Find Academic Supervisors

• Statistical Science
• Quality Control
• Robust Parameter Design
• +3 more

Yasushi Nagata is a Professor at Waseda University's School of Creative Science and Engineering. With a Doctor of Engineering from Osaka University, he specializes in statistical quality control, Taguchi methods, and multivariate analysis. Key affiliations: Japan Society for Quality Control Japan Statistical Society Japan Behaviormetrics Society Research Interests: His work focuses on advancing Taguchi's robust parameter design, Mahalanobis-Taguchi systems, and statistical anomaly detection. He has developed novel methods for handling missing data, high-dimensional datasets, and non-normal distributions in quality control contexts. Scientific Awards: He has received multiple Best Paper Awards at ANQ Congresses (2017-2024) Deming Prize for Individuals (2019) Waseda University Teaching Awards (2018, 2022) Nikkei Quality Control Literature Prizes Publications: His recent studies examine non-stationary extreme precipitation data, robust parameter design for multilevel systems, and EM-λ algorithm integration with MT methods. These works bridge theoretical statistics with practical engineering applications.

• Quantum Computing
• Quantum Information Theory
• Quantum Algorithms
• +6 more

Seiichiro Tani is a Professor at Waseda University's Faculty of Education and Integrated Arts and Sciences since April 2024. He previously held prominent roles at NTT Communication Science Laboratories (2003-2024), including Leader of the Computing Theory Research Group and Project Manager of the Research Center for Theoretical Quantum Information. He has also served as a Visiting Professor at Tokyo Institute of Technology (2022-2024) and a researcher at JST's ERATO projects (2004-2009). His academic journey includes a Ph.D. in Computer Science from the University of Tokyo (2006), preceded by M.E. and B.E. degrees from the University of Tokyo and Kyoto University, respectively.

• Computer Systems
• Soft Computing
• Combinatorial Optimization
• +5 more

Kazushi Kawamura is an Assistant Professor at the Tokyo Institute of Technology 's AI Computing Research Unit , with prior roles at Waseda University and the Institute of Science Tokyo. His academic journey began at Waseda University, where he earned a Dr. Eng in 2016. 2025.04 - Now: Assistant Professor, School of Fundamental Science and Engineering, Tokyo Tech 2024.10 - 2025.03: Assistant Professor, School of Fundamental Science and Engineering, Waseda 2020.04 - 2025.03: Specially Appointed Assistant Professor, Institute of Integrated Research, Institute of Science Tokyo His research spans combinatorial optimization , annealing processors , Ising machines , and FPGA-based computing systems . He has contributed extensively to LSI design methodology and high-level synthesis . Key publication trends include neural network compression , parallel annealing algorithms , edge AI inference , and sparse matrix operations on FPGAs. His work often integrates theoretical optimization with practical hardware implementations . 2023 CS Achievement Award 2016 ISOCC Best Paper Multiple Algorithm Design Contest Prizes (2014-2019) IPSJ SLDM Outstanding Student Awards Kawamura teaches courses like Physical Electronics Laboratory and Machine Learning at Waseda, with recent projects such as Amorphica (metamorphic annealer) and Pianissimo (sub-mW DNN accelerator). He serves on committees for IEEE , IPSJ , and IEICE , focusing on system design and circuit optimization.

Akira SuzukiView profile

Professor

• Combinatorial Reconfiguration
• Computational Complexity
• Graph Algorithms
• +2 more

Akira Suzuki is a Professor at the Center for Data-driven Science and Artificial Intelligence of Tohoku University, Japan. He earned his PhD in Information Sciences from Tohoku University in 2013, advised by Xiao Zhou. His career includes roles as Assistant Professor (2013-2019), Associate Professor (2019-2025), and a visiting student at the University of Waterloo (2013). His research spans combinatorial reconfiguration , computational complexity , graph algorithms , and threshold circuits . Education Bachelor of Engineering (2010), Tohoku University Master of Information Sciences (2011), Tohoku University PhD in Information Sciences (2013), Tohoku University Research interests focus on dynamic algorithmic transitions in combinatorial structures, including reconfiguration frameworks for graph problems, spanning trees, and vertex covers. His work often intersects with parameterized complexity and threshold circuit design . Recent publications emphasize spanning tree optimization , token swapping , and power distribution network reconfiguration . His 15 most recent articles address problems in combinatorial reconfiguration (spanning trees, vertex covers, graph colorings), computational complexity of puzzles, and applications to electrical distribution systems. Keywords include Graph Theory , NP-completeness , and Threshold Circuits . Scientific Awards Tohoku University ECEI Outstanding Performance Award (2012) IEICE Academic Encouragement Award (2013) Inoue Research Award for Young Scientists (2015) Best Paper Award at WALCOM 2025 (2025) Presidential Prize for Educational Excellence, Tohoku University (2024) He contributes to algorithmic education and has collaborated internationally, including with researchers at the University of Waterloo. His work appears in journals like Theoretical Computer Science and Algorithmica , with a focus on bridging theoretical computer science and applied systems.

• Software
• Intelligent informatics
• Control and system engineering
• +4 more

Professor Shigeru Fujimura is affiliated with Waseda University as a faculty member of the Faculty of Science and Engineering , specifically in the Graduate School of Information, Production, and Systems . With a PhD in Engineering from Waseda University, his research focuses on intelligent informatics and system engineering , particularly in scheduling, optimization, and human-robot collaboration. His research spans multiple domains including: Deep Reinforcement Learning for combinatorial optimization Energy-efficient manufacturing systems Multi-agent collaboration frameworks Augmented Reality interfaces IoT business modeling Recent publications demonstrate expertise in graph neural networks , particle swarm optimization , and generative adversarial networks applied to industrial problems. He has received multiple awards including the Invention Encouragement Prize (2003) and IEEJ Paper Presentation Award (1994) .

• Systems and Control
• Mathematical Optimization
• Cyber-Physical Human Systems
• +7 more

Yasuaki Wasa is an Associate Professor at Waseda University's Faculty of Science and Engineering, Department of Electrical and Bioengineering, where he has served since 2024. Previously, he held positions as Assistant Professor (tenured and non-tenured) at the same institution from 2019-2024, and Junior Researcher at Waseda University's Research Institute for Science and Engineering from 2017-2019. His academic journey began with Research Fellowships from the Japan Society for the Promotion of Science (2014-2017), following his doctoral studies at Tokyo Institute of Technology. Dr. Wasa earned his Ph.D. in Engineering from Tokyo Institute of Technology in 2016, after completing his Master's (2013) and Bachelor's (2011) degrees at the same institution, all in Mechanical and Control Engineering. His educational background established a strong foundation in systems and control theory that informs his current research. His research spans interdisciplinary domains at the intersection of control theory, game theory, and cyber-physical human systems. Key focus areas include mathematical optimization for dynamic systems, mechanism design for distributed decision-making, and the application of control theory to energy systems, robotics, and social dynamics. His work uniquely bridges theoretical control engineering with practical applications in sustainable energy, human-robot interaction, and societal systems, often employing game-theoretic approaches to address complex multi-agent coordination problems. Analysis of his recent publications reveals a strong trend toward integrating control theory with human factors in cyber-physical systems. His work increasingly focuses on the intersection of energy systems and human behavior, with significant contributions to net-zero energy solutions, game-theoretic approaches to resource allocation, and human-in-the-loop control systems for robotics applications. The mathematical sophistication of his work is consistently paired with practical implementation considerations. Outstanding Paper Award (2025) - Society of Instrument and Control Engineers Pioneer Award (2025) - SICE Control Division Outstanding Paper Award (2023) - Society of Instrument and Control Engineers Best Paper Award Finalist (2022) - Asian Control Conference Funai Information Technology Award for Young Researchers (2021) Waseda University Teaching Award (2024) Seiichi Tejima Doctoral Dissertation Award (2017) - Tokyo Institute of Technology Dr. Wasa actively mentors students through the Wasa Research Group (System Control Research), guiding numerous advisees who appear as co-authors on his publications. His current research is supported by multiple grants including a TEPCO Memorial Foundation Research Grant (2025-2028) on electricity market mechanisms and a JSPS Grants-in-Aid project (2023-2026) on control systems design for societal systems. His lab conducts cutting-edge research on cyber-physical human systems, with projects spanning VR-based drone swarm control, energy management systems, and human-robot cooperative transportation. The Wasa Lab maintains active collaborations with industry partners and participates in regular research camps and open house events to engage prospective students and collaborators.

• 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.

Tota SukoView profile

Associate Professor

• Bayesian statistics
• Statistical learning theory
• Business statistics
• +3 more

Tota Suko is an Associate Professor at the School of Social Sciences, Waseda University, specializing in statistical learning theory and business analytics. With a Ph.D. in Engineering from Waseda University, Dr. Suko leads the Suko Seminar (Management Science Seminar) where students learn to solve business problems using mathematical and management science approaches, primarily through data science techniques including statistical analysis and machine learning. Dr. Suko's research spans multiple domains in statistics and data science. His primary interests include Bayesian statistics, statistical learning theory, business statistics, data mining, and information theory. He has developed methods for analyzing survey data with selection bias, detecting poor responses in questionnaires, and parameter estimation in regression models. His work bridges theoretical statistics with practical applications in business analytics, e-commerce, and even nanotechnology through collaborations with physics researchers. Dr. Suko's recent publications demonstrate a strong trend toward practical applications of statistical methods. His work on generative AI for criminal case law analysis shows innovative application of AI in legal domains, while his research on questionnaire quality control addresses fundamental issues in survey methodology. He has also made significant contributions to theoretical aspects of statistical learning, particularly in the areas of label noise, selection bias, and parameter estimation under non-ideal data conditions. Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research projects Waseda Data Science Consortium industry-academia collaborations Research on nanoscale semiconductor prediction models Development of methods for low-quality data analysis Dr. Suko actively supervises both undergraduate and graduate students through the Suko Seminar. Students work on individual or team projects, participate in data analysis competitions, and present their research at academic conferences. He has developed educational approaches including full-on-demand content for data science education and modularized online statistical teaching materials. Dr. Suko leads the Suko Seminar (Management Science Seminar), which actively collaborates with companies and research institutions. His research team works on diverse projects including analysis of purchasing and browsing histories on e-commerce sites, prediction modeling for nanoscale conduction, and development of methods for low-quality data analysis. The seminar emphasizes both theoretical understanding and practical application of data science techniques to solve real-world business problems.

• Robotics
• Tactile Sensing
• Soft Robotics
• +3 more

Tito Pradhono serves as an Assistant Professor and Junior Researcher at the Future Robotics Organization under the Research Council, specializing in advanced robotics research with 34 publications and significant scholarly impact (884 Google Scholar citations, h-index 12). His work bridges hardware innovation and algorithmic development to solve critical challenges in robotic perception and interaction. His primary research focuses on tactile sensing systems and soft robotics, where he has pioneered novel sensor technologies including Halbach array-based robot skin (H-PME), interchangeable fingertip sensors (Fingertac), and low-cost proximity-force fusion systems ("Safe Skin"). These innovations enable enhanced human-robot interaction through precise force measurement, slip detection, and grasping stability prediction. His methodology consistently integrates machine learning—particularly spatio-temporal attention networks and ensemble learning—with physical sensor design to create practical, deployable solutions. Analysis of his 15 most recent publications reveals a clear trajectory toward multimodal perception systems (vision-touch fusion), geometric data augmentation techniques, and culturally contextual robotics (anime embodiment). His work demonstrates exceptional consistency in developing cost-effective, real-world applicable technologies while maintaining theoretical rigor in sensor fusion and deep learning architectures. He received the Integrated Doctoral Tuition Support Scholarship in 2015, which supported his foundational research. His scholarly impact is evidenced by sustained citation growth across Scopus (612 citations) and Google Scholar (884 citations) platforms. Dr. Pradhono's research is conducted within the Future Robotics Organization, which appears to focus on socially engaged robotics development including the darumato-3 social robot platform and culturally specific implementations like Wayang puppet theater robots with Gamelan music recognition. His work emphasizes participatory design and real-world deployment rather than purely theoretical exploration.

SAITO ShoichiView profile

Professor

• Information Security
• Computer Systems
• Software Engineering
• +3 more

Professor Shoichi Saito is a distinguished academic at Nagoya Institute of Technology, where he serves in the Department of Information Engineering within the College of Engineering. His research focuses on information security, computer systems, and software engineering, with particular expertise in IoT security, distributed systems, and network security. Professor Saito earned his Doctor of Engineering from Ritsumeikan University in March 2000. Prior to his current position, he served as Assistant Professor, Lecturer, and Associate Professor at Wakayama University's Faculty of Systems Engineering from 1998 to 2006. His research interests span multiple critical areas of modern computing: Information security with focus on IoT device protection Distributed systems and blockchain technologies Mobile application security, particularly for Android platforms Confidential information protection using virtual machine technologies Network security and anonymous communication systems Professor Saito's research outputs demonstrate a consistent focus on practical security solutions for emerging technologies. His recent work has centered on IoT security, data usage control in distributed environments, and advanced taint tracking mechanisms for mobile applications. His research bridges theoretical security concepts with practical implementation challenges. Among his notable recognitions are multiple awards from the Information Processing Society of Japan's Computer Security Research Group, including CSS2024 Student Paper Awards and Encouragement Awards. Professor Saito actively contributes to the academic community through committee memberships, including the Nagoya City Personal Information Protection Council and various program committees for the Information Processing Society of Japan. He has secured significant research funding, most recently for projects on IoT device emulation and virtual execution platform remote authentication.

• Intelligent Informatics
• Computer Systems
• Agent-based Systems
• +3 more

Takahiro Uchiya serves as Professor at Nagoya Institute of Technology, holding dual appointments in the Department of Information Engineering within the Faculty of Engineering and the Information Technology Center. His academic leadership spans agent-oriented knowledge engineering and intelligent informatics, with recent focus on disaster response robotics and multi-agent systems development. Uchiya completed his academic foundation at Tohoku University through a rigorous progression: Bachelor of Engineering, Faculty of Engineering (1999) Master of Information Science, Graduate School of Information Science (2001) Doctor of Information Science, Graduate School of Information Science (2004) His research centers on agent-oriented knowledge representation, problem solving, and acquisition techniques, with significant extensions into cyber society software platforms and social knowledge applications. Recent investigations reveal a pronounced shift toward practical disaster management solutions, including robot-guided evacuation systems and BLE-based positioning technologies. This trajectory demonstrates consistent innovation in translating theoretical multi-agent frameworks into real-world emergency response tools. Uchiya's scientific contributions have earned recognition including the BWCCA2024 Best Paper Award and IEEE CES West Japan Chapter Young Researcher Award. His award portfolio spans both Japanese and international venues, reflecting broad scholarly impact. Through committee roles in the Information Processing Society of Japan and Institute of Electronics, Information and Communication Engineers, Uchiya actively shapes academic discourse. His societal engagement manifests in developing voice dialogue systems for elderly care and robotics programming workshops for schoolchildren, bridging academic research with community needs through events like Science Agora 2018.

Tomoyuki MorimaeView profile

Associate Professor

• Quantum Computing
• Quantum Cryptography
• Theoretical Physics
• +3 more

body { font-family: Arial, sans-serif; } h2 { color: #333; } ul { list-style-type: disc; padding-left: 20px; } p { margin: 10px 0; } Tomoyuki Morimae Tomoyuki Morimae is an Associate Professor at the Yukawa Institute for Theoretical Physics (YITP), Kyoto University. He specializes in quantum computing and quantum cryptography. Before joining Kyoto University in 2020, he held positions at Gunma University (2014–2015) and was a Lecturer at YITP. Education MSc from The University of Tokyo PhD from The University of Tokyo Research Interests Morimae's research focuses on leveraging quantum properties for computation and cryptography. Key areas include quantum algorithms, cryptographic protocols resistant to quantum attacks, and complexity theory. His work bridges theoretical foundations and practical implementations, emphasizing secure quantum communication and computational advantages over classical systems. Key Contributions Notable publications explore quantum cryptographic primitives (e.g., CountCrypt), quantum group actions, and separations in cryptographic assumptions. Recent work addresses secure key leasing, quantum unpredictability, and revocable digital signatures. Awards Ogawa Publishing Award Young Physicist Prize from the Physical Society of Japan Grants & Teaching He leads projects on quantum computational supremacy and secure cloud quantum computing. Teaches advanced theoretical physics and quantum information seminars at Kyoto University's Graduate School of Science. Labs & Teams Morimae collaborates with researchers like Giulio Malavolta and Takashi Yamakawa on cryptographic protocols and quantum complexity theory.

• Materials Science
• Inorganic Chemistry
• X-ray Diffraction Analysis
• +4 more

Takashi Ida is a Professor at Nagoya Institute of Technology's College of Engineering, Department of Life and Applied Chemistry, Environmental Ceramics Field, leading the Advanced Ceramics Research Laboratory. His academic journey began with a Master of Science (1985) and Doctorate in Science (1989) from The University of Tokyo, where he completed his undergraduate studies in the Faculty of Science. His research focuses on advanced powder diffraction methodologies, particularly developing deconvolution-convolution treatments for X-ray diffraction data. Key contributions include correcting sample transparency aberrations in Bragg-Brentano geometry, modeling equatorial aberrations in silicon strip detector systems, and developing algorithms for removing Cu Kβ contamination and Ni K-edge effects. His work bridges theoretical modeling with practical instrumentation improvements. Analysis of his 15 most recent publications (2011-2024) reveals consistent focus on mathematical treatments of powder diffraction data, with increasing sophistication in modeling instrumental aberrations and developing correction algorithms. His research spans both fundamental theoretical developments and practical applications for ceramic materials characterization. Best Poster Award in ICDD Spring Meetings (2017) Richard and Patricia Spriggs Phase Equilibria Award (2010) ICDD Fellow (2010) Professor Ida has secured significant research funding, including a 2019-2022 Grant-in-Aid for Scientific Research (Category B) for developing powder X-ray diffraction data processing software. His committee memberships reflect his international standing, including Director at Large for the International Centre for Diffraction Data (ICDD) and committee membership in the International Union of Crystallography's Commission on Powder Diffraction. He leads the Advanced Ceramics Research Laboratory, which maintains strong connections with international crystallography organizations and focuses on developing next-generation diffraction analysis methodologies.

• Control and system engineering
• Thermal engineering
• Heat and Mass Transfer
• +6 more

Niccolo Giannetti is currently an Associate Professor at Waseda University, affiliated with the Department of Applied Mechanics and Aerospace Engineering and the Waseda Institute for Advanced Study. His career spans roles including Assistant Professor at Waseda University (2017-2021) and Research Associate (2014-2017). Doctor of Engineering, Waseda University Professional Engineer, Association of Professional Engineers of Florence Giannetti's research focuses on thermal engineering and fluid dynamics , particularly in heat and mass transfer, thermodynamic optimization, and absorption/refrigeration systems. He explores microchannel heat exchangers , two-phase flow distribution , and genetic programming for system modeling . His work integrates machine learning for performance prediction and variational principles in entropy production analysis. His recent publications emphasize heat pump optimization , ANN-based HVAC monitoring , and sorption systems . Awards include recognition from JSRAE, Elsevier, and IIR. Giannetti contributes to international standards (ISO, IEA) and serves on conference committees (ISHPC, IIR). Key publications address flow maldistribution, void fraction modeling, and energy-efficient desiccant systems using ionic liquids.

• Economic Statistics
• Machine Learning
• Bayesian Statistics
• +4 more

Naoki Awaya is an Assistant Professor at the School of Political Science and Economics , Waseda University. His research focuses on economic statistics, computational statistics, and financial econometrics with applications in machine learning and Bayesian inference. Education : Not explicitly stated Current Projects : Developing Bayesian estimation methods for nonstationary economic time series and structural changes His work includes tree-based models for probability distributions and advanced MCMC sampling techniques. He teaches graduate-level econometrics courses (Econometrics I/II) using R programming, emphasizing methodological rigor and theoretical foundations. Research interests span high-dimensional data analysis, density ratio estimation, and financial market applications through multivariate Hawkes processes. Recent publications highlight innovations in: Unsupervised tree boosting Hidden Markov Pólya trees Particle rolling MCMC algorithms Nonstationary errors-in-variables models