جستجوی استاد راهنمای دانشگاهی

• Intelligent robotics
• Mechanics and mechatronics
• Robotics and intelligent system
• +۳ مورد دیگر

Shigeki Sugano is a Professor at Waseda University's Faculty of Science and Engineering, School of Creative Science and Engineering. He has served as Senior Dean of the Faculty of Science and Engineering (2020-2024) and Dean of the School of Creative Science and Engineering (2014-2020). His academic journey at Waseda spans from Research Assistant (1986-1990) to Assistant Professor (1990-1992), Associate Professor (1992-1998), and Professor (1998-present), with a visiting scholar position at Stanford University (1993-1994). Dr. Sugano's research focuses on intelligent robotics, mechanics and mechatronics, and robotics and intelligent systems. His work emphasizes tactile sensing, human-robot collaboration, robotic manipulation, and assistive technologies. His extensive publication record demonstrates expertise in developing practical robotic systems for applications in disaster response, healthcare, infrastructure inspection, and human augmentation. He has made significant contributions to the development of tactile sensors, human-robot interaction frameworks, and robotic systems for gait analysis and assistance. His recent publications (2024-2025) reveal a strong focus on tactile sensing technologies (H-PME sensors, uSkin systems), human-robot collaboration frameworks, and advanced manipulation techniques using deep learning. His research integrates mechanical engineering principles with AI techniques to create practical robotic solutions. The consistent publication output across multiple high-impact venues demonstrates sustained research productivity and relevance in the robotics field. SII2025 Best Paper Award (2025) SI2024 優秀講演表彰 (2024) 文部科学大臣表彰（科学技術賞・研究部門）(2017) IEEE Fellow Award (2007) 日本ロボット学会功労賞 (2012) Dr. Sugano currently serves as President of The Robotics Society of Japan (2023-present) and previously as President of The Society of Instrument and Control Engineers (2017-2018). His leadership extends to editorial roles, including Editor-in-Chief of the International Journal of Advanced Robotics (2007-2012). His research group has secured numerous grants supporting their work in robotics and intelligent systems, with applications spanning healthcare, manufacturing, and infrastructure maintenance. He maintains active collaborations with researchers worldwide, as evidenced by his extensive co-authorship network.

• Image coding
• Machine learning
• Data science
• +۳ مورد دیگر

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.

• Childhood and Nursery Education
• Social Welfare
• Nutrition Science
• +۱ مورد دیگر

Miyamoto Yuji is an Associate Professor at the Faculty of Human Sciences, Advanced Research Center for Human Sciences , focusing on interdisciplinary research bridging education, welfare, and health sciences. His projects integrate epidemiological analysis with practical interventions in childcare settings and public spaces. Ph.D. in Human Sciences Research spans childhood education , social welfare , nutritional science , and health informatics , with recent work addressing pandemic impacts on youth, gaming addiction, playground safety, and functional food applications. Publications emphasize evidence-based policy development and environmental design. Project trends show emphasis on pandemic resilience , inclusive urban infrastructure , and digital health integration . Key themes include childhood development, public safety, and cross-sector collaboration. Grants include JSPS Research Projects on pandemic health management and playground equipment systems. Collaborations involve institutions like National Rehabilitation Center for Persons with Disabilities and local welfare committees.

• Environmental dynamic analysis
• Climate modeling
• Ecology
• +۳ مورد دیگر

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.

• River Engineering
• Hydraulics
• River Mechanics
• +۳ مورد دیگر

Masato Sekine is a Professor at Waseda University's Faculty of Science and Engineering, School of Creative Science and Engineering, specializing in hydraulic engineering with a focus on urban flooding, river mechanics, and sediment transport. He holds a Doctor of Engineering degree from Waseda University and maintains an active research profile with numerous publications and ongoing projects. His research interests encompass River Engineering, Hydraulics, River Mechanics, and Hydroengineering, with particular emphasis on urban flood risk assessment, sediment transport in mixed-grain rivers, and levee stability. Sekine's work bridges theoretical hydraulic principles with practical urban flood management applications, especially in Tokyo's complex urban environment. Sekine's recent research output demonstrates a strong focus on urban flooding phenomena, with numerous papers analyzing flood processes in Tokyo's 23 wards, Kawasaki, and Yokohama during extreme rainfall events. His work examines the interactions between river systems, sewer networks, and urban infrastructure during flood events, providing critical insights for flood risk management in densely populated areas. Waseda University Teaching Award President's Award (2018) Japan Society of Civil Engineers Hydraulic Engineering Paper Award (2016) Japan Society of Civil Engineers Hydraulic Engineering Paper Award (2015) Japan Society of Civil Engineers Hydraulic Engineering Paper Award (2004) Professor Sekine leads several significant research projects including 'Reconstruction of sediment transport models on riverbeds consisting of materials ranging from clay to large gravels' (2020-2023) and 'Real-time prediction and management control of urban flood risk' (2017-2020). His work has practical applications for urban flood management systems and infrastructure design in Japan's densely populated coastal regions.

• Lexical-Functional Grammar
• Constraint-based Grammar
• Linguistic Typology
• +۷ مورد دیگر

Ryo Otoguro is a Professor at Waseda University's Faculty of Law, specializing in theoretical linguistics. He holds a PhD from the University of Essex and has been at Waseda since 2009, progressing from Assistant Professor to Professor. His research focuses on Lexical-Functional Grammar, constraint-based approaches, and linguistic typology, with particular emphasis on morphology-syntax interfaces across languages including Japanese, Germanic, and Romance languages. His research examines case systems, agreement phenomena, verb inflection, modality, and negation through formal linguistic frameworks. Otoguro develops models connecting conceptual structures with linguistic representations using mathematical functions, contributing to theories of language evolution from primitive to complex grammatical systems. Otoguro has received the British Government Overseas Research Students Award (2003) and secured multiple JSPS grants including studies on agreement phenomena (2017-2020), verb inflection (2014-2017), and modality (2011-2013). As Director of Waseda's Institute for the Study of Language and Information (2021-2025), he leads research initiatives while teaching linguistics courses across departments.

• Educational Technology
• e-Learning
• Distance Education
• +۵ مورد دیگر

Shoji Nishimura is a Professor at the Faculty of Human Sciences, Waseda University, where he has served since 2006. Prior to his current position, he was an Associate Professor (2004-2006) and Assistant Professor (1997-1999) at the same institution. He holds a Doctor of Philosophy in Human Sciences from Osaka University and a Master of Science from Waseda University. Dr. Nishimura's educational background includes graduate studies in Pure and Applied Physics at Waseda University Graduate School and undergraduate studies in Mathematics at Waseda University Faculty of Science and Engineering. His academic journey reflects a strong foundation in quantitative disciplines that has informed his research in educational technology and data analysis. Dr. Nishimura's primary research interests focus on Educational Technology, Distance Education, and e-Learning . His work spans multiple domains including health informatics, biometrics, and human factors engineering. He has made significant contributions to the development of e-learning systems, particularly for tacit knowledge transfer and advanced skill acquisition. His research increasingly integrates health data analysis, wearable devices, and gait recognition technologies, demonstrating an interdisciplinary approach that bridges educational theory with practical applications in healthcare and safety. His recent publications (2020-2025) reveal a clear trend toward sophisticated health data analytics and biometric applications. The research shows increasing sophistication in causal analysis of health data, development of trustworthy decentralized health data systems, and applications of motion analysis for safety assessment. His work on gait recognition and driver behavior analysis demonstrates practical applications of his theoretical frameworks in real-world safety contexts. The shift from purely educational technology to health-focused applications represents a significant evolution in his research trajectory. Dr. Nishimura is actively involved in several major research projects including the development of e-learning systems for tacit knowledge transfer, research on broadcasting-telecommunications cooperation, and empirical studies on active learning behavior. His work has been supported by prestigious funding sources including Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research. He maintains active membership in numerous professional societies including The Institute of Electronics, Information and Communication Engineers, Information Processing Society of Japan, The Botanical Society of Japan, The Society of Population Ecology, Ecological Society of Japan, Japanese Society for Information and Systems in Education, and Japan Society for Educational Technology, reflecting the interdisciplinary nature of his work.

TSUMURA Tomoakiمشاهده پروفایل

استاد

• Parallel Processing
• High Performance Computing
• Computer Architecture
• +۷ مورد دیگر

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.

Motoko Kotaniمشاهده پروفایل

استاد

• Geometry
• Topological Data Analysis
• Graphene Modeling
• +۳ مورد دیگر

Motoko Kotani is a Professor at the Department of Mathematics , Graduate School of Science , Tohoku University , and serves as Principal Investigator at the Advanced Institute for Materials Research (AIMR). She leads the Mathematical Application Research Team at RIKEN Center for iTHEMS and has held positions such as Director of WPI-AIMR (2012–2020) and Executive Vice President for Research at Tohoku University since 2021. Her research focuses on geometric and topological analysis of materials, particularly graphene and amorphous structures, bridging mathematics with materials science. Recent work includes topological classification of weaves, heat conduction in germanium, and mathematical modeling for battery technologies. The 15 most recent publications highlight her work in applied mathematics and materials science , with sub-fields spanning topological data analysis, graphene geometry, jammed matter, and SDG-related science policy. She has contributed to the UN 10-Member Group (2024–2025), advising on science and technology for sustainable development. Asia’s 50 top women scientists (AASSA, 2019) Appointed to UN 10-Member Group (2024) As a science advisor to Japan’s Minister for Foreign Affairs (2022) and President-Elect of the International Science Council (2021), she emphasizes international collaboration. Her lab ( M. Kotani Laboratory ) hosts regular seminars on mathematical applications in materials science.

Hirokazu Takahashiمشاهده پروفایل

استاد

• Neuroscience
• Neural engineering
• Electrophysiology
• +۱۳ مورد دیگر

Hirokazu Takahashi is a Professor and Principal Investigator at the Department of Mechano-Informatics, Graduate School of Information Science and Technology, University of Tokyo. He leads the Bio-Intelligence Systems Lab, where his team approaches neuroscience from a mechanical engineering perspective. His research spans multiple scales of neural networks, from dissociated neuronal cultures to rodent and human brains. Born in Sendai, Japan (1975) B.S., M.S., Ph.D. in Mechanical Engineering from University of Tokyo (1998, 2000, 2003) Assistant Professor at Department of Mechano-Informatics (2004) Associate Professor (2019) Professor (2023) His research focuses on reverse engineering the brain to understand neural computation in the cerebral cortex. His lab develops novel experimental methods including high-density microelectrode arrays to obtain large-scale neural data, which is then analyzed using machine learning and AI techniques. Key research areas include emergent computing with dissociated neuronal cultures, auditory system processing in rodents, and epilepsy research in both animal models and humans. The lab investigates how intelligence, consciousness, and fine arts emerge from neural networks at various scales. His recent publications demonstrate significant advancements in understanding spontaneous beat synchronization in rats, physical reservoir computing with living neuronal cultures, and vagus nerve stimulation effects on cortical responses. His work bridges engineering, neuroscience, and informatics to extract design principles of brain function. Engineering Department Head Award (Research) for student Kiki Mamiya Professor Takahashi has supervised numerous students through graduation theses, master's theses, and doctoral research. His lab maintains extensive collaborations with institutions including ETH Zurich, Maxwell Biosystems, Monash University, and NTT. His research is funded through various grants supporting interdisciplinary work at the intersection of mechanical engineering and neuroscience. The Bio-Intelligence Systems Lab operates at the cutting edge of neural engineering, developing technologies such as high-density CMOS arrays with 10,000 recording sites and creating bio-silicon hybrid sensors. The team investigates neural representation with functional maps, learning-induced plasticity, auditory streaming, and mismatch negativity. Current projects include studying the effects of music on brain activity, developing seizure detection algorithms, and exploring the mechanisms of vagus nerve stimulation.

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.

Henrik Jeldtoft Jensenمشاهده پروفایل

استاد

• Statistical Physics
• Complex Systems
• Information Theory
• +۶ مورد دیگر

Henrik Jeldtoft Jensen is a Professor of Mathematical Physics at Imperial College London and a Specially-Appointed Professor at Tokyo Institute of Technology's Institute of Innovative Research. He leads the Centre for Complexity Science at Imperial College and is an External Faculty Member at the Complexity Science Hub Vienna. His research focuses on statistical physics, complex systems, and their applications in biology, economics, neuroscience, and social dynamics. He has pioneered frameworks such as the Tangled Nature model of co-evolutionary dynamics and contributed to studies on self-organized criticality and record dynamics in complex systems. His academic roles include Director of Postgraduate Studies at Imperial College and Program Leader for Complexity Science. He collaborates internationally, exploring topics like socio-economic sustainability, brain dynamics via EEG/fMRI analysis, and the intersection of music improvisation with neural synchronization. He holds affiliations with institutions such as the Guildhall School of Music and Drama for interdisciplinary projects on human creativity and sensory dynamics. His research spans theoretical physics, applied mathematics, and interdisciplinary biology, with recent work addressing ecological metapopulations, genetic dynamics, and critical phenomena in complex networks. He is actively engaged in projects analyzing financial networks, climate adaptation, and evolutionary rescue mechanisms in species facing environmental challenges.

Makoto Iwasakiمشاهده پروفایل

استاد

• Mechatronics
• Control Engineering
• Industrial Electronics
• +۵ مورد دیگر

Makoto Iwasaki is a Professor at the Nagoya Institute of Technology , Department of Electrical and Mechanical Engineering. He holds prestigious fellowships including IEEE Fellow (2015) and IEEJ Fellow (2021), and serves as Vice President (International and Global Activities) since 2024. Ph.D. in Electrical and Computer Engineering (Nagoya Institute of Technology, 1991) Professional memberships: IEEE Fellow, IEEJ Fellow, Science Council of Japan Member His research interests focus on intelligent motion control systems, with key contributions to: High-speed, high-precision positioning methodologies Nonlinear friction compensation Equivalent-input-disturbance approaches Robust control for mechatronic devices Soft computing applications in motion control Modeling and control of harmonic drive systems Recent publications emphasize advanced control strategies for industrial robots, autonomous vehicles, and collaborative systems, particularly addressing environmental adaptability, disturbance rejection, and nonlinear dynamics. His work integrates mechatronics with AI techniques for precision applications. Scientific awards include: 2025 IEEE Japan Best Paper Award 2024 IEEJ Technical Achievement Award 2022 AAIA Fellowship 2022 IEEE/IES Senior AdCom Honor He has secured significant grants from the Japan Society for the Promotion of Science (JSPS) for projects on: High-speed industrial robot control (Grant-in-Aid for Scientific Research A) Collaborative robot safety/precision (Grant-in-Aid for Scientific Research B) Harmonic drive positioning systems (JSPS C Grant) As an educator, he teaches Advanced Motion Control and Electrical Circuit Fundamentals , and leads the NIT Iwasaki Laboratory in mechatronics research.

• Human Genetics
• Population Genomics
• Anthropology
• +۷ مورد دیگر

OHASHI Jun is a Professor at the Graduate School of Science, University of Tokyo, specializing in Human Genetics. His research centers on natural selection and human genome diversity, integrating anthropological perspectives with genomic analysis to explore human evolutionary history and adaptation. His primary research spans population genomics and ancient DNA studies, with focus on the Jomon people of Japan, dispersal of modern humans in the Japanese archipelago during the last glacial period, and reconstruction of genetic relationships among prehistoric human remains. He investigates physiological and metabolic adaptations through Jomon-derived iPSC models. Additional research extends to infectious disease genetics, particularly hepatitis B virus-related hepatocellular carcinoma mechanisms and malaria drug resistance dynamics in African populations. His work combines genomic, physiological, and anthropological approaches to understand human evolutionary trajectories and disease susceptibility. Professor OHASHI leads multiple Japan Society for the Promotion of Science Grant-in-Aid projects, including Principal Investigator roles for Teotihuacan civilization history reconstruction and remote Oceania migration genetics. As Co-Investigator, he contributes to projects on Jomon iPSC-based physiology profiling, hepatitis B risk prediction, thermogenic capacity diversity, and malaria resistance containment strategies across Africa and Japan.

• Computational Science
• Fundamental Physical Chemistry
• Machine Learning
• +۳ مورد دیگر

Mikito Fujinami is an Assistant Professor at the Research Institute for Science and Engineering, Waseda University. He earned his Ph.D. in Science from Waseda University in March 2020 and has held academic positions there since 2018. His research spans computational chemistry, machine learning, and cheminformatics. Doctoral Degree: Waseda University Graduate School of Advanced Science and Engineering (2020) Professional Memberships: The Molecular Science Society, Theoretical Chemistry Association, Organic Synthesis Chemistry Association, The Chemical Society of Japan His research focuses on integrating machine learning with quantum chemical descriptors for reaction prediction, solvent selection, and experimental automation. He has developed systems for automated chemical experiment recognition using computer vision and machine-learned kinetic energy functionals for orbital-free DFT calculations. Scientific awards include: Doctoral Degree Award (Waseda University, 2020) Poster Award (41st Chemoinformatics Symposium, 2018) Excellent Poster Presentation Award (CSJ Chemical Festa 2016) Best Oral Presentation Award (39th Chemoinformatics Symposium, 2016) He has also contributed to educational materials, including a 12-part series on machine learning applications in chemistry and co-authored books on cheminformatics and materials informatics.