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.

• Medical Informatics
• Statistical Science
• Bioinformatics
• +5 more

Dr. Masato Inoue is a Professor at the Faculty of Science and Engineering , School of Advanced Science and Engineering at Waseda University. He holds a Doctor of Medical Science from Kyoto University. Education: 2003 - Kyoto University Graduate School of Medicine 2003 - Kyoto University His research spans multiple disciplines at the intersection of Medical Informatics , Bioinformatics , and Statistical Mechanics . Key areas include: Medical Imaging : Developing Bayesian super-resolution algorithms and Prior Ensemble Learning for improved MRI reconstruction Voice Analysis : Creating innovative voice quality quantification systems for clinical diagnostics Genetic Analysis : Advancing haplotype inference methods and gene network modeling Signal Processing : Applying statistical mechanics to diverse problems from coding theory to neuroscience His recent publications (2021-2012) demonstrate consistent contributions to medical imaging algorithms , voice disorder classification , and genetic data analysis . Notable collaborations include work with Kyoto University researchers , Swedish medical institutions , and cross-disciplinary teams in bioengineering.

• Signal Processing
• Machine Learning
• Optimization
• +7 more

Hiroyuki Kasai is a Full Professor at the School of Fundamental Science and Engineering, Waseda University, where he leads research in signal processing, machine learning, and optimization. He holds a B.Eng. (1996), M.Eng. (1998), and Dr.Eng. (2000) in Electronics, Information, and Communication Engineering from Waseda University. His career includes positions as Associate Professor and Professor at the University of Electro-Communications (2007-2019), Senior Policy Researcher at Japan's Cabinet Office (2011-2013), and visiting roles at Technical University of Munich and British Telecom. His research spans: Fundamental methodologies : Riemannian optimization, stochastic gradient algorithms, tensor decomposition Applied domains : Network analysis, multimedia systems, environmental sound processing, video coding Emerging areas : Low-rank modeling, manifold learning, and large-scale anomaly detection His publications focus on efficient algorithms for high-dimensional data, with recent work emphasizing Riemannian manifold optimization and real-time tensor analysis. This includes development of open-source tools like SGDLibrary (MATLAB) and McTorch (PyTorch) for optimization tasks. Awards include: IEEE ICCE Best Paper Award (2011) Yamashita Memorial Award (2003) Ericsson Young Scientist Award (2001) 電気通信普及財団賞 (2015) IEICE Service Recognition Award (2010) He maintains memberships in IEEE, IEICE, IPSJ, and JSIAM, and has contributed to over 100 peer-reviewed publications with significant citation impact (h-index 27 via Google Scholar).

• Artificial Intelligence
• Intelligence Informatics
• Internet of Things
• +4 more

Xin Qi is an Assistant Professor (non-tenure-track) at the School of International Liberal Studies, Faculty of International Research and Education, Waseda University. He holds a Doctor of Engineering degree from Waseda University (2019) and previously studied at Hangzhou Dianzi University (2009-2013). His educational background includes: Doctor of Engineering, Waseda University (2014.09-2019.09) Bachelor's degree, Hangzhou Dianzi University (2009-2013) Dr. Qi's research focuses on the intersection of artificial intelligence and network technologies. His primary research areas include Intelligent Informatics, with specific interests in Artificial Intelligence applications for security systems, IoT infrastructure, and Information-Centric Networking. His work bridges theoretical computer science with practical applications in public safety, disaster management, and secure communications. His research demonstrates strong interdisciplinary connections between computer science, electrical engineering, and practical security applications. Analysis of Dr. Qi's publication record (44 papers with 557 Scopus citations and h-index of 12, or 757 Google Scholar citations with h-index of 15) reveals a strong focus on practical applications of AI and blockchain technologies. His most recent work (2023-2024) centers on latency compensation in remote monitoring systems, GNSS spoofing detection using machine learning, and AI-based security screening systems. Earlier work (2021-2022) shows significant contributions to ledger-based point transfer systems for LPWAN networks and image processing techniques for secure data transmission. His research demonstrates a consistent trajectory toward solving real-world problems in security, networking, and IoT applications. Dr. Qi is an active member of professional organizations including the Institute of Electronics, Information and Communication Engineers and IEEE. His research is supported by multiple projects including "Low latency interactive zero latency video/Somatic integrated network" (2022-2024), "Dynamic Secure Network for Traffic and Logistics" (2021-2023), and "Lightweight distributed ledger technology authentication system for LPWA" (2020-2022). These projects reflect his focus on practical applications of his research in real-world scenarios, particularly in disaster management and secure communications infrastructure. He has received consistent research funding that supports both theoretical development and practical implementation of his work. Dr. Qi also contributes to educational initiatives at Waseda University, teaching courses including Data Structure and Algorithms, Human-Technology Interface, and Computerized Society, where he bridges theoretical computer science with practical applications for undergraduate students.

• Machine Learning
• Statistical Learning Theory
• Statistical Science
• +3 more

Goki Yasuda is an Associate Professor at the Center for Data Science, Waseda University. His research spans statistical science, intelligent informatics, and machine learning, with specialized interests in label noise robustness, semi-supervised learning, and asymptotic analysis of algorithms. He teaches extensively in data science education, including courses like 'Statistics Literacy', 'Data Analysis with Python', and 'Modeling for Data Science' through Waseda's Global Education Center. His research explores foundational machine learning challenges, including: Theoretical analysis of classification under label noise conditions Performance limits of semi-supervised learning with unlabeled data Bayesian inference for misspecified probabilistic models Algorithm optimization for real-world data imperfections Publications demonstrate a strong emphasis on theoretical machine learning (75% of recent work) with secondary focus on applied signal processing for video coding (25% of earlier publications). Research consistently employs statistical methods to address data quality issues in learning systems. He leads research projects including: 'Developing machine learning algorithms for low-quality data' (2022) 'Research on machine learning from data of various quality' (2019) 'Performance evaluation of prediction in half-ranked learning' (2018)

OKAMOTO EijiView profile

Professor

• Quantum Cryptography
• Satellite Communications
• Wireless Networks
• +3 more

OKAMOTO Eiji is a Professor at the Department of Electrical and Mechanical Engineering, School of Engineering, Nagoya Institute of Technology. His research focuses on quantum cryptography, satellite communications, wireless networks, 5G/6G technology, information security, and Sub-THz imaging. He has made significant contributions to the fields of quantum key distribution, non-terrestrial networks, and secure wireless communications. OKAMOTO received his Doctor of Informatics from Kyoto University in 2003, Master of Engineering in 1995, and Bachelor of Engineering in 1993, all from Kyoto University. Prior to his current position, he worked at the Communications Research Laboratory, Ministry of Posts and Telecommunications (1995-2002), NICT (2011-2013), and Simon Fraser University (2004). Professor OKAMOTO's research interests span multiple cutting-edge areas in communications technology. His work in quantum cryptography focuses on improving information reconciliation for continuous-variable quantum key distribution using polar codes and raptor codes. In satellite communications, he has conducted extensive research on non-terrestrial networks and optical satellite data relay systems. His contributions to wireless networks include developing low-latency communication techniques, advanced multiple access methods, and secure communication protocols. His recent work in Sub-THz imaging has led to innovations in hazardous material identification and complexity reduction methods. Analysis of his recent publications reveals a strong focus on quantum key distribution systems, with multiple papers addressing information reconciliation efficiency. There's also a significant emphasis on non-terrestrial networks for 6G applications, particularly leveraging LEO satellites and optical communications. His research bridges theoretical advances with practical implementations, as evidenced by numerous papers on experimental demonstrations and system implementations. Education Achievement Award from IEICE (2025) Best Paper Award from IEICE Communications Society (2024) Satellite Communication Research Award (2023) Activity Merit Award (Review Committee) (2022) Meritorious Service Award (Research Committee Chair) (2022) Excellent Teaching Award from Nagoya Institute of Technology (2022) IEICE ComEX Top Downloaded Letter Award (2022) IEICE Fellow (2022) Professor OKAMOTO actively mentors numerous graduate students, with recent research involving M1 and M2 students working on quantum cryptography, Sub-THz imaging, and non-terrestrial networks. His laboratory at Nagoya Institute of Technology has received funding for research on quantum cryptography communication (2019), autonomous driving (2014), sensor networks (2009), and optical satellite communication (2008). He has served as a committee member for numerous academic societies including IEEE and IEICE. Professor OKAMOTO leads the Eiji Okamoto Laboratory at Nagoya Institute of Technology, which focuses on creating next-generation mobile and satellite communication systems. The laboratory aims to cultivate independent thinking engineers while developing new wireless (and wired) communication methods to realize a safer, more secure, and more convenient super-smart society. Current research projects include quantum cryptography, Sub-THz imaging for security applications, non-terrestrial networks for 6G, and low-latency communication techniques for autonomous driving and V2X applications.

• Human-Computer Interaction
• Image Processing
• Digital Signal Processing
• +4 more

Yoichi Kato serves as a Professor (without tenure) at Waseda University's School of Creative Science and Engineering and Global Center for Science and Engineering. He maintains additional affiliations with the Graduate School of Creative Science and Engineering and the Global Education Center. His academic profile spans decades of research and teaching in information and communication technologies, with particular expertise in video coding algorithms, image processing, and human-computer interaction systems. Professor Kato's research interests focus on Human interface and interaction, Image Processing, Digital Signal Processing, and Design Thinking. His scholarly trajectory demonstrates a progression from foundational work in signal processing during the 1980s-1990s toward more applied, interdisciplinary research in recent years. Early publications established his expertise in motion picture coding algorithms and image restoration techniques, while his current work explores IoT applications, machine learning prototyping methods, and user-centered design approaches. Analysis of his publication history reveals significant contributions to video compression standards and image processing algorithms, with recent research expanding into collaborative systems, disaster prevention technologies, and educational applications. His work bridges theoretical foundations with practical implementations, particularly evident in his recent projects involving drone-based terrain analysis and automated plant monitoring systems. Professor Kato actively supervises graduate students through Master's Thesis projects in the Department of Modern Mechanical Engineering and Research on Neuro Robotics. His teaching portfolio includes diverse courses such as SHIP Field Practice, Modern Information and Communication Systems, Exercise for Co-Creation workshop, and Introduction to Python Programming, reflecting his interdisciplinary approach to education. His laboratory activities center on practical applications of information technologies, with current projects examining drone applications for disaster prevention, remote plant monitoring systems using IoT technology, and prototyping methodologies for machine learning applications. These initiatives demonstrate his commitment to translating theoretical knowledge into real-world solutions that address contemporary challenges.

• Information Technology
• Communication Engineering
• Image Processing
• +3 more

Hiroshi Watanabe is a Professor at Waseda University 's Department of Communications and Computer Engineering , School of Fundamental Science and Engineering. With a Doctor of Engineering from Hokkaido University (1985), his career spans NTT Human Interface Laboratories (1985-2000) and academic leadership at Waseda since 2000, including chairing ISO/IEC JTC 1/SC 29 (1999-2006). A Fellow of IEEE , IEICE , and other institutions, he focuses on image/video coding , machine vision , and multimedia distribution . Education: BE, ME, Ph.D. in Electronic Engineering (Hokkaido University) Professional Affiliations: IEEE, IEICE, IPSJ, ITE, IIEEJ His research bridges image/video processing with deep learning , emphasizing machine-centric coding , real-time detection , and multimodal analysis . Key recent work includes: Novel image coding frameworks combining edge learning and diffusion models Super-resolution techniques for QR codes and medical imaging Advanced object detection using non-local modules and attention networks 3D pose estimation and point cloud analysis for robotics and healthcare He has received prestigious awards including the 2005 Information Processing Society of Japan Standardization Contribution Award and multiple earlier honors. His recent publications (2024-2025) demonstrate leadership in machine vision coding , real-time medical detection , and multimodal signal processing , often integrating stable diffusion , feature fusion , and parameter-efficient models .

• Communication and network engineering
• Measurement engineering
• Electron device and electronic equipment
• +3 more

Makoto Tsubokawa is a Professor at the Faculty of Science and Engineering and Graduate School of Information, Production and Systems at Waseda University . His career spans multiple institutions, including a visiting scholar position at the University of California, Davis (2023-2024) and prior roles at NTT Labs and NTT-East Corp. Research Interests : Optical fiber sensors and polarization-maintaining fibers Fiber optic measurement techniques and mode coupling analysis Photonic network reliability and security in WDM/TDM systems Nanoscale optical devices and metasurface structures His work has focused on enhancing optical signal transmission, suppression of fiber fuse propagation, and innovative designs for photonic nanojets, bowtie core capillaries, and ultra-thin photodiodes. His recent publications (2023-2025) emphasize directional scattering for absorption enhancement, bidirectional nanoparticle transport, and MIMO-based network protection schemes. Education : Ph.D. in Engineering, Hokkaido University (1984) Master’s in Applied Physics, Hokkaido University (1982) B.Sc. in Applied Physics, Hokkaido University (1981) Professional Memberships : OSA (The Optical Society) IEEE (Institute of Electrical and Electronics Engineers) IEICE (Institute of Electronics, Information and Communication Engineers)

• Music Composition
• Sonification
• Auditory Display
• +3 more

Yota Morimoto is an Associate Professor at Waseda University's School of Fundamental Science and Engineering and a Visiting Professor at the Institute of Sonology, Royal Conservatory in The Hague. His work bridges music composition, sonification, and interactive sound systems. PhD in Music Composition (University of Birmingham, 2015) Master's in Sonology (Royal Conservatory in The Hague) His research focuses on auditory display, sonification, and ambient music, with applications in public space sound design (e.g., Singapore Airport, Floriade 2022). He has developed sound generation systems for institutions like NTT Communication Science Laboratories and Honda R&D. Key recent publications include studies on biofeedback sonification for autonomous vehicles, seismic data sonification, and sports biomechanics applications. His work integrates SuperCollider programming, spatial audio, and creative technology. Scientific Awards: Elite Scholarship (University of Birmingham, 2011–2013) He leads research projects funded by Creative Industries Fund and STROOM Foundation, while also contributing to academic societies like the Japanese Society for Sonic Arts and the International Community for Auditory Display.

• Applied mathematics
• Statistics
• Information theory
• +8 more

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.

• Image coding
• Machine learning
• Data science
• +3 more

Yuta Nakahara is an Assistant Professor (tenure-track) at Waseda University's Center for Data Science, where he has been working since 2019. His research focuses on the intersection of information theory, machine learning, and data science, with particular emphasis on Bayesian decision theory and its applications to image compression and decision tree modeling. Dr. Nakahara received his Doctorate from Waseda University's Graduate School of Fundamental Science and Engineering, Department of Pure and Applied Mathematics (2016-2019), following a Master's degree from the same institution (2014-2016) and a Bachelor's degree from Waseda University's School of Fundamental Science and Engineering, Department of Applied Mathematics (2010-2014). His research interests span image coding, machine learning, data science, lossless image compression, error correcting codes, and information theory. Nakahara's work particularly focuses on developing probabilistic models for image generation and compression, with an emphasis on Bayesian approaches that provide theoretical guarantees for optimal performance. His recent work extends these principles to decision tree models for improved uncertainty quantification and interpretability. Analysis of Nakahara's 15 most recent publications reveals a consistent focus on Bayesian methods for modeling hierarchical structures, particularly tree-based models. His work bridges theoretical information theory with practical machine learning applications, especially in image processing and decision systems. A significant thread throughout his research is the development of computationally efficient algorithms that maintain theoretical optimality. Top Reviewers of NeurIPS 2024 (8.6%, 1,304 of 15,160 reviewers) Dean's Award for Fundamental Science and Engineering, Grand Prize (2014) Dr. Nakahara leads the development of BayesML, an open-source Python library implementing Bayesian machine learning models with a unified API based on decision theory. His teaching portfolio includes numerous data science and statistics courses across Waseda University's Global Education Center, reflecting his commitment to data science education. His research is supported by multiple Waseda University Specific Research Grants focused on lossless image compression through probabilistic modeling, with projects running from 2019 to present.

Youki KadobayashiView profile

Professor

• Internet Engineering
• Web Security
• Cybersecurity Education
• +4 more

Youki Kadobayashi is a Professor at NAIST, specializing in cybersecurity and network engineering. He holds a Ph.D. in Computer Science from Osaka University. His research focuses on Internet infrastructure evolution, cybersecurity education, and standards development. He collaborates with industry and academia on projects like creating technologies for failure recovery and infrastructure co-creation. Research interests include: Internet engineering, web security, cybersecurity education standards, and privacy-preserving systems. His work addresses challenges in smart home security, federated learning for fraud detection, and secure edge computing. Publications span topics like differential privacy, federated learning frameworks, and authentication protocols. He contributes to consortia such as WIDE and organizes competitions like CDMC and Hardening Zero. His lab explores advanced cybersecurity tools and datasets.

• Civil Engineering
• Structural Engineering
• Concrete Technology
• +5 more

Professor Yasuhiko Sato is affiliated with Waseda University's Faculty of Science and Engineering, School of Creative Science and Engineering, where he has been working since April 2018. Prior to this, he held positions at Hokkaido University from April 1994 to March 2018, progressing from Assistant to Associate Professor and then to Professor. His academic journey began with a Doctor of Engineering degree from Hokkaido University. Professor Sato's research focuses on civil engineering materials, structural engineering and earthquake engineering, safety engineering, and social systems engineering, with particular emphasis on concrete technology and FRP strengthening of concrete structures. His work explores the durability of concrete under various environmental conditions, including frost damage and fatigue behavior, as well as the bond mechanics between FRP and concrete. He has developed innovative methods for analyzing and predicting the behavior of concrete structures under different loading conditions and environmental exposures. His research output demonstrates a strong focus on the mechanical properties of concrete, especially under combined deterioration from fatigue and frost damage. Professor Sato has pioneered methods for predicting ultimate debonding strain in FRP-strengthened concrete and has investigated the importance of mortar skin characteristics in concrete surface layers. His recent work (2023-2024) continues to advance understanding of FRP-concrete interfaces and their behavior under various conditions. Professor Sato has received numerous prestigious awards for his contributions to civil engineering, including the Structural Engineering Paper Award from the Japan Society of Civil Engineers (2020), the Yoshida Award (2020 and 2003), the Cement Association Paper Award (2013), and the Best Basic Research Paper award from the American Society of Civil Engineers Journal of Composites for Construction (2005). As an active researcher, Professor Sato maintains professional memberships with several organizations including fib (International Federation for Structural Concrete), aci (American Concrete Institute), Resource and Materials Society, Concrete Engineering Society, PC Engineering Society, Materials Society, and the Japan Society of Civil Engineers. His research has significant practical applications in infrastructure maintenance and repair, particularly in cold regions where frost damage is a major concern.

• Anglo-Irish Literature
• Drama Studies
• Body and Image Studies
• +4 more

Futoshi Sakauchi is a full-time Professor at Waseda University's School of Culture, Media and Society and Graduate School of Letters, Arts and Sciences. Holding a PhD from University College Dublin, his career spans over two decades of research and teaching in Anglo-Irish literature and performance studies. Current affiliations: Faculty of Letters, Arts and Sciences Secondary affiliation: Global Education Center Research focus examines: Body and image representations in Irish modernism Transformative public space in Joyce/Beckett Confession as secular/spiritual narrative Gendered corporeality in postcolonial contexts Cultural regeneration through performance Publisher trends show consistent engagement with James Joyce's works, Irish nationalist theatre, and body-centric methodologies. His 2018 project on confession in Irish drama reveals institutional authority's decline in contemporary contexts. Scientific recognition includes five consecutive Japan Society for the Promotion of Science grants (2007-2023) funding analyses of: Modernist body transfiguration Confession-as-secular-sacrament Technology's impact on bodily representations As educator , he teaches graduate seminars on body/media studies and performance theory while supervising master's research projects.