جست‌وجوی استاد و پژوهشگر

• Robotics
• Mechanical Engineering
• Soft Robotics
• +۲ مورد دیگر

Yuji Fujitsuka is a Research Fellow at Institute of Science Tokyo specializing in elastic telescopic arm robotics. His primary affiliation is with the university's mechanical engineering research ecosystem, where he leads the Elastic Telescopic Arm Research Laboratory. Collaborating closely with Professor Gen Endo, he contributes to advanced robotic systems development. Research focuses on innovative robotic manipulator designs, particularly elastic telescopic mechanisms enabling multi-directional motion, payload optimization, and integration with tendon-driven systems like 'Super Dragon'. His work bridges mechanical engineering and robotics through spiral tube actuators, quasi-static balancing (LIBRA-II), and wheeled robot mobility enhancement. Recent publications (2023-2025) reveal a clear research trajectory: foundational bending mechanisms (2023) → Super Dragon integration (2024) → advanced mobility solutions (2025). This progression demonstrates increasing technical sophistication in real-world robotic applications. Key achievements include the patented 'Telescopic Robot Arm and Drive Method' (2023-2025) and multiple presentations at JSME, SICE, and IEEE/SICE conferences. His work consistently addresses practical challenges in robotic arm extension, contraction, and spatial maneuvering. Professor Fujitsuka actively supervises students including Koki Hasegawa and Ryosuke Kiyohara, fostering hands-on development of tendon-driven systems and experimental validation protocols. His lab provides opportunities for students to contribute to patentable technologies and international conference presentations.

• Optical Fiber Sensors
• Brillouin Scattering
• Distributed Sensing
• +۳ مورد دیگر

Kouhei Noda is a Researcher at Tokyo Institute of Technology , specializing in Optical Fiber Sensors , Brillouin Scattering , and Distributed Sensing . His work focuses on advancing Brillouin optical correlation-domain reflectometry (BOCDR) for high-resolution, real-time tactile and temperature sensing applications. Education: Doctor (Engineering), Tokyo Institute of Technology (2023). Research Interests: Noda's research explores Brillouin scattering for distributed strain/temperature sensing, tactile sensors using polymer optical fibers, and polarization-sensitive reflectometry to enhance measurement accuracy. He investigates low-coherence light sources and cost-effective fiber amplifier configurations to improve system performance. Recent Article Trends: His 15 most recent publications (2020-2025) emphasize high-speed distributed sensing , real-time touch/tactile detection , and systematic error compensation in BOCDR systems. Key subfields include noise floor distortion compensation , low-coherence Brillouin sensors , and polymer fiber Bragg grating applications . Technical Contributions: Noda has co-authored patents related to wheelchair motorization devices and multimode FBG temperature stabilization . His collaborations with researchers like Yosuke Mizuno and Kentaro Nakamura span experimental validation, simulation analysis, and hardware optimization for optical sensing systems.

Youki Kadobayashiمشاهده پروفایل

استاد

• Internet Engineering
• Web Security
• Cybersecurity Education
• +۴ مورد دیگر

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.

Daisaku Yokoyamaمشاهده پروفایل

استادیار

• Parallel and Distributed Processing
• Combinatorial Search
• Game Tree Search
• +۴ مورد دیگر

Daisaku Yokoyama is an Assistant Professor at the Institute of Industrial Science, University of Tokyo, where he works in Department 3 of the Kitsuregawa-Toyoda Laboratory. His research focuses on parallel and distributed processing, combinatorial search, game tree search, and other search processes. He is also involved in the development of "Gekisashi," a computer shogi (Japanese chess) player. His academic background includes: March 1998: Graduated from the Department of Electronic and Information Engineering, Faculty of Engineering, The University of Tokyo March 2000: Completed Master's course in Information Engineering at the University of Tokyo 2002.3: Graduated from the Doctoral Program in Information Engineering, Graduate School of Engineering, The University of Tokyo September 2006: Obtained a PhD in Science from the Graduate School of Frontier Sciences, University of Tokyo Daisaku Yokoyama's research interests primarily center around parallel and distributed computing systems, with a particular focus on combinatorial search algorithms and game tree search techniques. His work bridges theoretical computer science with practical applications, especially in the domain of computer shogi where he has developed "Gekisashi." Beyond game AI, his research has expanded into big data analytics, particularly in transportation systems where he analyzes passenger flows in metro networks and driver behavior using vehicle recorder data. His work demonstrates a consistent thread of applying parallel processing techniques to solve computationally intensive problems across various domains. Yokoyama's publication record shows a clear evolution from foundational work in parallel combinatorial optimization (PopKern library) to more applied research in computer shogi and eventually to big data applications in transportation systems. His early work established frameworks for parallel search algorithms, while more recent publications demonstrate applications of these techniques to real-world problems involving massive datasets from metro systems and vehicle recorders. His research consistently emphasizes the importance of domain-specific knowledge in optimizing parallel algorithms. His notable scientific achievements include: DBSJ Best Paper Award 2014 for "Application and Evaluation of a Bayesian-Based Monte Carlo Tree Search Algorithm to Shogi" Game Programming Workshop Excellent Paper Award (awarded twice) Throughout his career, Yokoyama has been actively involved in academic service, serving on editorial boards, program committees, and as an organizer for numerous conferences and workshops related to programming, parallel computing, and game AI. His work on the Gekisashi shogi engine represents a long-term research project that has evolved from basic search algorithms to sophisticated AI systems, demonstrating both theoretical rigor and practical implementation skills. He is part of the Kitsuregawa-Toyoda Laboratory at the Institute of Industrial Science, University of Tokyo, which focuses on advanced computing systems, database technologies, and large-scale data processing. The laboratory provides a collaborative environment for research spanning theoretical computer science to real-world applications in transportation analytics and game AI.

• Computational Biology
• Bioinformatics
• Privacy-Preserving Data Mining
• +۵ مورد دیگر

Kana Shimizu is a Professor at Waseda University’s Faculty of Science and Engineering, School of Fundamental Science and Engineering, and a leading authority on privacy-preserving algorithms for genome and biomedical data. Since obtaining her Dr.Eng. from Waseda, she has held positions at AIST and a visiting investigator role at Memorial Sloan-Kettering Cancer Center, advancing to full Professor at Waseda in 2018. Education: Dr.Eng., Waseda University M.Eng., Waseda University (Dept. of Information Science) B.Eng., Waseda University (School of Science and Engineering) Research Interests: Prof. Shimizu integrates cryptography with life-science data analytics, developing homomorphic encryption and secret-sharing protocols that enable secure genome search, private chemical database queries, and privacy-preserving machine learning. She also contributes to computational biology through algorithms for next-generation sequencing, structural bioinformatics, and prediction of intrinsically disordered proteins. Publication Trends: Her recent works (2022-2024) emphasize practical privacy technologies—secure range queries, function secret sharing, and gradient-clipping for synthetic genomes—while earlier high-impact papers established fast similarity search (SlideSort), binding-site databases (PoSSuM), and encrypted genomic search using the Burrows-Wheeler transform, collectively bridging algorithmic innovation and real-world biomedical privacy needs. Scientific Awards: KDDI Foundation Achievement Award 2022 MEXT Commendation for Science and Technology (Research) 2018 Multiple best-paper/demo awards at CSS, IIBMP, and domestic bioinformatics meetings Grants & Advising: She currently leads JSPS KAKENHI (S) on “Compressed Secure Computation for Large-Scale Data” and an AMED project on precise cancer-genome graphs. She serves as advisor/evaluator for JST PRESTO, AMED, NBDC, and the Tokyo High Court, and has supervised numerous bachelor theses at Waseda. Labs & Teams: Prof. Shimizu heads a laboratory within the School of Fundamental Science and Engineering at Waseda, collaborating with national centers (AIST, RIKEN) and international partners (MSKCC, Finland Tekes/AF), focusing on encrypted bioinformatics platforms and high-performance genomic algorithms.

• Learning Support System
• Intelligent Informatics
• Human Interface and Interaction
• +۱ مورد دیگر

Ruichen Cong is currently an Assistant Professor (without tenure) at Waseda University's School of Human Sciences and a Guest Lecturer at Tokyo City University. He earned his Bachelor's, Master's, and Doctorate in Human Sciences from Waseda University (2020, 2022, 2025). Graduate School of Human Sciences, Waseda University (2022-2025) Graduate School of Human Sciences, Waseda University (2020-2022) School of Human Sciences, Waseda University (2016-2020) His research focuses on health informatics, intelligent informatics, and human-computer interaction. He specializes in causal discovery, feature selection, and decentralized systems for health data sharing. His work includes wearable device data analysis, cognitive load measurement, and accessibility technologies. Recent publications highlight his expertise in causal graphs for health risk factors, blockchain-based data sharing, and pandemic-related youth healthcare strategies. He applies machine learning to multidimensional health data and designs systems for people with disabilities. Scientific Awards: Research Encouragement Award, 65th Japanese Society of Social Medicine Annual Meeting (2024) Overseas Travel Expense Support, Japan Science and Technology Foundation (2023) Ogawa Memorial Foundation General Scholarship, Waseda University (2021) Ruichen Cong has received grants for projects including multimodal health data analysis, blockchain-integrated health systems, and barrier-free infrastructure. He actively contributes to academic societies like IEEE and JSAI. He serves as Program Chair for the 2025 International Workshop on LLM and Agentic AI and participates in IEEE and ACM conference committees. His teaching includes Data Science Literacy at Tokyo City University and TA roles for courses like Algorithms, Human-Computer Interaction, and Data Literacy.

• Fundamental Physical Chemistry
• Nanometer-Scale Chemistry
• Near-Field Optics
• +۸ مورد دیگر

Kohei Imura is a Professor at the School of Advanced Science and Engineering of Waseda University , where he leads research in Nanophotonics , Plasmonics , and Surface-Enhanced Spectroscopy . His work focuses on the optical properties of metal nanostructures, including gold and silver nanoparticles , and their applications in bioimaging , chemical sensing , and optical field manipulation . Research Areas : Fundamental Physical Chemistry, Nanometer-Scale Chemistry Key Techniques : Scanning Near-Field Optical Microscopy (SNOM), Time-Resolved Spectroscopy, Electromagnetic Simulations His recent publications highlight three-dimensional plasmon mode mapping , chiral nano-optical field control , and enhanced photoluminescence via plasmonic coupling. His studies on gold nanoplates and carbon dot composites reveal mechanisms for improving light-matter interactions at the nanoscale. Scientific Awards include the Minister of Education, Culture, Sports, Science and Technology Award for Young Scientists (2012), Chemical Society of Japan Progress Award (2007), and multiple Spectroscopical Society of Japan recognitions. He actively contributes to academic societies, serving in roles such as JSPS Special Researcher Review Committee and Molecular Science Society Officer .

• Structural optimization
• Additive Manufacturing
• Vibration Engineering
• +۵ مورد دیگر

Dr. Akihiro Takezawa is a Professor in the Department of Mechanical Science and Aeronautics and Astronautics at Waseda University's School of Fundamental Science and Engineering. Previously, he held positions at Hiroshima University Graduate School of Engineering and FANUC Corporation. His academic career spans structural optimization, additive manufacturing, and vibration engineering, with particular expertise in topology optimization for advanced material design. Dr. Takezawa's research interests focus on structural optimization methodologies, additive manufacturing processes, and vibration engineering applications. His work bridges theoretical optimization techniques with practical engineering applications, particularly in designing lattice structures with tailored mechanical and thermal properties. He has made significant contributions to the field of topology optimization for additive manufacturing, developing methods to control thermal deformation, optimize lattice structures for specific mechanical properties, and design metamaterials with unique characteristics. Analysis of his recent publications reveals a strong trend toward practical applications of topology optimization in additive manufacturing, with increasing focus on multi-physics problems involving thermal, mechanical, and fluid dynamics. His research has evolved from fundamental optimization methodologies to their application in complex engineering problems such as energy-absorbing metamaterials, thermal management systems, and vibration control devices. Japan Society of Mechanical Engineers, Design Engineering and Systems Division Achievement Award (2020.11) 2016 Mechanical Mechanics and Measurement Control Division General Award from the Japan Society of Mechanical Engineers (2017.08) Minister of Education, Culture, Sports, Science and Technology Young Researcher Award (2017.04) Japan Society of Mechanical Engineers, Design Engineering and Systems Division, Frontier Achievement Award (2015.09) The 2015 JACM Award for Young Investigators in Computational Mechanics (2015.07) Dr. Takezawa has supervised numerous graduate students and has been involved in multiple research projects funded by Japanese government agencies and industry partners. His research has resulted in over 100 publications with more than 5,000 citations according to Google Scholar, demonstrating significant impact in the fields of structural optimization and additive manufacturing. His laboratory at Waseda University focuses on advancing computational methods for designing next-generation materials and structures. Dr. Takezawa leads a research group that combines computational mechanics, materials science, and manufacturing technology to develop innovative solutions for engineering challenges. His team utilizes advanced optimization algorithms, finite element analysis, and additive manufacturing techniques to create novel material architectures with tailored properties for specific applications.

• Computational Fluid Dynamics
• Turbomachinery
• Fluid Engineering

Nobumichi Fujisawa is an Associate Professor at Waseda University, School of Fundamental Science and Engineering, specializing in Fluid Engineering and Turbomachinery . His research focuses on unsteady flow phenomena in centrifugal and axial compressors, including stall inception mechanisms, tip leakage vortices, and vortex-induced noise reduction strategies. Current affiliations: Waseda University (2024–present), Leibniz Universität Hannover (Visiting Researcher, 2025–2026) Past roles: Waseda University (2015–2024) Research interests span computational fluid dynamics (CFD) applications in turbomachinery, flow separation analysis, and aerodynamic stability enhancement through geometric modifications like tapered diffuser vanes and bleed slots. His work reveals flow blockage dynamics in diffuser passages and their correlation with stall development. Scientific awards include: 2024 Turbomachinery Society of Japan Best Paper Award 2021 JSME Paper Award 2018 ASME Turbo Expo Best Paper 2016 Turbomachinery Society Young Researcher Award

• Power Engineering
• Energy Management Systems
• Photovoltaic Power Generation
• +۳ مورد دیگر

Akihisa Kaneko is an Assistant Professor at Waseda University's Faculty of Science and Engineering and a Junior Researcher at the Advanced Collaborative Research Organization for SmartSociety. His research focuses on power systems engineering with particular emphasis on integrating renewable energy sources into electrical grids. Dr. Kaneko received his Doctor of Engineering from Waseda University in 2021, following his studies in Electrical Engineering and Bioscience at the Graduate School of Advanced Science and Engineering. His academic journey at Waseda spans from his undergraduate studies (2012-2016) through his doctoral work (2018-2021). Dr. Kaneko's research interests center around power engineering, with specific focus on energy management systems, photovoltaic power generation, smart grid technologies, and voltage control in both transmission and distribution systems. His work addresses critical challenges in modern power systems, particularly the integration of renewable energy sources and the development of advanced control strategies for maintaining grid stability and reliability. He has made significant contributions to understanding how photovoltaic systems, electric vehicles, and other distributed energy resources impact power system operations, and has developed innovative solutions for voltage regulation, congestion management, and optimal system configuration. His publication record demonstrates a strong focus on practical applications of power system research, with numerous papers addressing real-world challenges in Japanese distribution networks. Recent work shows increasing integration of machine learning techniques with traditional power system engineering to develop more adaptive and intelligent grid control methods. His research spans both theoretical development and practical implementation, often validated using actual distribution network models from Japan. Young engineer Oral presentation Competition (YOC) Excellent Presentation Award, The Institute of Electrical Engineers of Japan (2022) Young engineer Oral presentation Competition Encouragement Award, The Institute of Electrical Engineers of Japan (2020) Encouragement Award, The Institute of Electrical Engineers of Japan (2020) Young engineer Poster Competition (YPC) Encouragement Award, The Institute of Electrical Engineers of Japan (2016) Dr. Kaneko is actively involved in several research projects, including "Systematization of cooperative next-generation distribution system operation method for mass introduction of photovoltaic power generation" funded by the Japan Society for the Promotion of Science. His work bridges theoretical power system analysis with practical implementation considerations, focusing on solutions that can be deployed in existing infrastructure. He collaborates extensively with industry partners and other academic researchers to address the pressing challenges of modernizing electrical grids for renewable energy integration. As a member of the Advanced Collaborative Research Organization for SmartSociety at Waseda University, Dr. Kaneko works within a multidisciplinary team focused on developing smart society technologies. His research group specializes in power system analysis, grid integration of renewable energy, and development of advanced control algorithms for maintaining grid stability in the face of increasing distributed energy resources.

• Econometrics
• Applied Econometrics
• Regression Discontinuity Design
• +۵ مورد دیگر

Yoichi ARAI is an Associate Professor at the School of Social Sciences, Waseda University, specializing in econometrics and applied economic analysis. He holds a Ph.D. in Economics from the University of California, San Diego, and has established himself as a leading researcher in regression discontinuity designs, cointegration analysis, and program evaluation methodologies. Dr. ARAI's educational background includes a doctoral degree from UC San Diego, one of the world's leading institutions for econometric theory. His academic journey has positioned him at the intersection of theoretical econometrics and practical policy evaluation. Dr. ARAI's research focuses on econometrics and applied econometrics , with particular expertise in regression discontinuity designs, bandwidth selection methods, cointegration testing, and program evaluation. His work bridges theoretical developments with practical applications in labor economics, education economics, and monetary policy. His research has significantly advanced methodological approaches for causal inference in non-experimental settings, particularly through innovations in regression discontinuity frameworks and treatment effect estimation. His contributions have been instrumental in developing more robust statistical tests for identifying assumptions in fuzzy regression discontinuity designs and optimizing bandwidth selection procedures for both sharp and fuzzy regression discontinuity estimators. Analysis of Dr. ARAI's publication record reveals a strong trajectory of methodological innovation in econometrics, particularly in regression discontinuity designs and cointegration analysis. His recent work (2020-2025) focuses on high-dimensional extensions of regression discontinuity methods, optimal bandwidth selection, and testing identifying assumptions. Earlier work (2000-2015) established foundational contributions to cointegration testing with structural breaks and time series analysis. His research demonstrates consistent contributions to both theoretical econometrics and applied policy evaluation, with particular relevance to Japanese economic issues including educational upgrading of youth and labor market dynamics. Dr. ARAI has received recognition through substantial research funding, including multiple Grants-in-Aid for Scientific Research from the Japan Society for the Promotion of Science (JSPS). His projects include "Development and Application of Policy Evaluation Methods Based on Dynamic Structural Models" (2024-2029), "Econometrics for Policy Evaluation and its Application" (2015-2019), and "Econometric Analysis of Program Evaluation and Its Application to Unemployment Insurance Policy" (2011-2015). As an educator, Dr. ARAI teaches advanced econometrics courses at both graduate and undergraduate levels, including "Research on Econometrics for Policy Evaluation," "Basic Data Analysis (Regression Analysis)," and "Applied Econometrics." His teaching emphasizes the practical application of econometric methods to real-world policy questions. He has supervised numerous research projects and contributes significantly to the academic community through committee memberships with the Japan Statistical Society, Japanese Economic Association, American Economic Association, and Econometric Society.

• Macroeconomics
• Economic growth
• Technological change
• +۴ مورد دیگر

Professor Koki Oikawa is an academic researcher at Waseda University's Faculty of Social Sciences, School of Social Sciences, specializing in macroeconomics, economic growth, and innovation economics. With a Ph.D. in Economics from New York University (2007), he has established himself as a prominent researcher in monetary economics and firm dynamics, with significant contributions to understanding the relationship between inflation, monetary policy, and economic growth. His primary research interests focus on Macroeconomics, Economic growth, Technological change, Firm dynamics, and Social learning. Oikawa's work bridges theoretical macroeconomic models with empirical analysis of firm-level data, particularly examining how price stickiness, inflation, and monetary policy affect innovation incentives and resource allocation. His research often incorporates Japanese economic data to provide comparative insights with the United States. Oikawa has published 12 refereed journal articles with over 268 Google Scholar citations and an h-index of 8. His recent work examines reallocation effects of monetary policy, firm exit during the pandemic, and the tradeoffs between short-term and long-term impacts of monetary easing. His research consistently explores how firm-level dynamics aggregate to macroeconomic outcomes, with particular attention to innovation processes, technological diffusion, and the role of uncertainty in economic growth. He has received multiple research grants from the Japan Society for the Promotion of Science, including a current project (2025-2030) on 'Empirical Study on General Purpose Technologies: Generation, Diffusion, and Impact' and a recently completed project (2021-2025) analyzing economic growth policies based on matching between companies and researchers. His professional affiliations include the Japanese Economic Association, American Economic Association, and Econometric Society. As an educator, Oikawa teaches advanced macroeconomics courses at Waseda University's Graduate School of Social Sciences, including Macroeconomics I-III, Advanced Macroeconomics, and specialized seminars on applied macroeconomics. His teaching focuses on both theoretical foundations and empirical applications, preparing students for research in modern macroeconomics.

• Social Systems Engineering
• Social Informatics
• Artificial Intelligence
• +۳ مورد دیگر

Yuya IEIRI serves as an Assistant Professor (non-tenure-track) at Waseda University's Graduate School of Information, Production, and Systems since 2022. He holds a Ph.D. in Engineering from Waseda University (2021) and has held various research positions including a Visiting Research Fellow at University of Surrey and JSPS Research Fellow. His academic work bridges social systems engineering, information technology, and community development. Dr. IEIRI's research focuses on Social Systems Engineering, Social Informatics, Artificial Intelligence, Human-Computer Interaction, Tourism Informatics, and Internet of Things. His work particularly examines how digital technologies can revitalize commercial districts, analyze tourist behavior, and create value in local communities. His research employs network science, augmented reality applications, and consumer behavior analysis to address real-world community challenges. His publication record demonstrates consistent output with 31 papers indexed in Scopus (60 citations, h-index 4) and 98 citations in Google Scholar (h-index 5, i10-index 3). His recent work shows a clear trajectory toward analyzing second-hand luxury markets using network motif analysis, community management in low-digitalized environments, and tourism resource development. Notable Awards: Teaching Award (Spring 2022) and 2023 Waseda University Technical Writing & Presentation Multiple Best Presentation Awards at international conferences (2020-2022) 7th FOST Newcomer Award (2020) Azusa Ono Memorial Award from Waseda University (2019) Dr. IEIRI actively contributes to academic service as a peer reviewer for the International Conference on Collaboration Technologies and Social Computing and as a navigator for the Kitakyushu Future Creation Seminar. He has received research funding from JST PRESTO, JSPS Grants-in-Aid, and other foundations to support his work on social capital development, tourist route design, and community computing systems. His teaching portfolio includes Probability and Statistics, Fundamentals of Industrial and Management System Engineering, Technical Writing & Presentation, and Special Exercises in Community Computing at Waseda University's Graduate School of Information, Production, and Systems.

• Industrial Engineering
• Operations Research
• Optimization
• +۵ مورد دیگر

Shunichi Ohmori , a Professor at the Faculty of Science and Engineering , Waseda University , holds a Doctorate in Engineering from the same institution. His academic journey includes continuous affiliation with Waseda University since 2011, currently serving as a faculty member and concurrently as Director of Research Institute at the Institute of Global Production & Logistics (2022-2026). Education: Doctorate (2009-2012), Master's (2007-2009), and Bachelor's (2004-2007) from Waseda University His research focuses on industrial engineering and operations research , with specific interests in optimization , facility planning , logistics , and supply chain management . He has developed innovative frameworks for: Robust supply chain design under disruption risks Multi-echelon inventory optimization 3D facility layout planning with pipeline arrangements Collaborative vehicle routing cost allocation Green product portfolio strategies under uncertainty His publication record demonstrates expertise in stochastic optimization (15+ peer-reviewed papers) and heuristic algorithms (14+ conference proceedings). He has received multiple Best Paper Awards (2012-2016) and contributed to curriculum development through courses like Advanced Facilities Planning , Supply Chain Transformation , and Logistics at both undergraduate and graduate levels.

• Environmental economics
• Real Estate Economics
• Urban Economics
• +۲ مورد دیگر

Sho Kuroda is an Assistant Professor at Waseda University 's Faculty of Commerce (non-tenure-track) since October 2023, concurrently serving as a researcher at the Research Institute of Business Administration (RIBA). He earned his Ph.D. in Policy and Planning Sciences from University of Tsukuba in September 2023. His research focuses on applied econometrics , environmental economics , real estate , urban economics , and regional sciences . His work includes discrete-continuous choice models for carbon policy analysis, spatial econometric studies on automobile demand, and computational methods for energy-resilient communities. Recent publications (2021-2025) examine carbon dividend frameworks, transportation emission reductions, and hedonic models for urban view valuation. Articles demonstrate expertise in policy simulation , spatial modeling , and renewable energy integration . He teaches Introductory Econometrics , Basic Statistics , and Data Analysis Using Statistical Packages at Waseda University's Graduate Schools of Commerce and Accountancy. Concurrent roles include developer of educational materials for R/Stata-based statistical analysis and causal inference.