Yukihiko Funaki is a Professor at the School of Political Science and Economics, Waseda University, Japan. He holds a Doctor of Science degree from Tokyo Institute of Technology and has been active in game theory, experimental economics, and resource allocation mechanisms since the 1980s. Key Research Areas: Game Theory, Experimental Economics Affiliation: Waseda University (1998–present), previously Toyo University (1985–1998) His recent publications focus on proportional allocation of nonseparable contributions, coalition formation experiments, and consistency axioms in cooperative game theory. A 2023 paper examines balanced externalities in TU-games, while 2022 work investigates production function impacts on bargaining outcomes. His experimental studies range from energy labeling effectiveness to social preferences in public goods games. His work spans theoretical characterizations (e.g., Shapley value variants) and practical applications (e.g., financial market regulation, forest coffee certification). Grants include Japan Society for the Promotion of Science funding for coalition formation analysis (2022–2027) and financial market stabilization research (2017–2020).
Yuriko Zemba is a Professor at Waseda University's School of Creative Science and Engineering, Division of Socio-Cultural Studies. With a PhD in Social Psychology from the University of Tokyo, her work bridges psychological theory with organizational and cultural dynamics. Education: PhD in Social Psychology (University of Tokyo, 2005) Research Focus: Social psychology, organizational behavior, and cultural comparison Teaching: Offers courses like Industrial and Organizational Psychology, Social Psychology I/II, and seminars for graduate students Her research explores how cultural differences shape responsibility attribution in organizations, including proxy blaming of leaders and collective control illusions. Key themes include: Cross-cultural responsibility judgments Organizational crisis management AI and moral accountability Causal inference in blame/credit distribution Gendered and cultural control perceptions She has secured significant grants from Japan's Ministry of Education, Culture, Sports, Science and Technology for projects on AI responsibility (2019-2023) and criminal liability diffusion (2018-2021). Scientific Awards Misumi Award (2007) from Asian Association of Social Psychology Waseda University President's Teaching Award (2021) for 'Social Psychology I' Her work has been presented at major conferences across Japan and internationally, including the International Congress of the International Association for Cross-Cultural Psychology and the Asian Association of Social Psychology Conference.
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.
Siya BAO is an Assistant Professor at Waseda University's Faculty of Science and Engineering, focusing on quantum computing applications in combinatorial optimization and geospatial information processing. Currently affiliated with the Green Computing Systems Research Organization, her work bridges theoretical computer science with practical implementations in travel planning, indoor localization, and financial forecasting. Key research interests include: Quantum Computing Geospatial Information Processing Text Mining Based on 15 recent publications, her research trajectory demonstrates: Quantum annealing solutions for multi-day trip planning Machine learning applications in financial time series analysis Advancements in smartphone-based pedestrian dead reckoning Innovations in QUBO model formulation for constrained optimization Scientific recognition includes: DICOMO 2023 Outstanding Paper Award IEEE ICSC 2020 Best Student Opponent 2017 Telecommunications Advancement Foundation Travel Aid Research activities span: Principal investigator for JSPS-funded geospatial optimization projects (2021-2024, 2024-2027) Contributing author to Springer's 'Machine Learning for Indoor Localization and Navigation' (2023) Extensive conference presentation history including IPSJ-ONE 2024 invited talk on quantum computing applications
NAKAZATO, Hidenori is a Professor at the Waseda University, School of Fundamental Science and Engineering , specializing in Computer Science . His research focuses on Information Centric Networking (ICN) , Distributed Systems , and Communication Quality optimization. Education: Ph.D. and MS in Computer Science from University of Illinois (1993) Professional Memberships: IPSJ, IEICE, ACM, IEEE His work explores advanced networking paradigms like Named Data Networking (NDN) , IoT virtualization via platforms such as VirIoT , and edge cloud computing for multimedia workflows. Key contributions include optimized cache replacement algorithms and service function chaining frameworks to enhance resource utilization and reduce latency. His scientific awards include: Fellow , Institute of Electronics, Information and Communication Engineers (2018) Chairman's Award , IEICE Communication Systems Committee (2013) NAKAZATO's publications (94 papers, h-index 10) address topics like blockchain performance , NDN mobility support , and energy-efficient computing . His research projects involve collaborations with international teams on smart city applications and container orchestration using Kubernetes.
Masao Yanagisawa is a Professor at Waseda University's School of Fundamental Science and Engineering, with over 25 years of academic experience since 1998. An IEEE and ACM member, he holds a Doctor of Engineering degree from Waseda University.
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.
Atsushi Shimojima is a Professor at Waseda University's School of Advanced Science and Engineering , specializing in siloxane-based nanomaterials and self-healing materials . His research focuses on molecular-scale assembly of inorganic-organic hybrids, pore structure engineering, and photomechanical systems. He has published extensively in journals like Chemistry – A European Journal and ACS Nano . Education: PhD in Engineering from Waseda University Research Areas: Self-healing materials, porous materials, sol-gel methods Research Interests encompass designing siloxane networks for intrinsic self-healing, creating ordered nanoporous structures through cage siloxane assembly, and developing photoresponsive hybrids. His work bridges zeolite chemistry and dense silica polymorphs through framework density optimization. Scientific Awards include the Waseda Research Award (2017) Japan Ceramic Society Progress Award (2006) . He is a member of multiple chemical societies like the International Sol-Gel Society and American Chemical Society. His publications demonstrate expertise in siloxane bond dynamics, cage-type germoxanes, and hierarchical nanoporous material synthesis. Recent studies highlight mesoscale structural control and fluoride ion encapsulation strategies.
Motomu Sakai is an Assistant Professor (non-tenure-track) in the Department of Applied Chemistry at Waseda University's School of Advanced Science and Engineering. He holds a Doctor of Engineering degree from Waseda University (awarded February 2022). His research focuses on developing advanced separation technologies, particularly zeolite membranes for applications in energy-efficient processes and environmental solutions. Research interests span inorganic materials chemistry with emphasis on: Membrane separation processes (forward osmosis, vapor permeation) Synthesis and modification of microporous materials (zeolites, MOFs) Adsorption mechanisms and separation of hydrocarbons Defect engineering and performance optimization of ceramic membranes Membrane reactor design for chemical reactions (e.g., esterification, RWGS) His publications demonstrate strong focus on: Zeolite membrane performance for water treatment and gas separation Innovations in membrane synthesis (e.g., OSDA-free methods, defect-healing techniques) Structure-property relationships in nanoporous materials Applications in carbon neutrality and resource recovery Major scientific recognitions include: Nano Technology Forum Award (2024) for microporous membrane development Young Scientist Award from The Membrane Society of Japan (2023) Satomi Award (2023) for zeolite nanosheet research Multiple conference awards for membrane separation innovations Leads research projects funded by JSPS and foundations focusing on: Water vapor separation membranes for CO 2 recycling reactors (2024-2027) Zeolite pore connectivity quantification (2025-2026) Food dehydration membranes (2024) Supervises laboratory courses in Fundamental Science and Engineering at both undergraduate and graduate levels.
Shunji Ohta is a Professor at the Graduate School of Human Sciences , Waseda University, specializing in environmental dynamic analysis with a focus on climate-vegetation interactions and vector ecology. Doctor of Human Sciences from Waseda University (1996) Member of Japanese Society of Biometeorology and Ecological Society of Japan Research interests include: Malaria vector distribution modeling under climate change Urban heat island mitigation through green infrastructure Paddy water temperature dynamics Population dynamics of disease-carrying mosquitoes Global carbon budget analysis Recent publications demonstrate strong interdisciplinary focus across Environmental Science , Public Health , and Agricultural Meteorology . Key projects involve: Climate-driven mosquito population forecasting (2018-2021) High-resolution environmental data modeling (2016-2017) Heat island microclimate studies (2010-2013) Teaching activities span multiple courses in Global Ecosystem Sciences and Environmental Monitoring at both undergraduate and graduate levels.
TSUMURA Tomoaki is a Professor at the Department of Information Engineering, Graduate School of Engineering, Nagoya Institute of Technology. With a Doctor of Informatics from Kyoto University (2004), he has established himself as a leading researcher in computer architecture, parallel processing, and high-performance computing. His academic career spans from research assistant positions at Kyoto and Toyohashi Universities to his current professorship at Nagoya Institute of Technology. Graduated from Faculty of Engineering, Kyoto University (1996) Master of Engineering, Graduate School of Engineering, Kyoto University (1998) Doctor of Informatics, Graduate School of Information and Communication, Kyoto University (2004) Professor TSUMURA's research focuses on parallel processing systems, high-performance computing architectures, and innovative memory systems. His work bridges theoretical computer science with practical implementations, particularly in transactional memory systems, auto-memoization processors, and GPU computing. His research group has made significant contributions to shared memory parallel computing platforms that balance productivity and performance, with recent work extending to approximate computing applications and energy-efficient processor designs. His publication record shows a consistent output of high-impact research, with numerous papers presented at prestigious venues like xSIG, IEEE conferences, and IPSJ journals. The research trends indicate a strong focus on practical computing systems that address real-world challenges in parallelism, memory management, and energy efficiency. Recent work has particularly emphasized GPU computing, transactional memory systems, and precision optimization in numerical computing. Computer Science Field Achievement Award (IPSJ, 2019) Activity Contribution Award (IEICE, 2017) Multiple Best Paper/Research Awards from IEEE, ICNC, and xSIG conferences 1st Place in Championship Branch Prediction (CBP 2025) Professor TSUMURA has successfully secured substantial research funding, including multiple JSPS Grant-in-Aid projects spanning from 2006 to the present. His current major project "Software cache and distributed time management for shared memory massively parallel computing platform" (2025-2029) continues his long-standing research trajectory. He actively advises numerous graduate students, with many appearing as first authors on publications where he serves as corresponding author. His leadership extends to committee memberships including Chair of the IPSJ System Architecture Research Group and Editor-in-Chief of the IPSJ Journal of Computing Systems. Through his laboratory (tsumulab.org), Professor TSUMURA leads a research team focused on next-generation computing systems, with particular emphasis on practical implementations of theoretical concepts in computer architecture. The lab maintains strong industry and academic collaborations, evidenced by joint research projects and participation in international competitions like Championship Branch Prediction.
Hiroshi Matsuo is a Professor in the Department of Information Engineering at Nagoya Institute of Technology's Faculty of Engineering, with additional affiliations in the Graduate School of Engineering (Network Program) and Information Technology Center. His research focuses on distributed systems, network architecture, and operating systems with practical applications in cloud infrastructure. Education: Doctor of Engineering, Nagoya Institute of Technology (1989) Master of Engineering, Nagoya Institute of Technology Bachelor of Engineering, Nagoya Institute of Technology (1983) Matsuo's research centers on performance optimization in virtualized environments, particularly addressing bottlenecks in network I/O, distributed databases, and cloud-native applications. His work bridges theoretical informatics with practical system implementations, emphasizing real-world scalability and efficiency in high-throughput computing environments. Key contributions include novel caching mechanisms, transaction processing acceleration, and resource contention solutions for virtual network functions. Recent publications demonstrate consistent focus on network function virtualization and distributed systems, with increasing emphasis on hardware-aware optimizations and transparent proxy architectures. His team's work shows strong progression from foundational operating system research toward cloud-native infrastructure solutions, maintaining relevance in both academic and industrial contexts. Awards: IEEE NFV-SDN 2018 Best Paper Award 12th IEICE Communications Society Paper Award (2017) 2022 IEICE Information and Communication Management Research Award 1st International Conference on Networking and Computing Best Paper Award (2010) JAWS2010 Excellent Paper Award Matsuo has supervised numerous graduate students evident through co-authorship patterns in publications, particularly in network systems and distributed computing. His research has been supported by institutional projects on distributed processing frameworks, though specific grant details aren't publicly documented. He maintains active industry collaborations through his work on Microsoft Defender integration and enterprise networking solutions. His laboratory within Nagoya Institute of Technology's Network Field focuses on practical systems research, combining DPDK-based implementations with theoretical performance modeling. Current work emphasizes cache optimization for virtualized network functions and transaction processing acceleration in distributed databases, maintaining strong ties to industry partners through the Information Technology Center.
Toshiro Nunome serves as Associate Professor in the Department of Information Engineering at Nagoya Institute of Technology, Japan, specializing in network engineering and Quality of Experience (QoE) optimization for multimedia systems. His research focuses on Information-Centric Networking (ICN), adaptive bitrate streaming, and multi-view video transmission, with significant contributions to IEEE and IEICE publications. Dr. Nunome earned his Doctor of Engineering and Master of Engineering degrees from Nagoya Institute of Technology, where he also completed undergraduate studies in the Faculty of Engineering, Department of Electrical and Computer Engineering (1998). Prior to academia, he worked as Researcher at Pioneer Corporation's AV & Network Development Center (2000-2001). Doctor (Engineering), Nagoya Institute of Technology Master (Engineering), Nagoya Institute of Technology B.E., Nagoya Institute of Technology (1998) His research centers on user-perceived quality in multimedia delivery systems, particularly investigating cache control mechanisms in ICN/CCN architectures, multi-view video synchronization, and protocol impacts (HTTP/3, WebRTC) on streaming quality. Current work addresses emerging challenges in 5G environments, multi-link operation (MLO), and cloud gaming through rigorous subjective evaluation methodologies. Key innovations include cache hit judgment algorithms for adaptive streaming and QoE models for viewpoint changes in multi-view content. Analysis of his 10 recent publications (2024-2025) reveals a cohesive research trajectory emphasizing practical ICN/CCN implementations for QoE enhancement. The work spans theoretical modeling (cache decision policies) and applied studies (WebRTC in cloud gaming), consistently targeting real-world network constraints. A notable trend involves cross-layer optimization techniques bridging network protocols and human perception metrics. Dr. Nunome's scholarly recognition includes: IEICE Communication Quality Study Group 2021 Meritorious Service Award (2022) ICCE-TW 2021 Best Paper Award Third Place (2021) IEICE Information and System Society Activity Meritorious Service Award (2019) Multiple IEICE Communication Society Activity Awards (2010-2019) He currently leads the Japanese Grant-in-Aid project 'ICN/Wireless LAN Integrated Scalable Distribution Technology' (2024-2027) as Principal Investigator, continuing a 20-year history of competitive funding including 'QoE-based Multi-View Video Transmission' (2011-2014). His professional service spans editorial roles (IEICE Transactions) and committee leadership in IEICE Technical Committees on Communication Quality and Information-Centric Networking. Dr. Nunome actively contributes to the IEICE Technical Committee on Communication Quality and IEICE Technical Committee on Information-Centric Networking, while maintaining affiliations with IEEE, IEICE, and ITE societies. His work bridges academic research and industrial applications through ongoing collaborations with Japan's networking community.
Yonghwan Kim serves as an Associate Professor in the Department of Computer Science within the Graduate School of Engineering at Nagoya Institute of Technology. His academic foundation includes a Doctorate (2015) and Master's (2011) in Information Science from Osaka University, where he completed both graduate programs. Dr. Kim's research spans distributed algorithms with emphasis on autonomous mobile robot systems, fault tolerance, and self-stabilization. His work addresses critical challenges in multi-robot coordination under asynchronous scheduling, defected view models, and dynamic network topologies. Key research areas include: Distributed algorithm design for mobile entities Self-stabilizing graph construction techniques Optimization of robot gathering and dispersion Fault-tolerant systems in constrained environments His publication record reveals strong focus on theoretical foundations with practical applications, particularly in robotics and network systems. Recent work (2022-2024) demonstrates increasing complexity in handling defected views, multi-color luminous robots, and dynamic grid environments. His research shows consistent progression from foundational graph algorithms toward sophisticated mobile entity coordination systems. Professional recognition includes the Engineer of Information Processing qualification and multiple principal investigator roles for competitive research grants. His committee service spans prestigious conferences including SSS, DISC, and CANDAR where he served on program committees from 2018-2024. Dr. Kim actively mentors researchers, evidenced by his role as corresponding author for junior colleagues' publications. His grant portfolio demonstrates leadership in projects like 'Distributed Graph Algorithms for Unpredictable Dynamic Environments' (2020-2024) with ¥16,120,000 funding, and internal university grants focused on low-functionality mobile terminals and network optimization.
Tomonori Ihara is a researcher affiliated with the Tokyo Institute of Technology , focusing on advanced ultrasonic measurement techniques for fluid dynamics and industrial applications. His work spans robotics for environmental monitoring, multiphase flow analysis, and high-temperature material studies. Education: Doctor (Engineering) from Tokyo Institute of Technology (2015). Research Interests: He specializes in Ultrasonic Doppler Velocimetry , Bubble Dynamics , and Swirling Flow Analysis , applying these to critical areas like nuclear engineering, molten glass flow, and water leak detection. His methodological contributions include noise modeling, phased-array systems, and multi-dimensional velocity profiling. Patents: He holds multiple registered patents for ultrasonic measurement devices, including flow velocity vector distribution systems and buffer rod designs for molten materials. His 23 publications (2012–2020) emphasize practical solutions for industrial fluid monitoring, with a focus on robotics and sensor innovation.
