جست‌وجوی استاد و پژوهشگر

• Robotics
• Tactile Sensing
• Soft Robotics
• +۳ مورد دیگر

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.

• Artificial Intelligence
• Machine Learning
• Robotics
• +۲ مورد دیگر

Takamitsu Matsubara is a Researcher affiliated with Nara Institute of Science and Technology (NAIST) and Advanced Telecommunications Research Institute International (ATR), operating externally to the Institute of Science Tokyo as indicated in institutional records. His research spans core domains of Artificial Intelligence with emphasis on Machine Learning algorithms, Robotics systems integration, and Computer Vision applications. This work aligns with NAIST's engineering-focused research ecosystem and ATR's telecommunications innovation mandate, targeting practical implementations in autonomous systems and perceptual computing. No scientific awards, student advisement records, or laboratory teams were documented in the source material. Professional activities appear centered on collaborative research between NAIST's academic framework and ATR's industry-oriented projects without indication of part-time status or secondary appointments.

Akihiko Toriiمشاهده پروفایل

استادیار

• Computer Vision
• 3D Reconstruction
• Place Recognition
• +۶ مورد دیگر

Akihiko Torii is an Assistant Professor (Research Associate) at the Okutomi & Tanaka Lab in Tokyo Institute of Technology. He holds a PhD from Chiba University and completed a postdoctoral fellowship at the Center for Machine Perception (CMP) at Czech Technical University in Prague. His research focuses on computer vision, with expertise in 3D reconstruction, place recognition, localization, and structure from motion. He has contributed to influential datasets like the 24/7 Tokyo, Pittsburgh (Pitts250k), SF Revisited, and InLoc datasets, advancing visual localization and feature matching techniques. **Education and Background:** PhD in Computer Science, Chiba University Postdoctoral Researcher, Czech Technical University (2014–2018) **Research Interests:** His work spans Computer Vision , including 3D Reconstruction , Place Recognition , Feature Matching , and Multi-View Stereo . He emphasizes practical applications such as indoor/outdoor localization under changing conditions. **Awards and Recognition:** 2017: CVPR Outstanding Reviewers Award 2016: IEEE Japan Chapter Young Author Award 2015: Tokyo Tech Young Investigator Award Multiple Best Paper Awards (2013–2014) **Key Projects:** Developed algorithms like Multi-View Inverse Rendering and NetVLAD , and contributed to benchmarking frameworks for visual localization accuracy. His work bridges theoretical advancements and real-world applications in robotics and autonomous systems.

• Network Analysis
• Complex Systems
• Social Systems Engineering
• +۵ مورد دیگر

Tengfei SHAO is an Assistant Professor (non-tenure-track) at Waseda University's Global Education Center and Researcher at the Institute of Data Science. His academic journey includes a Doctorate in Engineering from Waseda University's School of Creative Science and Engineering, completed in March 2025. 2022.04 - 2025.03: Doctorate at Waseda University, School of Creative Science and Engineering, Management Systems Program 2020.04 - 2022.03: Master's studies at Waseda University Dr. SHAO's research centers on network science applications across diverse domains. His primary interests include Complex Systems, Network Analysis, and Social Systems Engineering, with particular focus on second-hand luxury market dynamics, AI ethics education, and sentiment analysis. His work frequently employs network motifs as analytical tools to uncover hidden patterns in consumer behavior, market trends, and social interactions. He has developed innovative approaches to analyzing e-commerce versus brick-and-mortar retail environments, particularly in the luxury goods sector. His publication record reveals a consistent trajectory of interdisciplinary research spanning computer science, economics, and social sciences. His most recent work integrates multimodal learning with sentiment analysis, medical image segmentation techniques, and advanced network analysis methodologies. The trend shows increasing sophistication in applying network science to real-world business problems, particularly in the luxury market sector. Association for Computing Machinery (ACM) member since 2024 Institute of Electrical and Electronics Engineers (IEEE) member since 2024 計測自動制御学会 (SICE) member since 2022, serving on Social Systems Committee since 2024 人工知能学会 (JSAI) member since 2022 電子情報通信学会 (IEICE) member since 2022 情報処理学会 (IPSJ) member since 2020 At Waseda University's Global Education Center, Dr. SHAO teaches multiple programming courses including Basic AI Programming, Introduction to Python Programming, Database Management, and Fundamentals of Information Science across different quarters. His teaching portfolio demonstrates expertise in foundational computer science education for international students. His research methodology consistently applies network science principles to diverse domains, creating bridges between technical analysis and practical business applications, particularly in understanding consumer behavior in digital marketplaces.

• Circadian rhythm
• Chronobiology
• Plant molecular biology
• +۴ مورد دیگر

Hideo Iwasaki is a Professor at Waseda University in the Department of Electrical Engineering and Bioscience within the Faculty of Science and Engineering, School of Advanced Science and Engineering. He holds a Ph.D. from Nagoya University and has established himself as a leading researcher at the intersection of biology, engineering, and art. His career spans multiple prestigious institutions including RIKEN, University of Tokyo, and Nagoya University. Dr. Iwasaki's research focuses on the fascinating intersection of chronobiology, cyanobacteria, and bioaesthetics. His work explores circadian rhythms in cyanobacteria, particularly examining the molecular mechanisms of the Kai protein-based circadian clock system. He investigates how these biological clocks control various cellular processes including UV resistance, glycogen metabolism, and colony pattern formation. His research extends beyond traditional biology into bioart and bioaesthetics , where he creates interfaces between living organisms and humans, exploring the artistic potential of biological systems. His analysis of floral morphology in water lilies demonstrates his ability to bridge mathematical modeling with biological observation. Dr. Iwasaki's scientific contributions have been recognized with numerous prestigious awards: Excellent Prize of Japan Media Arts Festival (2019) Good Design Award (2017) for Biolab, BioClub Shibuya Research Encouragement Award of the Japanese Society for Genome Microbiology (2011) Minister of Education, Culture, Sports, Science and Technology Young Scientists Award (2008) Toyota Triennale, Contemporary Art Award (2004) Research Award from Japanese Society for Chronobiology (2003) Inoue Research Award for Young Scientists (2001) As founder and director of metaPhorest (a bioaesthetics platform), Dr. Iwasaki leads innovative projects that bridge science and art. His research demonstrates remarkable consistency in exploring the boundaries between biological rhythms, mathematical modeling of biological patterns, and creative applications. His work on cyanobacterial colony patterns, circadian control of UV resistance, and mathematical modeling of water lily morphology reveals a unifying theme of pattern formation across biological scales.

• Machine Learning
• Statistical Learning Theory
• Statistical Science
• +۳ مورد دیگر

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

• Informatics
• Perceptual Information Processing
• Computer Vision
• +۳ مورد دیگر

SAKAUE Fumihiko is an Associate Professor at the Faculty of Engineering, Department of Information Engineering at Okayama University. He holds a Doctor of Engineering degree from Okayama University, awarded in 2006. His research focuses on innovative computer vision and computational photography techniques, aiming to develop novel methods for 3D measurement and real-time motion analysis without relying on conventional cameras or computers. His work integrates light-ray processing and spatiotemporal modulation to enhance visual information extraction and has contributed significantly to fields such as pattern recognition and imaging systems. Education background includes graduation from Okayama University's Faculty of Engineering in 2001, followed by earning his Doctor of Engineering degree from the same institution in 2006. His research interests span several key areas in informatics and engineering, including: Perceptual information processing for dynamic visual analysis Computer vision applications in 3D reconstruction and motion capture Computational photography techniques for advanced imaging systems Pattern recognition methodologies in unstructured environments Development of light-based measurement systems without conventional sensors Integration of light projection and observation for real-time data interpretation SAKAUE has received numerous awards, including: MIRUインタラクティブ発表賞 (2024) Best student paper award at International Workshop on Frontiers of Computer Vision (2022) Best paper award at INTERNATIONAL WORKSHOP ON ADVANCED IMAGE TECHNOLOGY (2022) MIRU2018長尾賞 (2018) 山下記念研究賞 (2018) CGVI研究会優秀研究発表賞 (2017) ICPR Best Student Paper Award (2016) MIRUインタラクティブ発表賞 (2019) MRU2016インタラクティブ発表賞 (2016) In terms of advising, SAKAUE has guided notable students including Toshiki Kamiya (recipient of 2022 Best Student Paper Award) and Yuma Nishikawa (2024 Best Student Paper award recipient). He has secured multiple grants from the Japan Society for the Promotion of Science (JSPS), including a 2020-2023 grant focused on 3D motion visualization through spatiotemporal light-ray integration, and a 2016-2019 grant on 5D light field display technologies. Additional funding includes a 2022-2025 project with Aichi Prefecture for AI-driven textile inspection systems. SAKAUE collaborates with interdisciplinary research teams at Okayama University, focusing on developing innovative imaging systems and sensorless vision technologies. His work often involves partnerships with industry through patents and applied research projects, such as the 'Position Measurement Device' (2016) and 'Three-Dimensional Information Presentation Device' (2014), demonstrating practical applications of his theoretical research.

• Information Technology
• Communication Engineering
• Image Processing
• +۳ مورد دیگر

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

• Fluid Engineering
• Thermal Engineering
• Aerospace Engineering
• +۳ مورد دیگر

Professor Matsuda Yu at Waseda University 's Faculty of Science and Engineering (School of Creative Science and Engineering) is a leading researcher in fluid engineering and aerospace systems. With a Doctor of Engineering from Nagoya University, he has developed innovative measurement techniques for micro/nano-scale phenomena. Current position: Professor, Waseda University (2022-present) Previous roles: Japan Science and Technology Agency (2018-2022), Nagoya University (2008-2018) Research Focus spans thermal engineering , microfluidics , and quantum-inspired data analysis . His recent work involves pressure-sensitive paint optimization, single-particle tracking , and quantum annealing applications for fluid dynamics. Scientific Recognition includes multiple JSME awards, MEXT Commendation for Young Scientists, and the 2025 Ichiro Tanaka Award . His 45+ scientific awards highlight contributions to measurement science and fluid dynamics. Technical Innovations include ambient-light-resistant PSP methods, quantum-optimized sensor placement, and bioluminescent temperature-pressure sensors. His 95+ publications with 1497 Google Scholar citations demonstrate significant impact in microscale flow analysis and nanoparticle dynamics .

• Human Engineering
• Industrial Engineering
• Management Engineering
• +۲ مورد دیگر

Takuya Hida is an Assistant Professor at Waseda University's Faculty of Human Sciences since 2025. Previously, he served as a Lecturer (tenure-track) at Tokyo Metropolitan University's College of Science and Engineering, Department of Industrial and Systems Engineering (2014-2023). Education: PhD in Engineering (Tokyo Metropolitan University, 2013) Research Focus: Human engineering, industrial ergonomics, and work posture analysis His research investigates ergonomic challenges in visual/tactile inspections, focusing on factors like defect shape, lighting conditions, and posture-induced physical burden. Recent work includes developing AI-based posture evaluation systems and RFID positioning models. Key Trends: Visual inspection optimization using peripheral vision Upper limb load analysis in repetitive tasks Defect detection in contaminated surfaces Integration of motion capture and machine learning Scientific Awards: 2021 Japan Society for Management Engineering Academic Award 2022 Japanese Society of Human Engineering Research Encouragement Award 2012 Japan Society for Management Engineering Paper Encouragement Award Professional Engagement: Active in committees for Japan Society for Management Engineering and Japan Institute of Plant Maintenance. Leads research projects on ergonomic evaluation tools funded by JSPS and private enterprises.

• Software Engineering
• Human-Computer Interaction
• Artificial Intelligence
• +۳ مورد دیگر

Jialong Li is an Assistant Professor (non-tenure-track) at the Waseda Institute for Advanced Study. His research focuses on dynamic responsibility allocation in human-software collaboration, with applications in autonomous driving, robotics, and adaptive systems. He employs techniques such as discrete controller synthesis and large language models to address runtime environmental changes. Key research themes: human-robot collaboration, self-adaptive software, autonomous systems Technical approaches: Discrete Controller Synthesis, LLM integration, reinforcement learning Recent publications emphasize multimodal human-AI collaboration, prompt engineering for software development, and ethical considerations in adaptive systems. His work bridges theoretical modeling (e.g., requirements analysis, stochastic control) with real-world applications like warehouse robotics and color-blind accessibility tools. While no formal awards are listed, his research has been presented at top conferences in software engineering and autonomous systems.

• High Performance Computing
• Entertainment and Game Informatics
• Human Interface and Interaction
• +۳ مورد دیگر

Dr. Tsukasa Fukusato is an Assistant Professor at the School of Fundamental Science and Engineering , Waseda University since April 2023. His work spans Human Interface and Interaction , Entertainment Informatics , and High-Performance Computing , with a focus on interactive systems for digital art and animation. Current Research: Developing interactive tools for 2D/3D animation, workflow systems in bioinformatics, and AI-assisted artistic creation Technical Expertise: Latent diffusion models, motion segmentation, sketch-based interfaces, garment transfer, and aerodynamic design His recent publications (2022-2024) demonstrate advancements in: Animation and motion design (15+ papers) Workflow execution services AI-guided facial synthesis Interactive garment/textile modeling Biomechanical simulation systems Visual language interfaces Scientific Awards: 2024 Best Poster Award (NICOGRAPH) 2023 Honorable Mention (Computational Visual Media) Multiple Best Paper/Poster awards (2014-2023) 2014 Nishida Award from the Institute of Image Information and Television Engineers of Japan Teaching Activities (2025): Lecturer for Computer Graphics, Media Science, and Project-Based Learning Supervising graduation theses and advanced digital media projects

• Applied mathematics
• Statistics
• Information theory
• +۸ مورد دیگر

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.

• Intelligent informatics
• Safety engineering
• Social systems engineering
• +۸ مورد دیگر

Reiko HishiYama is a Professor at WASEDA University's Faculty of Science and Engineering, School of Creative Science and Engineering. With a Doctor of Informatics from Kyoto University (2005), she has established herself as a leading researcher in intelligent informatics, safety engineering, social systems engineering, and educational technology. Her educational background includes: Doctor of Informatics from Kyoto University (2005) HishiYama's research spans multiple interdisciplinary fields with a strong focus on the intersection of technology and society. Her primary research interests include artificial intelligence, social informatics, business informatics, communication design, computer vision, mobile computing, and IoT (Internet of Things). She particularly focuses on how these technologies can be applied to community management, tourism development, and cultural preservation through innovative approaches such as augmented reality and network analysis. Analysis of her recent publications reveals a consistent focus on applying network motif analysis to diverse domains including tourism, luxury goods markets, and community management. Her work increasingly integrates augmented reality technologies with traditional cultural experiences and demonstrates a strong commitment to practical applications that address real-world community challenges, particularly in low-digitalized environments. Her scientific achievements have been recognized with numerous prestigious awards: The 12th FOST Award (2019) The 6th WASEDA e-Teaching Award (2018) The 7th Career Development Essay Contest for Young Professionals and Women Engineers (2015) The 4th FOST Award (2011) Pacific Rim International Workshop on Multi‐Agents PRIMA Runner Up Paper Prize (2004) The 1st KK-MAS Competition Grand Prize (2001) As an educator and researcher, Professor HishiYama has been instrumental in developing innovative teaching methods, particularly in AI ethics education using the case method. Her professional engagements extend beyond academia through various committee memberships including SoftBank Corp. External Director, HAYAO NAKAYAMA Foundation for Science & Technology and Culture Planning Committee, and ASAHI INTELLIGENCE SERVICE CO., LTD. External Director. She maintains active roles in numerous professional societies including IEICE, IEEE, and ACM. Her research laboratory (HishiYama Lab) focuses on developing social support systems through the designable evaluation network framework, with applications in community management, tourism development, and multilingual communication. The lab has produced numerous publications and practical applications that bridge theoretical research with real-world implementation.

• 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.