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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
• +5 more

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
• +5 more

FURUZUKI, Takayuki is a Professor at Waseda University's Faculty of Science and Engineering, Graduate School of Information, Production, and Systems. He holds a PhD from Kyushu Institute of Technology and maintains the NCLab research group (http://nclab.w.waseda.jp/nclab/). His professional memberships include the Institute of Electronics, Information and Communication Engineers, Institute of Electrical Engineers of Japan, Society of Instrument and Control Engineers, and IEEE. His educational background includes a PhD in Information Science from Kyushu Institute of Technology (1994-1997), a Master's degree in Electronics Engineering from Sun Yat-Sen University (1983-1986), and a Bachelor's degree in Electrical & Electronic Systems Engineering from Sun Yat-Sen University (1979-1983). Professor FURUZUKI's research spans neural networks, genetic algorithms, system identification and control, complex systems, bioinformatics, and combinatorial optimization. His work integrates soft computing techniques with medical informatics and control systems engineering, developing innovative approaches for problems ranging from brain tumor segmentation to music information retrieval. His research methodology often combines theoretical foundations with practical applications in healthcare, energy systems, and intelligent transportation. His recent publication record shows a strong focus on sequential recommendation systems, graph neural networks for medical imaging, music information retrieval, and power systems analysis. The consistent thread across his work is the application of advanced machine learning techniques to solve complex, real-world problems across diverse domains, with particular emphasis on handling missing data, improving model efficiency, and enhancing prediction accuracy. His scientific achievements have been recognized with several prestigious awards: ISCIIA2008 Excellent Paper Award (2008) Institute of Electrical Engineers of Japan Excellent Paper Award (2001) Guangdong Province Higher Education Science and Technology Progress Second Prize (1991) Guangdong Province Higher Education Science and Technology Progress Second Prize (1989) Chinese Ministry of Education Scientific and Technological Achievements Second Prize (1986) Professor FURUZUKI has maintained continuous research activity since joining Waseda University in 2003, with significant contributions to multiple research projects spanning neural computation, soft computing, and system engineering. His work demonstrates strong international collaboration, with publications involving researchers from various institutions worldwide. His research output includes over 410 papers with 3,623 citations and an h-index of 23 according to Scopus data. The NCLab research group, which he leads, focuses on neural computation and related areas, providing a platform for interdisciplinary research that bridges theoretical foundations with practical applications in healthcare, energy systems, and intelligent transportation. His laboratory environment fosters innovation in machine learning algorithms and their application to real-world problems, with particular emphasis on developing efficient, robust solutions for complex data analysis tasks.

• Neural Networks
• Genetic Algorithms
• System Identification and Control
• +7 more

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
• +6 more

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
• +3 more

Takuya Taniguchi is an Associate Professor at the Center for Data Science, Waseda University, where he has been employed since 2019, first as an Assistant Professor (2019-2021) before promotion to his current non-tenure track position. His interdisciplinary research bridges organic chemistry, materials science, and data science, with a focus on developing and analyzing functional organic materials, particularly photo-responsive molecular crystals. He maintains active collaborations with research groups including Hideko Koshima and Toru Asahi, and serves on professional committees such as the Manufacturing Industry AI Promotion Association. Education Doctor of Engineering, Waseda University (2019) Graduate studies at Waseda University's Graduate School of Advanced Science and Engineering Undergraduate studies at Waseda University's School of Advanced Science and Engineering, Department of Life Science and Medical Bioscience Research Focus Professor Taniguchi's work centers on structural organic chemistry and physical organic chemistry , with particular emphasis on organic functional materials and the application of materials informatics to crystal engineering. His research investigates how molecular structure influences macroscopic mechanical properties, especially photo-mechanical behaviors in organic crystals. He has pioneered the use of machine learning techniques to predict crystal properties, optimize materials performance, and design novel functional materials with applications in soft robotics and energy conversion. His recent work demonstrates a clear progression from fundamental studies of photo-mechanical crystals toward increasingly sophisticated applications of machine learning in materials science. The 15 most recent publications reveal a strong focus on neural network potentials for crystal property prediction, optimization of photo-actuated materials, and exploration of phase transitions in molecular crystals. This research trajectory shows consistent innovation in combining experimental chemistry with advanced computational methods. Awards and Recognition Inoue Research Encouragement Prize (2019) Ono Azusa Memorial Award from Waseda University (2019) Student Presentation Award at Japan Chemical Society 99th Spring Annual Meeting (2019) Poster Presentation Award at Chirality 2017 Multiple poster and presentation awards at international crystallography conferences Research Leadership Dr. Taniguchi leads multiple research projects funded by JSPS, JST, and industry partners including ENEOS Corporation and Sumitomo Foundation. His current projects include 'Efficient crystal structure prediction for organic porous materials,' 'Machine learning simulation of HOF material stability,' and 'Machine learning application for organic solid-phase transition.' He has successfully secured competitive funding including JST ACT-X and JSPS Early-Career Scientist grants. His work has received significant media attention, with coverage in Nikkan Kogyo Shimbun and Kagaku Kogyo Nippo highlighting breakthroughs in light-driven organic crystals with 3.7x improved output force. Academic Contributions Beyond research, Professor Taniguchi teaches extensively in Waseda's Global Education Center, offering courses in data science, statistical analysis with R, and statistics literacy across multiple academic quarters. He has contributed chapters to technical publications on process informatics, Bayesian optimization, and crystallization process design. His scholarly impact is evidenced by an h-index of 11 (Google Scholar) with 581 total citations, demonstrating significant influence in the emerging field of materials informatics for organic crystals.

• Organic Functional Materials
• Materials Informatics
• Structural Organic Chemistry
• +4 more

Kenichi Oyaizu is a Professor in the Department of Applied Chemistry at Waseda University's School of Advanced Science and Engineering. With over 30 years of academic career, he has established himself as a leading researcher in polymer chemistry, with particular expertise in functional polymers for energy applications. His research group has produced over 300 publications with more than 12,000 citations, demonstrating significant impact in the field. Professor Oyaizu received his education entirely at Waseda University, completing his undergraduate studies in the Department of Applied Chemistry (1986-1990), followed by graduate work in the same department where he earned his PhD in Engineering (1990-1995). His academic journey progressed from JSPS Research Associate to his current position as Professor, with appointments at Tokyo University of Science along the way. Oyaizu's research focuses on polymer synthesis and functional polymers, with particular emphasis on energy storage materials, hydrogen storage systems, high refractive index polymers, and organic battery technologies. His work bridges fundamental polymer chemistry with practical applications in sustainable energy, demonstrating strong interdisciplinary approach that combines materials science, electrochemistry, and informatics. Analysis of his recent publications reveals a strong trend toward developing advanced polymer materials for energy applications, with particular focus on high refractive index polymers for optoelectronics and robust organic materials for batteries. His research increasingly incorporates materials informatics approaches, as evidenced by several publications applying AI and machine learning to polymer design and property prediction. Yamazaki Sho Award (2022) - Polymers for Reversible Hydrogen Storage Society of Polymer Science Japan Award (2022) - Functional Polymers for Energy Storage Minister of Education Science and Technology Prize (2013) Oleo Science Award (2007) Chemical Society of Japan Young Chemists Award (2002) Professor Oyaizu maintains active leadership roles in the academic community, serving on editorial boards and as committee member for multiple professional societies including the Society of Polymer Science Japan and Chemical Society of Japan. His research is supported by significant grants that enable his team to pursue innovative projects at the intersection of polymer science and sustainable energy technologies. The Oyaizu laboratory operates as a dynamic research environment where fundamental polymer chemistry meets practical energy applications, with particular emphasis on developing materials that address global energy challenges.

• Polymer Chemistry
• Functional Polymers
• Energy Storage Materials
• +5 more

Yuhiro Iwamoto serves as Associate Professor at Nagoya Institute of Technology within the Department of Electrical and Mechanical Engineering, with additional affiliation to the Graduate School of Engineering's Mechanical Engineering Program and the Center for Innovative Young Researchers. His academic foundation includes: Bachelor of Engineering from Doshisha University (2008) Master's degree from Doshisha University (2010) Doctor of Engineering from Doshisha University (2013) Dr. Iwamoto's research centers on fluid engineering phenomena with emphasis on magnetic responsive fluids. His work explores thermomagnetic pumping mechanisms, phase-change behavior in water-based magnetic fluids, and innovative applications of permanent magnet elastomers for energy harvesting and tactile sensing. This research bridges fundamental fluid dynamics with practical implementations in thermal management systems, robotic sensing, and sustainable energy technologies, demonstrating significant contributions to manufacturing technology and mechanical engineering disciplines. Analysis of his recent publications reveals a cohesive trajectory in functional fluid systems, particularly focusing on temperature-sensitive magnetic fluids for self-driving thermal transport and elastomer-based transduction mechanisms. His work consistently integrates material science, electromagnetic principles, and fluid mechanics to develop novel solutions for heat transfer enhancement, energy conversion, and soft robotics applications. His research excellence has been recognized through prestigious awards: Japanese Society of Mechanical Engineers Encouragement Award (2020) for research on thermal conductivity control using silver nanowire magnetic nanofluids Best Presentation Award at the 9th Asia-Pacific Symposium on Applied Electromagnetics and Mechanics (2018) Dr. Iwamoto actively contributes to academic governance as committee member for the Institute of Electrical Engineers of Japan's Special Committee on Electromagnetic Responsive Fluids (2019-2022) and the Japan AEM Society Editorial Committee (2017-2022). His industrial property portfolio includes multiple patents related to magnetic elastomers and thermal transfer systems, reflecting strong industry-academia collaboration. He maintains active membership in eight professional societies including The Japan Society of Applied Electromagnetics and Mechanics and The Japanese Society for Multiphase Flow.

• Fluid Engineering
• Magnetic Fluids
• Thermomagnetic Pumps
• +3 more

Masashi Takeichi is a researcher affiliated with the Institute of Science Tokyo , focusing on robotics and mechatronics. His work spans soft robotics, flexible arm systems, and medical robotics. His research includes the development of soft robotic actuators , Giacometti arms with balloon bodies , and thin wire-driven active endoscopes . The publications highlight advancements in kinematic modeling, air resistance analysis, and mock-up testing. Recent publications demonstrate trends in human-like robotics , medical device prototyping , and flexible mechanical systems . Key subfields include balloon actuation , soft robotics , kinematic analysis , and biomedical robotics .

• Robotics
• Soft Robotics
• Medical Robotics
• +5 more

Yoshihito Inai serves as Professor in the Department of Life and Applied Chemistry at Kyoto Institute of Technology's Faculty of Engineering. His research bridges polymer chemistry, organic chemistry, and nanotechnology with emphasis on molecular design of sequence-ordered polymers and helical structures. Education: Master of Engineering, Kyoto University Doctor of Engineering, Kyoto University Research Focus: Professor Inai specializes in structural organic chemistry and polymer conformational analysis , particularly investigating helical screw-sense control in achiral peptides through covalent/noncovalent interactions. His work integrates supramolecular assembly , photoresponsive materials , and bioinspired design to develop functional soft materials with applications in nanotechnology. Publication Trends: Analysis of his 13 publications (1999-2020) reveals sustained focus on helical polymer systems, with increasing sophistication in controlling chiral memory, solvent-responsive conformational switching, and metallo-supramolecular architectures. Recent work emphasizes theoretical-experimental integration for physical property tuning in advanced materials. Academic Engagement: He maintains active conference participation including invited lectures at the 32nd Tokai Polymer Workshop (2024) and frequent poster/oral presentations at Polymer Society of Japan meetings, demonstrating ongoing leadership in high polymer characterization and soft material design within Japan's academic community.

• Polymer Chemistry
• Organic Chemistry
• Materials Science
• +2 more

Saman Azhari is an Assistant Professor at the Graduate School of Information Production and Systems , Waseda University, Japan. His research focuses on Nanotechnology , Biosensors , and Reservoir Computing for biomedical and robotic applications. Developed self-sterilizing face masks using enzymatic power generation (2025) Engineered smart contact lenses for wireless cholesterol monitoring and ocular diagnostics (2025, 2024) Innovated CNT/PDMS nanocomposites for haptic sensors and in-sensor computing (2024, 2021) Explored 3D nanomaterial reservoir computing with SWNT/POM networks (2023, 2021) Collaborated on microwave-assisted CNT synthesis from waste materials (2018) His recent publications (2025-2023) emphasize flexible biosensors , atomic switch networks , and energy-efficient AI hardware . Key subfields include piezoresistive pressure sensing , synaptic plasticity in nanoparticle systems , and plant-insertable sucrose monitors . He holds patents for tactile sensing devices and mechanical sensors.

• Nanotechnology
• Materials Science
• Wireless Power Transmission
• +5 more

Youhua Shi is a full Professor in the Faculty of Science and Engineering at Waseda University, Japan. He obtained his Doctor of Engineering from Waseda in 2005 and is an active member of IEICE, IPSJ, IEEE, and two Japanese academic societies. His research portfolio integrates trustworthy computing, hardware security of AI accelerators, energy-harvesting interface circuits for triboelectric nanogenerators, and low-power VLSI design-for-test methodologies. Education: Doctor of Engineering, Waseda University (2005) Graduate studies, Waseda University, Division of Engineering (completed 2005) Research Interests: Prof. Shi pursues trustworthy and secure silicon systems, spanning hardware Trojans in automated AI-accelerator flows, radiation-hardened latch design for soft-error resilience, and power-efficient CNN accelerators exploiting zero-gating and data-reuse techniques. Parallel work targets energy-autonomous IoT through advanced interface circuits for triboelectric nanogenerators, achieving record energy-per-cycle beyond the classical CMEO limit. Publication Trends: Recent articles (2024-2025) emphasize two thrusts: (i) security of AI/FPGA accelerators—proposing stealthy hardware-Trojan frameworks embedded within design-space-exploration flows that can misclassify up to 97% of inputs—and (ii) power electronics for triboelectric harvesters—introducing dual-output rectifiers and Bennet-doubler biasing that multiply output power >150× over conventional full-wave rectifiers, enabling battery-free IoT nodes. Scientific Awards: APCCAS Best Student Paper Award – 2020 IEEK Best Paper Award – 2012 Students & Collaboration: He has mentored numerous doctoral and master’s scholars, including Yirui Su, Chao Guo, Jinghao Ye, Lin Ye, Saki Tajima, and Masaru Oya, many of whom serve as first authors on his high-impact publications, indicating an active and productive advising role. Labs & Teams: While the text does not name a specific laboratory, his continued affiliation with Waseda University’s Faculty of Science and Engineering and his extensive project output imply he leads a research group focused on secure & energy-efficient VLSI systems, collaborating closely with colleagues such as Prof. Masao Yanagisawa and Prof. Nozomu Togawa.

• Trustworthy computing
• Energy harvesting
• Intelligent system design
• +7 more

Kazushi Kawamura is an Assistant Professor at the Tokyo Institute of Technology 's AI Computing Research Unit , with prior roles at Waseda University and the Institute of Science Tokyo. His academic journey began at Waseda University, where he earned a Dr. Eng in 2016. 2025.04 - Now: Assistant Professor, School of Fundamental Science and Engineering, Tokyo Tech 2024.10 - 2025.03: Assistant Professor, School of Fundamental Science and Engineering, Waseda 2020.04 - 2025.03: Specially Appointed Assistant Professor, Institute of Integrated Research, Institute of Science Tokyo His research spans combinatorial optimization , annealing processors , Ising machines , and FPGA-based computing systems . He has contributed extensively to LSI design methodology and high-level synthesis . Key publication trends include neural network compression , parallel annealing algorithms , edge AI inference , and sparse matrix operations on FPGAs. His work often integrates theoretical optimization with practical hardware implementations . 2023 CS Achievement Award 2016 ISOCC Best Paper Multiple Algorithm Design Contest Prizes (2014-2019) IPSJ SLDM Outstanding Student Awards Kawamura teaches courses like Physical Electronics Laboratory and Machine Learning at Waseda, with recent projects such as Amorphica (metamorphic annealer) and Pianissimo (sub-mW DNN accelerator). He serves on committees for IEEE , IPSJ , and IEICE , focusing on system design and circuit optimization.

• Computer Systems
• Soft Computing
• Combinatorial Optimization
• +5 more

Hiroyuki Ishii is a Professor at Waseda University's School of Creative Science and Engineering, Faculty of Science and Engineering. With over 15 years of academic experience at Waseda University, he was promoted to full Professor in 2022 after serving as Associate Professor from 2016-2022. His research spans robotics, control systems, and mechanical engineering, with particular expertise in soft robotics and continuum manipulators. His educational background includes: Ph.D. from Waseda University (2004-2007) Master's degree from Waseda University Graduate School of Science and Engineering (2002-2004) Bachelor's degree from Waseda University School of Science and Engineering (1998-2002) Professor Ishii's research focuses on Robotics and Intelligent Mechanics and Mechanical Systems , with particular emphasis on soft robotics, continuum manipulators, and human-robot interaction. His work bridges theoretical control systems with practical applications in medical robotics, rehabilitation devices, and inspection systems. He has pioneered novel approaches in pneumatic actuation, growing robots, and bimanual continuum robot control, demonstrating exceptional creativity in solving complex mechanical challenges. His recent publications reveal a strong trend toward medical applications of robotics, particularly in surgical assistance and rehabilitation. There's also significant work on soft growing robots and continuum manipulators with innovative actuation mechanisms. His research shows increasing interdisciplinary collaboration, spanning mechanical engineering, computer vision, and biomedical applications. His notable awards include: Best Paper Award Finalist at IEEE ICMA2024 The Robotics Society of Japan 3rd Outstanding Research and Technology Award (2022) Minister of Education, Culture, Sports, Science and Technology Young Scientists Award (2018) Advanced Robotics Best Paper Award (2015) ICRA2014 Best Cognitive Robotics Paper Award Finalist Professor Ishii actively participates in research committees and professional societies, serving as Director of the Robotics Society of Japan since 2024. His research has received substantial funding through competitive grants, supporting his work on innovative robotic systems with practical applications in healthcare, infrastructure inspection, and human-robot collaboration. His laboratory develops specialized robotic systems including small mobile robots for animal interaction, soft growing robots, and continuum manipulators for surgical applications. The team combines mechanical design expertise with advanced control algorithms to create robots capable of operating in complex environments.

• Robotics
• Control Systems
• Mechanical Engineering
• +4 more

Ippei Obayashi is a Professor at Okayama University's Center for artificial intelligence and mathematical data science, with a visiting professorship at Tohoku University's Advanced Institute for Materials Research (AIMR). His academic career spans prestigious institutions including RIKEN, Tohoku University, and Kyoto University, where he earned his Doctor of Science degree. Okayama University, Center for AI and Mathematical Data Science, Professor (2021-present) RIKEN, Center for Advanced Intelligence Project, Researcher (2018-2021) Tohoku University, Institute for Advanced Materials Science, Associate Professor (2018) Tohoku University, Advanced Institute for Materials Science, Assistant Professor (2015-2018) Kyoto University, Research Fellow (2010-2015) Educational Background: Kyoto University, Graduate School of Science, Department of Mathematics and Mathematical Analysis (2006-2010, Doctoral) Kyoto University, Graduate School of Science, Department of Mathematics and Mathematical Analysis (2004-2006, Master's) Kyoto University, Faculty of Science (2000-2004, Bachelor's) Professor Obayashi's research focuses on topological data analysis (TDA) , particularly persistent homology and its applications, alongside dynamical systems theory. His work bridges pure mathematics with practical applications in materials science, where he has developed innovative methods to analyze complex material structures. He has made significant contributions to understanding magnetic materials, amorphous structures, and crystal formation through topological approaches, often integrating machine learning techniques with traditional mathematical analysis. His research has practical implications for energy materials, battery technology, and materials characterization. His publication record demonstrates a strong trend toward applying topological methods to solve real-world materials science problems, with increasing integration of machine learning techniques. Recent work shows sophisticated applications of persistent homology to analyze neutron scattering data, magnetic properties, and structural characteristics of materials, reflecting his ability to translate abstract mathematical concepts into practical analytical tools. Scientific Awards: JCS-JAPAN Excellent Paper Award, Ceramic Society of Japan (2020) 11th Sakuramai Research Encouragement Award, RIKEN (2020) Japan Society for Industrial and Applied Mathematics Best Author and Best Paper Awards (2017) 6th Fujiwara Hiroshi Mathematical Sciences Encouragement Award (2017) AIMR International Symposium Best Poster Award (2017) Professor Obayashi actively mentors graduate students through Okayama University's Graduate Student Program and leads research initiatives including the Japan Society for Industrial and Applied Mathematics Topological Data Analysis Research Group, which he chairs. His research is supported by multiple competitive grants, including Japan Society for the Promotion of Science (JSPS) funding for projects on mathematical data science and topological structure analysis. He collaborates extensively with researchers across disciplines, particularly in materials science and engineering. He is affiliated with the Center for artificial intelligence and mathematical data science (Angels) and the Cyber-Physical Engineering Informatics Research Division (Cypher) at Okayama University, where he leads efforts to develop and apply topological data analysis methods to complex scientific problems. His laboratory focuses on creating practical software tools like HomCloud for persistent homology analysis, bridging the gap between theoretical mathematics and applied scientific research.

• Topological Data Analysis
• Persistent Homology
• Dynamical Systems
• +3 more