جستجوی استاد راهنمای دانشگاهی

Atsuo Takanishi is a distinguished Professor at Waseda University's Faculty of Science and Engineering, School of Creative Science and Engineering, with appointments in both the Department of Bioscience and Biotechnology and the Department of Modern Mechanical Engineering. With over 700 publications, 10,399 citations, and an h-index of 47, Professor Takanishi has established himself as a leading figure in robotics research. His work spans multiple institutions, including visiting positions at Showa University School of Dentistry and KDDI Research, Inc. Professor Takanishi received his Doctor of Engineering degree from Waseda University in 1985, following his undergraduate studies in the Faculty of Science and Engineering at the same institution, which he completed in 1980. His academic journey began with positions as an Assistant at Waseda University (1985-1988), Lecturer (1988-1990), and Associate Professor (1990-1997) before achieving his current Professor status. Professor Takanishi's research interests center around robotics and intelligent systems, with particular expertise in humanoid robotics, surgical dentistry applications, and biomechatronics. His work demonstrates a unique integration of mechanical engineering principles with biological systems, resulting in innovative robotic platforms that mimic human capabilities. Notably, his laboratory has developed the Waseda Anthropomorphic Saxophonist Robot series and various medical training simulators that have significantly advanced the field of human-robot interaction. His research in experimental psychology complements his robotics work, particularly in human-robot interaction studies. Analysis of Professor Takanishi's recent publications reveals a strong focus on practical applications of robotics technology, particularly in assistive devices for elderly mobility, medical training simulators, and agricultural robotics for Synecoculture environments. His work consistently bridges theoretical robotics with real-world implementation, with recent papers emphasizing reinforcement learning approaches, haptic feedback systems, and computer vision techniques for complex environments. The Waseda Anthropomorphic Saxophonist Robot series represents a culmination of decades of research in humanoid robotics and musical expression. IEEE Fellow (2020-present) Robotics Society of Japan Fellow (2012-present) Japan Society of Mechanical Engineers Fellow (2007-present) Multiple Best Paper Awards from IEEE conferences (ICRA, IROS, ROMANSY) BusinessWeek Asia's Stars Bloomberg (2001) IFToMM Award of Merit (2010) Professor Takanishi has maintained extensive collaborations with research institutions worldwide, particularly with Italian institutions through the Italy-Japan Workshop series. His laboratory has secured substantial funding from Japanese government agencies including the Japan Science and Technology Agency, with particular emphasis on projects bridging robotics with medical applications and human-centered technologies. His international recognition is evidenced by his numerous visiting professorships and collaborative projects across continents. Professor Takanishi leads the Takanishi Laboratory at Waseda University, which maintains specialized facilities for humanoid robotics development, medical robotics research, and human-robot interaction studies. The laboratory has developed several notable robotic platforms including the WABIAN series of bipedal humanoid robots, the WASEDA FLUTIST ROBOT, and various medical training simulators used in clinical education settings. His work on the WASEDA SAXOPHONIST ROBOT represents a unique fusion of musical artistry and robotics engineering.

• Robotics
• Mechatronics
• Humanoid Robots
• +۴ مورد دیگر

Tetsuya Ogata is a Professor at the Faculty of Science and Engineering, School of Fundamental Science and Engineering at Waseda University. He also holds joint appointments as a Fellow at the Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology (AIST), and as a visiting professor at the National Institute of Informatics (NII). Professor Ogata serves as director of the Institute of AI and Robotics at Waseda University, chairperson of the AI Robot Association (AIRoA), and research supervisor of JST CREST "Fundamentals and Core Technologies for Embodied AI" since 2025. Professor Ogata received his B.S., M.S., and D.E. degrees in mechanical engineering from Waseda University in 1993, 1995, and 2000, respectively. He began his academic career as a Research Associate at Waseda University (1999-2001), followed by positions as a Research Scientist at RIKEN Brain Science Institute (2001-2003), Lecturer (2003-2005) and Associate Professor (2005-2012) at Kyoto University's Graduate School of Informatics, before becoming a Professor at Waseda University in 2012. He was also a JST PRESTO Researcher from 2009 to 2015. Professor Ogata's research focuses on cognitive developmental robotics, deep predictive learning, and the integration of vision, language, and action (VLA) for human-robot interaction. His work explores how robots can learn through experience and interaction with humans and environments, developing models that allow for flexible behavior generation and adaptation. His research has significant implications for creating robots that can understand human intentions, collaborate effectively in real-world settings, and continuously learn from their experiences. The integration of multimodal information processing with predictive models forms the core of his approach to embodied artificial intelligence. Analysis of Professor Ogata's recent publications reveals a strong focus on deep predictive learning frameworks that enable robots to anticipate future states and generate appropriate actions. His research spans multiple domains including soft object manipulation, bimanual coordination, transparent object grasping, and integration of large language models with robotic systems. A notable trend is the increasing emphasis on multimodal integration, combining visual, tactile, and linguistic information to create more robust and adaptable robotic systems. His recent work also shows growing interest in the application of foundation models to robotics, aiming to create more general-purpose robotic capabilities. Best Paper Award, Advanced Robotics, The Robotics Society of Japan (2024) Best paper award Nomination Finalist, IEEE/SICE International Symposium on System Integration (2024) Frontiers of Science Awards, The International Congress for Basic Science (2023) Minister of Education, Culture, Sports, Science and Technology Award (2023) Fellow, Japan Society of Mechanical Engineering (2023) Fellow, The Society of Instrument and Control Engineers (2022) Fellow, The Robotics Society of Japan (2022) IBM Academic Awards (2017) Professor Ogata has been instrumental in establishing collaborative research frameworks between academia and industry, serving in leadership roles for multiple professional organizations including the Robotics Society of Japan, Japanese Society for Artificial Intelligence, and Japan Deep Learning Association. His research has been supported by significant grants including JST CREST funding for "Fundamentals and Core Technologies for Embodied AI." He has mentored numerous researchers who have gone on to contribute to the field of robotics and AI, with many of his former students now holding positions in leading academic and industrial research institutions. Professor Ogata directs the Ogata Laboratory at Waseda University, which focuses on cognitive developmental robotics and deep predictive learning. The lab maintains strong collaborations with industry partners including major robotics companies and technology firms. In 2025, he played a key role in establishing the AI Robot Association (AIRoA), which brings together companies like Toyota, Nissan, and KDDI to advance the development of practical AI robotics technologies. His research group is known for its interdisciplinary approach, combining insights from neuroscience, cognitive science, and engineering to create more human-like robotic capabilities.

• Cognitive Robotics
• Developmental Robotics
• Human-Robot Interaction
• +۵ مورد دیگر

HARADA Tatsuya is a Professor at the Research Center for Advanced Science and Technology (RCAS), University of Tokyo. His research focuses on intelligent robotics , real-world image processing , and human-informatics AI systems . Degree: PhD Research Themes: Harada investigates real-world intelligent information processing, fast image recognition and retrieval, and AI applications in pathology diagnostics. His work spans explainable AI systems for cancer analysis, tactile sensor integration for humanoid robots, and knowledge acquisition via dialog systems. Research Categories: His projects have been funded through multiple Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) grants, including Grant-in-Aid for Scientific Research (A/B/C) and Innovative Areas programs. Specific projects include "Explainable AI diagnostic system for breast cancer" (2020-2021) and "Behavior Capture Suit with Motion Sensors" (2010-2013). Scientific Awards & Grants: Recipient of competitive JSPS grants for interdisciplinary research bridging robotics, computer vision, and medical diagnostics.

• Intelligent Robots
• Intelligent Information Processing
• Real-World Image Annotation and Retrieval
• +۴ مورد دیگر

Jiro Katto is a Professor at Waseda University's School of Fundamental Science and Engineering, where he has been conducting research and teaching since 1999. He received his Ph.D. from the University of Tokyo and has established himself as a leading researcher in multimedia signal processing and computer networks. His academic journey includes positions as Associate Professor (1999-2004), Professor (2004-present), and Director at NEDO (2004-2008), along with research experience at NEC C&C Laboratories (1992-1999) and a Visiting Scholar position at Princeton University (1996-1997). Professor Katto's research interests focus on Multimedia Signal Processing and Computer Networks, with particular expertise in video compression, 5G network performance, and learned image compression techniques. His work bridges theoretical advancements with practical implementations, as evidenced by his extensive publications in top-tier conferences and journals. His research group has made significant contributions to point cloud compression, latency compensation in remote systems, and hardware-accelerated video encoding for UHD streaming. His publication record is impressive, with 276 papers cited 3,323 times in Scopus and 6,169 times in Google Scholar, reflecting his substantial impact in the field. His recent work shows a strong trend toward applying deep learning techniques to traditional signal processing problems, particularly in the areas of image and video compression, where his team has developed novel approaches to improve compression efficiency while reducing computational complexity. Electric Telecommunications Promotion Foundation Telecommunications System Technology Award (2023) Takayanagi Kenjiro Foundation Takayanagi Kenjiro Achievement Award (2020) Institute of Image Information and Television Engineers Fellow (2020) Institute of Electronics, Information and Communication Engineers Fellow (2015) IEICE Communications Society Activity Contribution Award (2006) IEICE Academic Encouragement Award (1995) SPIE VCIP 1991, Best Student Paper Award (1991) Professor Katto has served on numerous prestigious committees including IEEE ComSoC Tech News Editorial Board, IEEE Technical Program Committees for major conferences (Globecom, ICC, ICIP), and editorial boards for several academic journals. His leadership in the academic community extends to chairing conferences like IWAIT 2011 and serving as Editor-in-Chief for journals in his field. His research has practical applications in commercial 5G networks, video streaming services, and remote monitoring systems, demonstrating the real-world impact of his work.

• Multimedia Signal Processing
• Computer Networks
• Communication Engineering
• +۳ مورد دیگر

Akio Kodaira is affiliated with the Institute of Science Tokyo as a researcher. His work focuses on soft robotics, mechatronics, and advanced actuator design using materials like IPMC (Ionic Polymer-Metal Composites) and flexible fuel cells. Primary institution: Institute of Science Tokyo Research Interests Kodaira's research spans the development of soft robots, thin-film actuators, and bio-inspired mechanical systems. Key areas include IPMC fabrication techniques, energy-efficient actuators using Au/Pt electrodes, and 3D crafts using paper/fabric materials. Publication Trends Recent publications emphasize soft robotics, material hybridization (e.g., paper/fabric-assisted IPMC), and flexible fuel cell applications. His collaborations with researchers like Koichi Suzumori and Hiroyuki Nabae highlight interdisciplinary efforts in mechatronics and mechanical engineering. Collaborations Frequent co-authors include Koichi Suzumori (Professor, Institute of Science Tokyo), Kinji Asaka , and Hiroyuki Nabae . Projects involve thin-film robotics, McKibben muscles, and simulator-based navigation software.

• Soft Robotics
• Mechatronics
• Smart Materials
• +۳ مورد دیگر

Toshiharu Sugawara is a Professor in the Department of Computer Science and Engineering at Waseda University's Faculty of Science and Engineering, School of Fundamental Science and Engineering, a position he has held since April 2007. With a Ph.D. in Engineering from Waseda University, his research spans multiple domains in artificial intelligence and multi-agent systems, maintaining active collaborations across international institutions and contributing significantly to the field through numerous publications and awards. Dr. Sugawara received his BS and MS degrees in Mathematics from Waseda University in 1980 and 1982, respectively, followed by his Ph.D. in 1992. Before joining Waseda University as faculty, he worked as a Research Scientist at NTT Laboratories from 1982 to 2007, with a visiting researcher position at the University of Massachusetts at Amherst in 1992-1993. He also held part-time lecturer positions at University of Electro-Communications (2003-2007), Waseda University (2004-2006), and Tokyo University of Agriculture and Technology (1990-1991). His research interests focus on artificial intelligence with particular expertise in multi-agent systems, machine learning, cooperation and coordination mechanisms, soft computing, computational social science, and social informatics. His work bridges theoretical foundations with practical applications in network management and information systems. Recent publications demonstrate a strong trajectory toward interpretable multi-agent reinforcement learning, efficient path planning algorithms, and modeling social behaviors in complex networks. His research group has made significant contributions to multi-agent path finding, cooperative task execution, and understanding virtual economies in social media platforms. Dr. Sugawara has received numerous prestigious awards including multiple Best Paper Awards at JAWS conferences (2014, 2015, 2018), ACM SAC 2015, and various research paper awards from Japanese academic societies. His work on multi-agent systems has been consistently recognized for its theoretical rigor and practical impact. As an advisor, Dr. Sugawara has mentored numerous students who have become prominent researchers in their own right, with many co-authoring papers that have received awards. His laboratory maintains strong collaborations with industry partners, particularly in the areas of network management and intelligent systems. Current research directions include developing interpretable multi-agent reinforcement learning frameworks, optimizing multi-agent coordination in constrained environments, and analyzing social dynamics in virtual economies.

• Artificial Intelligence
• Multi-agent systems
• Machine learning
• +۵ مورد دیگر

Professor Masatoshi Okutomi is affiliated with the Department of Systems and Control Engineering at the School of Engineering, Institute of Science Tokyo. His research focuses on advanced medical imaging techniques, particularly in endoscopy and 3D reconstruction, leveraging deep learning and neural networks. Key interests include virtual chromoendoscopy for cancer detection, image restoration, and stereo matching under challenging conditions. His work bridges computer vision and healthcare, addressing real-world applications such as MRI reconstruction and foggy stereo matching. Notable contributions include developing lightweight medical segmentation networks for edge devices and advancing neural radiance fields (NeRF) for novel view synthesis. His research spans diverse domains: from improving video quality assessment to enhancing object detection in high-dynamic-range images. Collaborative projects emphasize practical solutions for medical diagnostics and robust image processing in adverse environments. Recent articles highlight advancements in temporally-consistent video restoration, few-shot view synthesis, and degraded image classification using knowledge distillation. These innovations underscore his commitment to pushing boundaries in both theoretical computer vision and applied medical technology.

• Medical Imaging
• Computer Vision
• Deep Learning
• +۵ مورد دیگر

Tetsunori Kobayashi is a Professor in the School of Fundamental Science and Engineering at Waseda University, Japan, where he has served since 1997. He is renowned for pioneering research in human–robot interaction, spoken language processing, and multimodal conversational systems, leading to over 230 refereed papers and an h-index of 35 (Google Scholar). Education: 1980 B.Eng. in Electrical Engineering, Waseda University 1982 M.Eng. and 1985 Dr.Eng. from Graduate School of Science and Engineering, Waseda University Research Interests: His work spans intelligent robotics , perceptual information processing , pattern recognition , image and audio processing , and conversational AI . He develops algorithms for real-time dialogue systems, multi-party conversation facilitation robots, and non-autoregressive speech recognition leveraging CTC and pre-trained language models. Recent Publication Trends: Since 2020 his group has advanced non-autoregressive end-to-end ASR (Mask-CTC, Intermpl, BECTRA), noise-robust attention , multi-look-ahead conversational ASR , and neural speaker diarization . They integrate BERT-style pre-training with CTC losses to accelerate inference while maintaining accuracy. Parallel work explores vision-and-language topics such as scene-graph generation, video semantic indexing, and personalized summarization for spoken news delivery. Scientific Awards: IEICE Fellow 2023 – for multi-modal multi-party conversation research IPSJ Fellow 2016 – for pioneering robot conversation studies JST Award for Academic Start-ups 2024 Best Paper Awards from IEICE, IEEE BTAS, ACM SIGGRAPH VRCAI, and several IPSJ workshop prizes Advising & Grants: He has mentored dozens of PhD and Master’s students who now lead in academia and industry. Major funded projects include JST CREST on conversational robotics, NEDO and JST-support for AI-based speech interfaces, and industry collaborations with NHK, OKI, and NEC. Labs & Teams: Kobayashi heads the Perceptual Computing Laboratory at Waseda, conducting interdisciplinary research with domestic and international partners such as MIT, ATR, and NHK Science & Technology Labs.

• Human–robot interaction
• Spoken language processing
• Image and audio processing
• +۳ مورد دیگر

Satoshi Funabashi is an Assistant Professor in the Department of Intermedia Art and Science at Waseda University's School of Fundamental Science and Engineering, Japan. He is affiliated with the Graduate Program for Embodiment Informatics under Waseda University's Program for Leading Graduate Schools and contributes to multiple graduate schools including the Graduate School of Creative Science and Engineering. Education: Doctor of Engineering (Waseda University, 2017-2021) Research Focus: Robotics, tactile sensing, deep learning, and embodiment informatics Academic Appointments: Assistant Professor (non-tenure-track) His research centers on symbiotic robotics and tactile-driven manipulation, with recent publications exploring graph convolutional networks, vision-touch fusion, and morphology-specific deep learning for robotic hands. He has secured multiple competitive research grants including JSPS KAKENHI and JST ACT-I programs. Scientific Awards: Grant-in-Aid for Scientific Research (B) (KAKENHI), JSPS (2024-2027) Grant-in-Aid for Early-Career Scientists, JSPS (2022-2024) JST ACT-I Research Fellow (2020-2022, 2018-2020) JSPS Research Fellowship DC1 (2017-2020) He collaborates with the Intelligent Dynamics and Representation Lab (Prof. Tetsuya Ogata) and the Intelligent Machine Lab (Prof. Shigeki Sugano) at Waseda University. He has interned at MIT's CSAIL (2018-2019) and conducted research at UC Davis (2015). His work has been cited over 500 times with an h-index of 14 according to Google Scholar.

• Robotics
• Artificial Intelligence
• Tactile Sensing
• +۶ مورد دیگر

WANG, Yushi is currently a Junior Researcher (Assistant Professor) at the Future Robotics Organization of Waseda University , with prior roles in the Faculty of Science and Engineering (2018–2021). His research focuses on robotics, tactile sensing, and actuator design. Education: Ph.D. in Science and Engineering from Waseda University (2015–2018). Research interests include Humanoid Robotics , Force/Torque Control , and Soft Robotics , particularly for applications in tactile sensing and safety mechanisms . Recent work explores Permanent Magnet Elastomer (PME)-based sensors and Series Clutch Actuators , enabling safer human-robot interactions and adaptive compliance. His publications span conferences like IROS , AIM , and SII , addressing challenges in 3-axis force measurement , collision safety , and material testing . He has taught courses such as 理工学基礎実験 and メカニカルエンジニアリングラボA (2018–2021). Professional memberships include IEEE , IEEE WIE , and the Japan Robotics Society . His work also involves patents for haptic interfaces and torque limiters , with grants like the 若手研究 (Young Researcher Grant) (2021–2023).

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

Shoji Makino is a Professor at Waseda University's Graduate School of Information, Production and Systems. He has held academic and research positions at institutions such as the University of Tsukuba and NTT Communication Science Laboratories. His work spans acoustic signal processing, blind source separation, and adaptive filtering. Education: Ph.D., Tohoku University (1993.03) Mechanical Engineering, Tohoku University Graduate School of Engineering (1979.04–1981.03) Engineering, Tohoku University Faculty of Engineering (1975.04–1979.03) Research Interests: His research focuses on acoustic signal processing for speech and audio, including blind source separation (BSS) , beamforming , and adaptive filtering . He pioneered methods for solving permutation alignment in frequency-domain BSS and developed geometrically constrained ICA techniques. Scientific Awards: Hoko Award (2018.10, Hattori Hokokai Foundation) Outstanding Contribution Award of the Institute of Electronics, Information, and Communication Engineers (2018.06) IEEE Signal Processing Society Best Paper Award (2014.01) IEEE Fellow (2004.01) IEICE Achievement Award (1997.05) Committee Memberships: He has served as Chair of the IEEE CAS Society's Blind Signal Processing TC, General Chair of IEEE WASPAA2007, and Associate Editor of IEEE Trans. SAP. He is actively involved in EURASIP, APSIPA, and the Acoustical Society of Japan.

• Acoustic Signal Processing
• Blind Source Separation
• Digital Signal Processing
• +۶ مورد دیگر

Yoshitaka Tanimizu is a Professor at the School of Creative Science and Engineering, Faculty of Science and Engineering, Waseda University. His research focuses on intelligent manufacturing systems, scheduling optimization, and human-centered production models. He holds a Doctor of Engineering degree from Osaka University and maintains an active research laboratory.

• Mechatronics
• Robotics
• Safety Engineering
• +۶ مورد دیگر

SATO Jun holds the position of Professor at the Department of Information Engineering (メディア情報分野) within the Faculty of Engineering at Nagoya Institute of Technology. He received his Ph.D. in Information Engineering from the University of Cambridge (1993–1996) and previously served as a Research Assistant at Cambridge (1996–1998). His research focuses on perceptual information processing and intelligent informatics, with specializations in computer vision, 3D reconstruction, and optical engineering applications. He has authored influential books like Computer Vision - Geometry of Vision (1999) and Computer Graphics (2017), and contributed to international publications such as Springer's Computer Vision: A Reference Guide (2020). Key professional roles include serving as President of the IEEE Nagoya Branch since 2023, Associate Editor of the International Journal of Computer Vision (Springer, 2010–present), and committee member for various organizations including Japan's Ministry of Education (2015–present) and the Nagoya City Business Potential Evaluation Committee (2008–2015). He has been recognized with prestigious awards including the BMVC Best Science Paper Prize (1994, 1997) and ITE Niwa-Takayanagi Prize (2015). His research extends to industrial collaborations, evidenced by patents like the "3D Information Presentation Device" (2014–2017) and "Position Detecting Device" (2016–2019). Recent work emphasizes applications in automotive safety, occluded object reconstruction, and novel imaging systems using advanced optical configurations and neural networks.

• Computer Vision
• 3D Reconstruction
• Perceptual Information Processing
• +۷ مورد دیگر

Mikihito Tanaka is a Professor at Waseda University 's School of Political Science and Economics , with a PhD from the University of Tokyo. He serves as Director of the Institute for the Next Generation of Journalism and Media since 2025.04. His research areas span Science Communication , Risk Communication , Social Media Studies , and Science Journalism . He has held visiting roles at institutions like the University of Wisconsin-Madison (2010-2023) and advisory positions for Japan's Ministry of Health, Cabinet Office, and JST. Research Trends from his 25+ publications (2000-2025) reveal: Climate change communication strategies across 68 countries Analysis of artificial earthquake misinformation on social media Pandemic science-policy dynamics during Japan's early COVID-19 response Cultural AI perception through techno-animism frameworks Global HPV vaccine discourse polarization on Twitter Wikipedia knowledge co-production during public health crises Scientific Contributions include: 2025: Kakiuchi Memorial Encouragement Prize for science communication 2011: NiSTEP Award for outstanding policy research Professional Leadership involves: Chairing the G7 Science Communication Working Group (2023-Now) Advisory roles for Tokyo Metropolitan Government (2021-Now) and JST's Genome Ethics Research Group (2017-Now) Editorial contributions to journals like Frontiers in Sociology and Scientific Data

• Science Communication
• Risk Communication
• Science Journalism
• +۴ مورد دیگر

Eiichiro Tanaka is a Professor at Waseda University's Faculty of Science and Engineering , specializing in Medical Assistive Technology , Robotics , and Design Engineering . His research focuses on developing wearable robotic systems for gait training, neuro-rehabilitation, and elderly mobility assistance. Key Research Areas : 1. Human-Robot Interaction for emotion-adaptive assistive devices. 2. Biomechanical Modeling of lower-limb assistance. 3. Ontological Frameworks for academic emotion analysis. 4. Non-Powered Exosuits for muscle fatigue reduction. His work integrates deep neural networks and physiological signal processing to create emotion-aware walking aids. Recent studies (2022-2020) demonstrate 24% fatigue delay and 16% walking distance improvement using RE-Gait® devices. Earlier projects include guide-dog robots and self-contained gear diagnostics . All publications employ 3D motion analysis , Wearable Sensors , and torque control algorithms .

• Medical Assistive Technology
• Robotics and Intelligent Systems
• Design Engineering
• +۳ مورد دیگر