Find Academic Supervisors

• Video Processing
• Image Processing
• Signal Processing
• +7 more

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)

• Cognitive Robotics
• Developmental Robotics
• Human-Robot Interaction
• +5 more

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.

• Perceptual information processing
• Computer Vision
• Artificial Intelligence
• +3 more

Hiroshi Ishikawa is a Professor in the Department of Computer Science and Engineering at Waseda University's Faculty of Science and Engineering. He also serves as a Visiting Professor at the National Institute of Informatics since 2016. Previously, he held positions at Nagoya City University from 2004-2010 as Assistant Professor, Associate Professor, and Professor. His academic journey includes being a JST PRESTO Researcher from 2009-2013 and an Associate Research Scientist at New York University's Courant Institute of Mathematical Sciences from 2000-2001. Ph.D. in Computer Science, New York University (2000) Master of Science, Kyoto University Bachelor's degree in Mathematics, Kyoto University Faculty of Science (1991) Hiroshi Ishikawa's research spans perceptual information processing, computer vision, artificial intelligence, deep learning, and discrete optimization. His work focuses on developing algorithms for image restoration, segmentation, and understanding, with significant contributions to energy minimization techniques in computer vision. He has pioneered approaches in sketch simplification, medical image segmentation, and higher-order graph cuts. His research bridges theoretical advances in mathematical optimization with practical applications in medical imaging, computer graphics, and consumer electronics. Ishikawa's recent publications demonstrate a strong focus on leveraging deep learning for image enhancement and understanding. His work spans super-resolution techniques, colorization methods, human avatar generation, and medical image analysis. A notable trend is the increasing integration of attention mechanisms and generative models to solve complex vision problems, with growing emphasis on real-world applications in medical imaging and computer graphics. His research group consistently produces high-impact work that appears in top-tier computer vision conferences. 75th Annual IEICE Best Paper Award (2019) Innovative Technologies 2016 Special Prize for Culture (Ministry of Economy, Trade and Industry) MIRU Nagao Award (Best Paper Award) (2009) Young Author Award (IEEE Computer Society Japan Chapter, 2006) MIRU2006 Excellent Paper Award (2006) Harold Grad Memorial Prize (Courant Institute of Mathematical Sciences, NYU, 2000) As a professor at Waseda University, Ishikawa has mentored numerous students who have become active researchers in computer vision, including Yuya Masuda, Edgar Simo-Serra, and Satoshi Iizuka. His research has been supported by various grants, including JST PRESTO funding from 2009-2013. He has served on editorial boards for prestigious journals including IEEE Transactions on Pattern Analysis and Machine Intelligence and has held leadership roles in major computer vision conferences such as ICCV, CVPR, and ACCV. Ishikawa leads a vibrant research group at Waseda University focused on computer vision and image processing. His laboratory collaborates extensively with researchers at Nagoya City University, National Institute of Informatics, and international institutions. The group maintains strong connections with industry partners, particularly in medical imaging and consumer electronics sectors, translating theoretical advances into practical applications.

Naoki YoshinagaView profile

Associate Professor

• Natural Language Processing
• Computational Linguistics
• Multilingual and Multimodal NLP
• +4 more

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 .

Keigo KobayashiView profile

Associate Professor

• Architectural planning
• City planning
• Urban design
• +5 more

Keigo Kobayashi is an Associate Professor at Waseda University's Faculty of Science and Engineering, School of Creative Science and Engineering, Department of Architecture. He has served in this position since 2016, previously holding the rank of Assistant Professor from 2012 to 2016. His professional journey includes significant experience at the Office for Metropolitan Architecture (OMA) in Rotterdam, where he worked as a Senior Architect and Project Architect from 2007 to 2012. His educational background includes a Master of Architecture II from Harvard University's Graduate School of Design (2005), a Master of Architecture from Waseda University's Graduate School of Science and Engineering (2003), and a Bachelor's degree in Architecture from Waseda University's School of Science and Engineering (2002). Kobayashi's research focuses on architectural planning and city planning, with particular interests in food-related architecture, spatial behavior, and sustainable design. His work explores the intersection of architecture with everyday life, examining how spatial configurations influence human behavior and community formation. Recent research has investigated food systems in urban contexts, playful approaches to spatial design, and the relationship between architectural form and environmental performance. His publications demonstrate a strong focus on practical applications of architectural theory, with projects spanning from food truck design in Shodoshima to zero-energy housing solutions and innovative approaches to architectural education. His work shows a consistent interest in how architecture can respond to contemporary social challenges while maintaining theoretical rigor. Excellence in Concrete Construction Award 2019, American Concrete Institute (ACI), Qatar National Library / OMA Kobayashi actively contributes to architectural education through various committee memberships, including serving as Chief of the Subcommittee on Strategies for International Compatibility in Architectural Education at the Architectural Institute of Japan and leading the Caberra Accord Correspondence Subcommittee at the Japan Accreditation Board for Engineering Education. His teaching portfolio at Waseda University is extensive, covering architectural design studios from undergraduate to doctoral levels. He leads several research initiatives, including the Wakusei Project in Tosa, Kochi, NPO PLAT (Platform for Architectural Thinking), and the European Thinkbelt/McDonald's Radio University project which represents an innovative approach to architectural education and community engagement, particularly in contexts of migration and cultural exchange.

• 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.

• Information Security
• Privacy
• Autonomous Driving
• +5 more

Dr. Tatsuya Mori is a Professor at the Department of Computer Science and Communication Engineering , Faculty of Science and Engineering, Waseda University . He also holds visiting researcher positions at RIKEN Center for Advanced Intelligence Project (since 2018) and National Institute of Information and Communications Technology (since 2019). Education: Ph.D. in Information Science (2005), Waseda University Research Interests: Spanning information security and privacy across emerging technologies like autonomous driving , AI , 3D sensing , VR , biometric measurement , and Web3 . His work focuses on offensive security and interdisciplinary research , including physical-layer attacks on sensors and behavioral studies on phishing detection. Scientific Awards: Recipient of multiple prestigious awards, including the Distinguished Paper Award Runners-Up at IEEE EuroS&P 2024 , IPSJ Outstanding Paper Award 2024 , and CSS2024 Concept Research Prize . His research has been recognized in top conferences like USENIX Security , NDSS , and ACM CCS . Professional Leadership: Active in academic governance as Chief Investigator for NISC Working Groups and Committee Member for JST Research Areas . He serves on program committees for NDSS , IMC , and ACM CCS .

• Data science
• Machine learning
• Business analytics
• +10 more

Masayuki Goto is a Professor in the Department of Industrial Systems Engineering, School of Creative Science and Engineering at Waseda University, Japan, where he has served since 2011. He earned his Doctor of Engineering from Waseda University and leads research integrating statistical science, machine learning, information theory and management engineering to solve business-analytics, marketing, AI ethics and industrial optimisation problems. Education: Doctor of Engineering, Waseda University Research Interests: His work spans data science, machine learning, business analytics, statistical learning theory, generative AI, deep neural networks, natural language processing, network analysis and information theory, with recent emphasis on trustworthy AI and synthetic data generation. Publication Trends: Over 2024-2025 his group has published extensively on deep learning for tabular data, vision-language models, recommender systems, causal inference and ethical AI, demonstrating a shift toward generative-AI-driven business analytics and interpretable models. Scientific Awards: Best Paper Award, CIE51 2024 Outstanding Paper Award, APIEMS 2023 Best Paper Award, APIEMS 2022 Best Paper Award, 20th ANQ Congress 2022 2022 PC Conference Best Paper Award Best Paper Award, JASMIN 2021 Best Paper Award, 19th ANQ Congress 2021 Encouragement Award, AAMSA 2021 IDR User Forum 2020 Enterprise & DBSJ Special Awards Best Paper Award, APIEMS 2019 Best Paper Award, ANQ Congress 2018 World CIST'18 Best Paper Award Best Paper Award, ANQ Congress 2017 JSPS Grant Review Commendation 2016 JIMA Distinguished Research Award 2015 Best Paper Award, Journal of JIMA 2015 IPSJ National Convention Best Paper Awards (2015 & 2012) Advising & Grants: He has mentored a large cohort of graduate students evidenced by co-authorship on over 100 recent papers. He has served as PI on numerous JSPS KAKENHI grants and industry projects focused on data-driven management, AI marketing and ethical AI frameworks. Labs & Teams: He heads the Goto Laboratory within the Waseda Institute for Advanced Study, leading interdisciplinary projects on business AI, data-ethics education and industrial optimisation.

• Homomorphic Encryption
• Big Data Analysis
• Database Systems
• +6 more

Hayato Yamana serves as Professor at Waseda University's Faculty of Science and Engineering and concurrently holds the position of Vice President for IT Promotion and Chief Information Officer since October 2020. His academic journey began with a Dr. Eng. degree from Waseda University in 1993, followed by positions at the Electrotechnical Laboratory of MITI, before joining Waseda University as Associate Professor in 2000 and becoming full Professor in 2005. He has held significant leadership roles including Director of the Database Society of Japan and the Information Processing Society of Japan, as well as Vice Chair of IEICE's Information and Communication Society. Waseda University, Faculty of Science and Engineering (2005-Present) National Institute of Informatics, Visiting Professor (2005-Present) Waseda University, Vice President for IT Promotion (2020-Present) Deputy Chief Information Officer (2015-2020) His research spans homomorphic encryption, big data analysis, and computer architecture, with notable contributions in privacy-preserving computation, recommender systems, and secure data processing. His work bridges theoretical cryptography with practical applications in smart cities, healthcare, and e-commerce security. Recent publications demonstrate strong focus on accelerating homomorphic encryption operations, improving recommendation system diversity, and developing novel authentication mechanisms. Analysis of his 15 most recent publications reveals consistent emphasis on privacy-preserving technologies (particularly homomorphic encryption applications), innovative recommender system architectures, and biometric security solutions. His research group produces highly cited work at the intersection of cryptography, machine learning, and systems security, with practical implementations in real-world scenarios including smart grids, e-commerce, and healthcare. Fellow, Information Processing Society of Japan (IPSJ), 2020 Golden Core Award, IEEE Computer Society, 2018 Fellow, Institute of Electronics, Information and Communication Engineers (IEICE), 2018 IBM Faculty Award, 2009 Multiple Best Paper Awards from IEICE, IPSJ, and ITE Yamana has secured substantial research funding for projects in homomorphic encryption, smart city infrastructure, and privacy-preserving systems. His leadership extends to advising numerous doctoral students and directing major research initiatives including the Smart Systems and Services Innovative Professional Education Program. He maintains active collaborations with industry partners through projects involving secure computation and data analytics. His research group operates at the forefront of secure computing, with specialized laboratories focused on homomorphic encryption acceleration, privacy-preserving machine learning, and secure mobile authentication. The team actively develops practical implementations of cryptographic protocols for real-world applications in healthcare, finance, and smart city infrastructure, bridging theoretical cryptography with deployable security solutions.

• Optical fiber communication
• Space-division multiplexing (SDM)
• Wavelength-division multiplexing (WDM)
• +5 more

Itsuro Morita is Professor in the School of Fundamental Science and Engineering, Faculty of Science and Engineering, Waseda University, Tokyo. Before joining Waseda in 2022 he spent 23 years at KDDI R&D Laboratories, advancing from researcher to executive research fellow, and has been a visiting researcher at Stanford University. He is an IEEE Fellow and IEICE Fellow recognized for pioneering large-capacity, long-haul optical transmission systems. Education: 2004 – 2005 Tokyo Institute of Technology, Graduate School of Science & Engineering, Department of Electrical and Electronic Engineering (Doctoral coursework) 1990 – 1992 Tokyo Institute of Technology, Graduate School of Science & Engineering, Department of Physical Electronics (M.E.) 1986 – 1990 Tokyo Institute of Technology, School of Engineering (B.E.) Research Interests: Morita’s work sits at the intersection of optical fiber communication and software-defined networking. He explores ultra-high-capacity transmission via space-division multiplexing (multi-core/few-mode fibers), real-time MIMO digital signal processing for modal crosstalk mitigation, and SDN/NFV orchestration of disaggregated optical networks. Additional interests include quality-of-transmission estimation using machine learning, telemetry-enabled control planes (gRPC/gNMI), and metro-embedded edge/cloud architectures for IoT services. Publication Trends: Recent articles emphasize two converging themes: (i) petabit-per-second SDM/WDM experiments using novel fiber geometries and real-time DSP, and (ii) cloud-native SDN control frameworks that integrate machine-learning-based QoT prediction, YANG/NETCONF modeling, and open APIs (TAPI/OpenConfig) for multi-domain, partially disaggregated networks. These works collectively push both the physical capacity frontier and the agility of next-generation optical infrastructure. Scientific Awards: C&C Prize 2024 (NEC C&C Foundation) – contributions to WDM optical submarine cable systems IEICE Achievement Award 2021 – pioneering research on 10-Pbit/s ultra-large-capacity SDM transmission Telecom System Technology Award 2021 – 10.16-Pbit/s dense SDM/WDM transmission record IEEE Fellow (2021) – contributions to large-capacity high-speed transmission systems IEICE Fellow (2020) – research on trans-oceanic high-speed optical signal transmission Ichimura Industrial Award – Contribution Prize 2018 – development of terabit-class submarine cable systems Maejima Hisoka Award 2012 – proposal and demonstration of distributed-control soliton communication Minister of Economy, Trade and Industry Award for Advanced Technology 2006 – 160 Gbit/s ultra-high-speed optical transmission technology Advising & Grants: At Waseda University Morita advises graduate students on experimental photonic networking and leads externally funded projects on petabit SDM transmission and SDN orchestration. While specific grant numbers are not disclosed, his continuous industry-university collaborative testbeds (with KDDI, CTTC, and others) indicate substantial competitive funding. Labs & Teams: He heads the Optical Space-Division-Multiplexing Laboratory at Waseda, maintaining joint experimental facilities with KDDI Research and international partners (e.g., CTTC, Spain). The group operates real-time coherent MIMO testbeds, multi-domain SDN controllers, and fiber-level SDM prototypes capable of petabit-per-second demonstrations.

• Space Systems
• Micro/Nano-satellites
• Formation Flight
• +5 more

Shinichi NAKASUKA is a Professor at the Graduate School of Engineering, The University of Tokyo, specializing in Space Technology with primary focus on Spacecraft Systems development and space-based observation technologies. His research integrates Micro/Nano-satellites, Formation Flight, and Space Interferometry to advance autonomous space systems. Key contributions include development of densified pupil interferometry for infrared space telescopes, high-precision formation flight control for synthetic aperture systems, and adaptive optics applications in space environments. His work bridges spacecraft engineering with astronomical observation techniques, emphasizing practical implementation of novel space technologies through nano-satellite platforms. Professor NAKASUKA has secured continuous research funding through Japan's Grants-in-Aid program since 1995, with recent projects including: Performance verification of densified pupil interferometry on formation flight simulator Pyxis toward space infrared interferometers (2023-2026, Co-Investigator) Ground Demonstration Experiment of a Synthetic Aperture Telescope with High Precision Formation Flight and Adaptive Optics (2021-2023, Co-Investigator) Research on Practical On-Orbit Servicing Systems Using Nano-Satellite Technologies (2009-2011, Co-Investigator) Development and on-orbit operation of nano-satellite systems enabling rapid technology demonstration (2004-2006, Principal Investigator) Study on trial development of can-sized satellites through Japan-US collaboration (2002-2003, Principal Investigator) His leadership spans electric propulsion systems development, knowledge processing for space applications, and pioneering university nano-satellite programs. While specific student mentorship details are not provided, his extensive project portfolio indicates active supervision of graduate researchers in spacecraft systems engineering.

• Energy Chemistry
• Inorganic Materials Chemistry
• Solid-State Ionics
• +2 more

Professor Masashi Okubo at Waseda University's School of Advanced Science and Engineering specializes in electrochemistry and energy materials development. With cross-appointments at Kyoto University and the Advanced Collaborative Research Organization for SmartSociety, his work focuses on sustainable battery systems including aqueous proton batteries, MXene-based electrodes, and oxygen-redox chemistry. His research bridges fundamental materials science with practical energy storage applications through combined experimental-theoretical approaches. Education : Ph.D. in Basic Science (2005) and M.Sc./B.Sc. in Basic Science from The University of Tokyo Research Strengths : Solid-state ionics and intercalation chemistry MXene electrode engineering Oxygen-redox reaction mechanisms High-rate energy storage systems Hydrate-melt electrolyte optimization Scientific Contributions include: Discovering near-zero-volume-phase battery materials Developing distortion-relieving voids in host structures Elucidating multiorbital bond formation in oxygen-redox reactions Advancing aqueous redox-flow battery catholyte design Prominent Awards : Waseda Research Award (2021) ACS Reviewer Excellence Award (2018) Ministry of Education Young Scientist Award (2017) Multiple Young Investigator Awards (2016)

• Theoretical Particle Physics
• Nuclear Physics
• Cosmic Ray Physics
• +7 more

Masatoshi Takano is a Professor at the Faculty of Science and Engineering, Waseda University, specializing in theoretical studies of nuclear physics, particle physics, and astrophysics. His work focuses on nuclear equations of state (EOS) for neutron stars and core-collapse supernovae, incorporating realistic nuclear forces like the Argonne v18 and Urbana IX potentials. He has developed variational methods with explicit energy functionals to model hyperonic nuclear matter, spin-orbit forces, and finite-temperature effects. Education : PhD in Science, Waseda University Professional Memberships : American Physical Society, Japan Physical Society Research spans neutron star structure, supernova simulations, and nuclear matter phase transitions. His recent presentations address neutrino emission rates, braking radiation in nuclear matter, and cluster variational methods. Key collaborations include H. Togashi, K. Nakazato, and K. Sumiyoshi. Scientific contributions involve refining variational energy expressions for asymmetric nuclear matter, incorporating three-body forces, and studying pion condensation effects on neutron star cooling. He has applied his EOS models to multidimensional supernova simulations and cosmic ray detector design.

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

• Biomaterials
• Biomedical Engineering
• Non-clinical testing methodology for Medical Devices
• +3 more

Professor Kiyotaka Iwasaki at Waseda University's Faculty of Science and Engineering is a leading figure in biomedical engineering with a focus on cardiovascular device development , tissue engineering , and regulatory science . His career spans over two decades at Waseda University, including roles as Associate Professor (2006-2014) and positions at Harvard Medical School's Laboratory for Tissue Engineering. Holding a Doctor of Engineering from Waseda, he serves on numerous international regulatory committees and has contributed to ISO/TC194 standards for medical devices. 1993-2002: Waseda University Education in Mechanical Engineering 2001-2004: Research Associate at Waseda University 2004: Research Scientist at Harvard Medical School 2018-Present: Professor at Waseda University His research interests include Non-clinical testing methodologies for medical devices Regulatory science frameworks Tissue engineering for ligament and cardiac applications Cardiovascular biomedical engineering His scientific contributions reveal through Development of decellularized tissue grafts for orthopaedic surgery Innovations in 3D cardiac tissue engineering using fibrin-based cell sheet stacking Pioneering bioresorbable stent technology with magnesium alloys Creation of biomechanical simulators for valvular disease modeling His awards span from the 2021 Japanese Ministerial Science Commendation 2020 JSME Standards Award 2018 ARIA Innovation Award 2001 ASAIO Fellowship While his publications demonstrate expertise in Vascular and cardiac device testing Bioresorbable stent evaluation Machine learning in medical device regulation Decellularized tissue applications