Find Academic Supervisors

• Multimedia Signal Processing
• Computer Networks
• Communication Engineering
• +3 more

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.

Katsuro InoueView profile

Professor

• Software Engineering
• Program Analysis
• Code Clone Detection
• +5 more

Katsuro Inoue is a Professor at Ritsumeikan University within the College of Information Science and Engineering. He holds a Dr. degree of Engineering from Osaka University (1984) and specializes in Software Engineering with a focus on Program Analysis , Code Clone Detection , Software Ecosystem Analysis , and Process Modeling . His work includes developing systems like CCFinder for code clone analysis and SPARS for software component significance ranking. Research Interests Program Analysis: Code Clone Analysis, Origin and Evolution Analysis, Software Ecosystems, Bug Detection, Analysis Tools and Algorithms Program Reuse: Code Search Engines, Program Archives, Searching Mechanisms Software Process: Process Modeling, Process Centered Environments, Process-Based Metrics, Quality Standards Key Publications Code Clone Analysis (2021), Library Dependency Updates (2018), Code Clone Tracking in Open Source (2012), Distributed Code Clone Detection (2007), Software Component Significance Ranking (2005), Compiler Garbage Collection (1991), Code History Tracking (2012) Professional Activities Program Committee Member in over 20 conferences (ICSE, IWPSE, PROFES) Editorial Board Member for IEEE Transactions on Software Engineering Co-Chair of multiple workshops (IWSC, IWPSE) Reviewer for SEC Journal Teaching Course: System Architect Course Developed course materials for Compiler Design and Language Processing Created exam problems and optimization examples for language processing courses

• Mechatronics
• Robotics
• Safety Engineering
• +6 more

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.

• Computer Architecture
• Parallel Computing
• Compiler Technology
• +3 more

Keiji Kimura 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. He earned his Doctor of Engineering from Waseda University and has held academic positions at the university since 1999, progressing from Research Associate to Assistant Professor (2004-2005), Associate Professor (2005-2012), and Professor (2012-present). He is affiliated with multiple professional organizations including ACM, IEEE Computer Society, The Institute of Electronics, Information and Communication Engineers, and Information Processing Society of Japan. His research focuses on computer architecture, particularly parallel computing systems and compiler technology. Kimura has made significant contributions to the development of the OSCAR (Optimally Scheduled Advanced Multiprocessor) automatic parallelizing compiler framework. His work spans multiple areas including multicore processor architecture, power reduction techniques for embedded systems, non-volatile memory systems, and parallelization methods for heterogeneous architectures. His research interests specifically include Multiprocessor Architecture and Parallelizing Compiler development, with applications in real-time systems and energy-efficient computing. Analysis of his recent publications reveals a strong focus on practical implementations of parallel computing technologies across diverse hardware platforms including RISC-V, ARM, and heterogeneous multicore systems. His work demonstrates a consistent trajectory from theoretical compiler development toward practical applications in embedded systems, security, and non-volatile memory technologies. The publications show increasing emphasis on RISC-V architecture, persistent memory programming, and power-efficient computing solutions. MEXT Award for Science and Technology (Research category), 2014.04 Ministry of Education, Culture, Sports, Science and Technology (MEXT) Kimura has served on numerous prestigious conference program committees including PACT, IPDPS, HPCA, and LCPC. His research has been supported through collaborations with major technology companies and government initiatives such as the METI/NEDO project entitled "Multicore Technology for Realtime Consumer Electronics." His work with the OSCAR compiler framework has demonstrated significant performance improvements and power reductions in real-world applications. He leads research in the APAL laboratory (http://www.apal.cs.waseda.ac.jp/) at Waseda University, focusing on advanced parallel processing technologies. His team works on compiler-directed approaches to solve challenges in heterogeneous multicore architectures, with particular emphasis on making parallel programming more accessible while optimizing for both performance and power efficiency. Current research directions include RISC-V secure boot verification, non-volatile memory systems, and GPU-based persistent memory solutions.

• Educational technology
• Science education
• e-learning
• +4 more

Kusumoto Noriaki is a Professor at Waseda University's School of Education within the Faculty of Education and Integrated Arts and Sciences. With a Doctor of Science degree from Waseda University, he maintains an active research profile with teaching responsibilities for 2025 including Seminar in Cultural Sciences, Introduction to Information Processing, Cultural Sciences: Maps, Information Society/Information Ethics, and Application of Information Technology and Career courses. His academic work bridges educational technology and biological sciences, reflecting a unique interdisciplinary approach. Professor Kusumoto's research interests focus on educational technology and science education, particularly e-learning and Web-Based Training (WBT) systems. His work demonstrates significant contributions to language learning technologies, including mobile learning applications for English vocabulary acquisition, learning history analysis for personalized instruction, and corpus development for language proficiency assessment. He has also maintained a parallel research line in photosynthetic reaction centers of green sulfur bacteria, with publications dating back to the 1990s that examine electron transfer mechanisms and ferredoxin interactions. His publication record shows a clear evolution from biological research toward educational technology applications, with recent work (2003-2008) predominantly focused on language learning systems, data infrastructure for educational research (VALIS project), and information ethics. The 15 most recent publications reveal a strong emphasis on practical applications of technology in language education, with particular attention to mobile learning, learning analytics, and networked systems for language data collection and analysis. His work consistently addresses the intersection of technology, pedagogy, and practical implementation challenges. Professor Kusumoto has been involved in numerous research projects funded by the Japan Society for the Promotion of Science, including 'Data Collection and Annotation of Relatively Spontaneous Utterances by Japanese Learners of English' (2009-2013) and 'English learning with handheld devices' (2007-2009). His professional memberships include the Biophysical Society of Japan, Japanese Society for Biology Education, Japan Society for Educational Technology, and Information Processing Society of Japan, reflecting his dual expertise in both biological sciences and educational technology. As a concurrent researcher at the Waseda Research Institute for Science and Engineering and affiliated with the Global Education Center (2024-2026), Professor Kusumoto maintains an active research presence. His work on information ethics, particularly in educational contexts, demonstrates his commitment to addressing the social and ethical dimensions of technology in learning environments. His early research on photosynthetic reaction centers continues to inform his approach to science education methodology and biological curriculum development.

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

• Cognitive Psychology
• Psycholinguistics
• Experimental Psychology
• +2 more

Yasushi Hino is a Professor at the School of Humanities and Social Sciences , Waseda University . His research focuses on Cognitive Psychology and Psycholinguistics , particularly the interplay between orthography, phonology, and semantics in Japanese and cross-linguistic contexts. Ph.D. in Psychology from The University of Western Ontario (Canada) Key research areas: Masked Priming , Orthographic-Phonological Consistency , Bilingual Word Recognition , and Phonological Units in Kanji . Hino’s work investigates how logographic scripts (Kanji, Katakana) and alphabetic scripts influence lexical decision-making, speech production, and semantic activation. His studies often employ masked priming paradigms and cross-modal tasks to explore phonological feedback, morphological decomposition, and bilingual integration of phonological representations. Recent publications (2025–2020) highlight his contributions to understanding orthographic-semantic consistency effects , phoneme-based Stroop effects , and backward priming in logographic scripts . Collaborations include researchers like Stephen J. Lupker , Debra Jared , and Mariko Nakayama . Hino is a member of the Japanese Psychological Association , American Psychological Association , and Psychonomic Society . He has presented extensively at international conferences, including the Psychonomic Society and Cognitive Neuropsychology Research Meeting , and contributed to key publications such as Cognitive Neuropsychology of Language and New Developments in Cognitive Psychology .

• Information Theory
• Coding Theory
• Statistical Learning Theory
• +3 more

Shunsuke Horii is an Associate Professor at the Center for Data Science, Waseda University. His research spans information theory, coding theory, statistical learning theory, and data science applications. He actively collaborates with industry through initiatives like the Waseda Data Science Consortium. Education: Ph.D. in Science and Engineering from Waseda University (2009), Master's from Waseda University Graduate School of Science and Engineering (2004). Research Focus: Addresses causal effect estimation in data science using Bayesian decision theory, sparse modeling, and optimization techniques like ADMM and variational inference. Develops efficient algorithms for multiuser communication, matrix completion, and privacy-preserving distributed computing. Teaching: Instructs courses on statistics literacy, data science, and programming with Python/R across multiple academic quarters. Grants: Leads projects funded by Japan Society for the Promotion of Science, including causal inference frameworks, product recommendation systems, and business analytics. Publications: 21 papers with 61 Scopus citations, focusing on LP decoding, Bayesian hierarchical models, and statistical causal analysis.

• Logic Programming
• Constraint Programming
• Hybrid Systems
• +2 more

Kazunori Ueda is a Professor at Waseda University's Faculty of Science and Engineering, with a career spanning over three decades in logic/constraint programming, hybrid systems, and concurrency. He has held visiting positions at the Egypt-Japan University of Science and Technology and part-time roles at the University of Tokyo. His research bridges theoretical advancements and practical implementations, focusing on languages like HydLa and LMNtal for hybrid and concurrent system modeling. Research Interests: Logic and Constraint Programming Hybrid Systems Modeling Concurrency and Parallelism Programming Language Design and Implementation Article Trends: Recent works emphasize symbolic simulation of hybrid systems, graph rewriting optimization, and distributed storage reliability. His work integrates interval arithmetic, constraint hierarchies, and formal verification techniques. Scientific Awards: Fellow, Japan Society for Software Science and Technology (2016) Fellow, Information Processing Society of Japan (2015) Basic Research Award, Japan Society for Software Science and Technology (2011) Multiple Best Paper and Encouragement Awards (1985–2010)

• Information Centric Networking
• Distributed Systems
• Communication Quality
• +3 more

NAKAZATO, Hidenori is a Professor at the Waseda University, School of Fundamental Science and Engineering , specializing in Computer Science . His research focuses on Information Centric Networking (ICN) , Distributed Systems , and Communication Quality optimization. Education: Ph.D. and MS in Computer Science from University of Illinois (1993) Professional Memberships: IPSJ, IEICE, ACM, IEEE His work explores advanced networking paradigms like Named Data Networking (NDN) , IoT virtualization via platforms such as VirIoT , and edge cloud computing for multimedia workflows. Key contributions include optimized cache replacement algorithms and service function chaining frameworks to enhance resource utilization and reduce latency. His scientific awards include: Fellow , Institute of Electronics, Information and Communication Engineers (2018) Chairman's Award , IEICE Communication Systems Committee (2013) NAKAZATO's publications (94 papers, h-index 10) address topics like blockchain performance , NDN mobility support , and energy-efficient computing . His research projects involve collaborations with international teams on smart city applications and container orchestration using Kubernetes.

TSUMURA TomoakiView profile

Professor

• Parallel Processing
• High Performance Computing
• Computer Architecture
• +7 more

TSUMURA Tomoaki is a Professor at the Department of Information Engineering, Graduate School of Engineering, Nagoya Institute of Technology. With a Doctor of Informatics from Kyoto University (2004), he has established himself as a leading researcher in computer architecture, parallel processing, and high-performance computing. His academic career spans from research assistant positions at Kyoto and Toyohashi Universities to his current professorship at Nagoya Institute of Technology. Graduated from Faculty of Engineering, Kyoto University (1996) Master of Engineering, Graduate School of Engineering, Kyoto University (1998) Doctor of Informatics, Graduate School of Information and Communication, Kyoto University (2004) Professor TSUMURA's research focuses on parallel processing systems, high-performance computing architectures, and innovative memory systems. His work bridges theoretical computer science with practical implementations, particularly in transactional memory systems, auto-memoization processors, and GPU computing. His research group has made significant contributions to shared memory parallel computing platforms that balance productivity and performance, with recent work extending to approximate computing applications and energy-efficient processor designs. His publication record shows a consistent output of high-impact research, with numerous papers presented at prestigious venues like xSIG, IEEE conferences, and IPSJ journals. The research trends indicate a strong focus on practical computing systems that address real-world challenges in parallelism, memory management, and energy efficiency. Recent work has particularly emphasized GPU computing, transactional memory systems, and precision optimization in numerical computing. Computer Science Field Achievement Award (IPSJ, 2019) Activity Contribution Award (IEICE, 2017) Multiple Best Paper/Research Awards from IEEE, ICNC, and xSIG conferences 1st Place in Championship Branch Prediction (CBP 2025) Professor TSUMURA has successfully secured substantial research funding, including multiple JSPS Grant-in-Aid projects spanning from 2006 to the present. His current major project "Software cache and distributed time management for shared memory massively parallel computing platform" (2025-2029) continues his long-standing research trajectory. He actively advises numerous graduate students, with many appearing as first authors on publications where he serves as corresponding author. His leadership extends to committee memberships including Chair of the IPSJ System Architecture Research Group and Editor-in-Chief of the IPSJ Journal of Computing Systems. Through his laboratory (tsumulab.org), Professor TSUMURA leads a research team focused on next-generation computing systems, with particular emphasis on practical implementations of theoretical concepts in computer architecture. The lab maintains strong industry and academic collaborations, evidenced by joint research projects and participation in international competitions like Championship Branch Prediction.

• Distributed Systems
• Network Systems
• Operating Systems
• +3 more

Hiroshi Matsuo is a Professor in the Department of Information Engineering at Nagoya Institute of Technology's Faculty of Engineering, with additional affiliations in the Graduate School of Engineering (Network Program) and Information Technology Center. His research focuses on distributed systems, network architecture, and operating systems with practical applications in cloud infrastructure. Education: Doctor of Engineering, Nagoya Institute of Technology (1989) Master of Engineering, Nagoya Institute of Technology Bachelor of Engineering, Nagoya Institute of Technology (1983) Matsuo's research centers on performance optimization in virtualized environments, particularly addressing bottlenecks in network I/O, distributed databases, and cloud-native applications. His work bridges theoretical informatics with practical system implementations, emphasizing real-world scalability and efficiency in high-throughput computing environments. Key contributions include novel caching mechanisms, transaction processing acceleration, and resource contention solutions for virtual network functions. Recent publications demonstrate consistent focus on network function virtualization and distributed systems, with increasing emphasis on hardware-aware optimizations and transparent proxy architectures. His team's work shows strong progression from foundational operating system research toward cloud-native infrastructure solutions, maintaining relevance in both academic and industrial contexts. Awards: IEEE NFV-SDN 2018 Best Paper Award 12th IEICE Communications Society Paper Award (2017) 2022 IEICE Information and Communication Management Research Award 1st International Conference on Networking and Computing Best Paper Award (2010) JAWS2010 Excellent Paper Award Matsuo has supervised numerous graduate students evident through co-authorship patterns in publications, particularly in network systems and distributed computing. His research has been supported by institutional projects on distributed processing frameworks, though specific grant details aren't publicly documented. He maintains active industry collaborations through his work on Microsoft Defender integration and enterprise networking solutions. His laboratory within Nagoya Institute of Technology's Network Field focuses on practical systems research, combining DPDK-based implementations with theoretical performance modeling. Current work emphasizes cache optimization for virtualized network functions and transaction processing acceleration in distributed databases, maintaining strong ties to industry partners through the Information Technology Center.

Daisaku YokoyamaView profile

Assistant Professor

• Parallel and Distributed Processing
• Combinatorial Search
• Game Tree Search
• +4 more

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

• Theoretical astrophysics
• Core-collapse supernovae
• Neutrino transport and oscillations
• +3 more

Ryuichiro Akaho is a tenure-track Assistant Professor in the Faculty of Science and Engineering, School of Advanced Science and Engineering at Waseda University, Japan. He earned his B.S., M.S., and Ph.D. in physics from the same university and is internationally recognized for developing general-relativistic Boltzmann neutrino transport codes applied to core-collapse supernovae and neutron-star cooling. Education: Ph.D. in Science, Waseda University, 2021–2024 M.S. in Advanced Science and Engineering, Waseda University, 2019–2021 B.S. in Advanced Science and Engineering (Physics), Waseda University, 2015–2019 Research Interests: Akaho’s theoretical work centers on neutrino radiation hydrodynamics in extreme astrophysical environments. He investigates how neutrinos drive supernova explosions, how flavor oscillations modify neutrino spectra, and how fallback accretion affects late-time neutrino emission from protoneutron stars. His simulations incorporate full general relativity, multidimensional transport, and state-of-the-art nuclear physics inputs. His recent studies reveal the universality of collisional flavor instabilities and quantify the detectability of supernova neutrinos by experiments such as Super-Kamiokande. These results bridge nuclear physics, high-energy astrophysics, and multimessenger astronomy. Awards & Honors: Young Scientist Presentation Award, Asia Nuclear Physics Association, 2025 HPCI Achievement Award (高エネルギー天体現象中の量子運動論的ニュートリノ輸送シミュレーション), RIST, 2024 Grants & Projects: PI, JSPS Grant-in-Aid for Early-Career Scientists, “The fate of massive stars explored by the first principle calculations in general relativity with nuclear physics,” 2024–2029 Co-I (completed), JSPS grant on black-hole formation and Boltzmann neutrino transport, 2023–2024 Teaching & Service: Since 2024 he has taught “Science and Engineering Experiment 1A” and “Physics Exercise B” to undergraduates at Waseda. He holds leadership roles in the Astronomical Society of Japan, Japan Physical Society, and two national astrophysical consortia (理論天文学宇宙物理学懇談会 and 宇宙核物理連絡協議会).

• Robotics
• Aerospace Engineering
• Mechanics and Mechatronics
• +3 more

Professor Tomoyuki Miyashita is a distinguished faculty member at Waseda University's Faculty of Science and Engineering, specializing in Mechanical Engineering. With a career spanning over three decades, he has established himself as a leading researcher in robotics, aerospace engineering, and mechanics and mechatronics. His academic journey began at Waseda University where he earned both his undergraduate and graduate degrees in Mechanical Engineering before embarking on his professional career. Dr. Miyashita's research interests span a remarkably diverse range of topics including robotics, medical systems, aerospace engineering, and design engineering. His work bridges theoretical foundations with practical applications, particularly evident in his numerous publications on surgical robotics, space structures, and intelligent mechanical systems. His research group has produced significant contributions in areas such as lunar rover mobility, medical robotics for laparoscopic surgery, and deployable space structures. His publication record demonstrates consistent high-impact research across multiple disciplines. Analyzing his recent works reveals a strong focus on robotic systems with applications spanning medical procedures, space exploration, and industrial automation. His research shows particular strength in optimization techniques applied to mechanical systems, haptic interfaces, and deployable structures. The interdisciplinary nature of his work is evident in collaborations across engineering, medical, and aerospace domains. IEEE ISATP2003 Best Paper Award (2003.07) JSCES Encouragement (2003.05) Professor Miyashita has mentored numerous students who have become co-authors on his publications, indicating an active research group with strong student involvement. His work has attracted significant research funding, particularly in the areas of space structures and medical robotics, though specific grant details are not provided in the current documentation. His laboratory appears to maintain strong connections with industry partners and international research institutions, facilitating collaborative projects across multiple domains of engineering.