Takeshi Ikenaga is a Professor at Waseda University’s School of Fundamental Science and Engineering and Graduate School of Information, Production and Systems . He earned his Ph.D. in Information & Computer Science from Waseda University in 2001, following B.E. and M.E. degrees in Electrical Engineering (1988–1990). His career spans roles at NTT LSI Laboratories (1990–2002), Kitakyushu Foundation for Advancement of Industry, Science and Technology (FAIS) (1999–2002), and visiting researcher at the University of Massachusetts (1999–2000). Research Interests : Application-specific SoCs for video/image processing, including compression (H.264/AVC, H.265/HEVC), filters (super-resolution, noise reduction), recognition systems (feature detection, object tracking), and communication (UWB, LDPC). He also works on many-core processor design, ultra-low-delay vision systems, and sports analytics (volleyball, figure skating) with real-time 3D pose estimation and ball tracking. Awards : Recipient of the Furukawa Sansui Award (Waseda University, 1988) IEICE Research Encouragement Award (1992) Multiple Best Paper/Presentation Awards (2006–2022) at conferences including DAC/ISSCC, LSI IP Design, ISOCC, ISPACS, and CVIT APSIPA Distinguished Lecturer Certificate (2015) Waseda University Presidential Teaching Award (2020)
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Naoki Yoshinaga is a tenured Associate Professor at the Institute of Industrial Science, The University of Tokyo, with extensive experience in natural language processing and computational linguistics. He has held academic positions since 2008 and currently leads research on pragmatic NLP models and multilingual systems. PhD in Computer Science, The University of Tokyo (2005-2008) MSc in Information Science (2000-2002) BSc in Information Science (1996-2000) His research focuses on mechanistic interpretability in NLP models, multilingual/multimodal NLP , and efficient model design using trie structures and conjunctive features. He also investigates knowledge acquisition from social data and evaluation metrics for language generation . Recent publications include work on neuron empirical gradient analysis (ACL-25), multilingual knowledge representation (EACL-24), and compact embedding methods (CoNLL-24). His research has been funded by multiple grants, including the University of Tokyo Excellent Young Researcher program and JSPS fellowships. Committee Special Award, Association for NLP (2023) JSAI SIG Research Award (2022) Best Interactive Award, DEIM Forum (2019, 2016) He developed widely-adopted NLP tools like pecco (fast classification library), RenTAL (LTAG-to-HPSG grammar converter), and J.DepP (Japanese dependency parser). His lab emphasizes strong equivalence in formalism comparisons and pragmatic model design .
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.
NAKAJIMA, Tatsuo serves as a Professor at Waseda University's School of Fundamental Science and Engineering, Department of Computer Network Engineering. Holding a Doctor of Engineering from Keio University, he has been affiliated with Waseda since 1999 after positions at Japan Advanced Institute of Science and Technology (1993-1999), Cambridge University, and Carnegie Mellon University. His academic profile shows substantial research output with 433 papers and 3,338 citations on Scopus, and 7,604 citations with an h-index of 42 on Google Scholar. Dr. Nakajima's research focuses on Distributed Systems, Embedded Systems, and Ubiquitous Computing, with particular emphasis on virtualization architectures for embedded environments. His work bridges theoretical computer science with practical applications in information appliances, operating systems, and persuasive computing technologies. He has developed innovative systems including SPUMONE (a composition kernel for multi-OS environments), SIGMA System, and SPLiT (a performance optimization library for multicore processors). Analysis of his 15 most recent publications reveals a consistent research trajectory centered on enhancing reliability, security, and performance of embedded and pervasive computing systems. His work shows increasing integration of human factors, particularly in sustainable behavior applications through persuasive technology. The research spans from low-level system architecture to user-centered applications, demonstrating both technical depth and practical relevance. Nokia Research Center, Visiting Research Fellow (2005.04) Dr. Nakajima's research has produced numerous practical frameworks including SPUMONE for multi-OS environments, SPLiT for performance optimization, and persuasive applications like EcoIsland for sustainable behavior. His work on kernel monitoring, anomaly detection, and self-healing systems demonstrates strong focus on system dependability. Current research appears directed toward integrating human factors with embedded systems, particularly in environmental sustainability applications. His laboratory work centers around the SPUMONE project, a virtualization layer for multi-core embedded systems that enables multiple operating systems to coexist with minimal engineering cost. This research environment supports exploration of resource management, security monitoring, and performance optimization in embedded contexts. The work has practical applications in information appliances, smart homes, and pervasive computing environments.
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.
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
- Mathematical Logic
- Computer Science
- Proof Theory
- +۵ مورد دیگر
Kazushige Terui is an Associate Professor at the Research Institute for Mathematical Sciences (RIMS), Kyoto University. His research focuses on mathematical logic and its applications to computer science, particularly proof theory, computational complexity, and nonclassical logics. He investigates proof normalization complexity, algebraic reformulations of proof-theoretic techniques, and logical foundations of computation. Terui maintains an active research group at RIMS and teaches courses including Mathematical Logic and Computer Science Fundamentals. Research Interests: Terui's work spans: Proof-theoretic aspects of nonclassical logics (linear logic, substructural logics) Computational complexity of proof normalization in lambda calculus Algebraic reformulation of logical techniques (cut-elimination, interpolation) Denotational semantics approaches to complexity characterization Effective proof discovery methods based on programming language theory Publications: His recent articles primarily explore proof theory, computational complexity, and logical foundations, with frequent focus on lambda calculus, linear logic, and type systems. Works frequently bridge theoretical computer science and mathematical logic. Education & Outreach: Authored the book Can Computers Become Mathematicians? (2015) for general audiences and maintains extensive lecture materials on mathematical logic and computer science foundations.
- Mechatronics
- Robotics
- Safety Engineering
- +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.
Professor Tomoji Kishi is a distinguished faculty member at Waseda University's School of Creative Science and Engineering, where he has been serving since 2009. Previously, he held academic positions at Japan Advanced Institute of Science and Technology (2003-2009) following a 21-year career at NEC Corporation (1982-2003). He earned his Ph.D. in Information Science from Japan Advanced Institute of Science and Technology in 2002, building upon his earlier engineering graduate studies at Kyoto University. Professor Kishi's research focuses on software engineering, particularly in software product line development, model checking, formal verification, and aspect-oriented modeling. His work bridges theoretical formal methods with practical applications in embedded systems, automotive software, and IoT technologies. He has made significant contributions to scalability challenges in model checking for configurable systems and has pioneered approaches to variability management and approximate modeling techniques. His publication record demonstrates remarkable consistency and evolution, with 42 papers and 153 citations according to Scopus data (h-index: 7), spanning from foundational work in software architecture in the 1990s to cutting-edge research on AI-enhanced verification methods in 2025. His recent work shows increasing application of machine learning techniques to traditional formal methods problems, particularly in the context of highly configurable systems and IoT applications. ITS Standardization Activity Merit Prize (2022) from Society of Automotive Engineers of Japan IPSJ/ITSCJ Standardization Contribution Award (2017) IPSJ/ITSCJ Project Editor Award (2016 and 2013) Information Processing Society of Japan Society Activity Contribution Award (2010) IPA/SEC Journal Best Paper Award (2007) Information Processing Society of Japan Yamashita Memorial Research Award (1998) Professor Kishi has led multiple JSPS-funded research projects, including recent work on 'variability management methods prioritizing usability through variability mining' (2020-2023) and 'utility-first modeling method' (2017-2020). His industry collaborations, particularly with automotive systems developers, demonstrate the practical impact of his research. He maintains active membership in major professional societies including IEEE Computer Society, ACM, and the Information Processing Society of Japan.
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.
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 .
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.
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.
Kazushi Kawamuraمشاهده پروفایل
استادیار
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.
- Robotics
- Control Systems
- Mechanical Engineering
- +۴ مورد دیگر
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.