جستجوی استاد راهنمای دانشگاهی

• Educational Technology
• Learning Support Systems
• Generative AI
• +۳ مورد دیگر

Shintaro Uchiyama serves as a Research Associate at Waseda University's Faculty of Human Sciences since April 2025. Previously, he held positions as a Part-time Lecturer at National Institute of Technology, Toyota College (2021-2024) and teaching assistant roles at Toyohashi University of Technology. His academic foundation includes Bachelor's and Master's degrees in Engineering from Toyohashi University of Technology, completed in 2020 and 2022 respectively. Bachelor of Engineering (2020), Toyohashi University of Technology Master of Engineering (2022), Toyohashi University of Technology Graduate Coursework Completed (2025), Toyohashi University of Technology Uchiyama's research focuses on educational technology innovation, particularly in generative AI applications for learning support systems and flipped classroom methodologies. His work bridges speech recognition technologies with educational applications, developing systems that enhance student engagement through immediate feedback mechanisms and annotation tools. Current projects include STEAM learning environments using XR technology and learning behavior analysis systems for correspondence high schools. His publication record demonstrates consistent output in educational technology conferences and journals, with recent work emphasizing large language models for educational feedback and mixed reality applications. Research trends show progression from foundational VR/Hololens educational tools (2018) toward sophisticated AI-driven learning systems (2023-2025), maintaining focus on practical classroom implementation. 特別研究報告会最優秀特別研究発表賞 (Toyohashi University, 2022) 優秀講演賞 (ATS2020 Symposium, 2021) Rinnai Scholarship Foundation Award (2022) Japan Student Services Organization Half-Repayment Exemption (2022) Multiple student support awards from Toyohashi University (2021-2022) Uchiyama actively contributes to educational research through JSPS-funded projects including 'Establishing STEAM learning environments utilizing generative AI' (2024-2029) and 'Learning behavior analysis for correspondence high schools' (2025-2027). His committee work includes publicity chair roles for International Conferences on Advanced Informatics. Professional memberships span the Japanese Society for Information and Systems in Education and Japan Society for Educational Technology since 2019-2020.

Yasutaka Kameiمشاهده پروفایل

استاد

• Empirical Software Engineering
• Software Reliability
• Software Testing and Debugging
• +۷ مورد دیگر

Yasutaka Kamei is a Full Professor at the Graduate School and Faculty of Information Science and Electrical Engineering , Kyushu University since 2024. He holds a Doctorate in Information Science from Nara Institute of Science and Technology and has been a InaRIS Fellow since 2023. His career spans roles as Associate Professor (2015-2023), Visiting Researcher at Queen's University (2015-2017), and Assistant Professor (2011-2015). Research Fields: Specializing in Empirical Software Engineering , he investigates software reliability, defect prediction, code review practices, and mining software repositories. His work on fuzz testing , technical debt , and automated program repair has produced influential frameworks like TraceJIT and PAFL . He pioneered studies on developer behavior in GitHub and federated learning for cross-project defect prediction. Scientific Trends: Recent publications focus on LLM applications in mutation testing , visual bug reporting , and CI/CD inefficiencies . His team explores developer-centric challenges in modern practices, including token-based micro commits and fuzzing build failures . Awards & Grants: InaRIS Fellowship (2023): 10-year, 100M yen grant for human-machine interaction in software development IPSJ/ACM Early Career Award (2013) Leadership: He chairs PC for MSR2018 , co-organizes NII Shonan Seminars , and serves on committees for ICSE , ASE , and SANER conferences. His editorial roles include Empirical Software Engineering and Automated Software Engineering journals.

• Machine Learning Applications in Finance
• Market Microstructure
• Foreign Exchange Markets
• +۲ مورد دیگر

Yoshihiro Kitamura is a Professor at Waseda University's Faculty of Social Sciences, School of Social Sciences, specializing in international finance and market microstructure. He has held academic positions at Waseda University since 2005 and previously taught at University of Toyama from 2006-2011. His academic journey began with undergraduate studies at Waseda University's Faculty of Humanities and Social Sciences in 1998, followed by graduate studies at Waseda University's Graduate School, Division of Economics in 2002. Professor, Waseda University (2013-Present) Associate Professor, Waseda University (2011-2013) Associate Professor, University of Toyama (2008-2011) Lecturer, University of Toyama (2006-2008) Research Assistant, Waseda University (2005-2006) Research Fellow, Japan Society for the Promotion of Science (2003-2005) Dr. Kitamura's research focuses on the application of machine learning to finance, market microstructure, foreign exchange markets, and international finance. His work bridges theoretical finance with empirical analysis, particularly examining how market participants process information and how that affects price formation in foreign exchange markets. He has developed innovative methodologies for measuring market efficiency, assessing foreign exchange intervention effectiveness, and understanding the role of informed trading in price discovery processes. His most recent research explores the application of cutting-edge AI techniques including generative adversarial networks (GANs) and large language models to foreign exchange rate prediction, building on his earlier work with LSTM networks and traditional econometric approaches. This represents a clear evolution in his research from theoretical models of exchange rate regimes to sophisticated machine learning applications for understanding market dynamics. Dr. Kitamura has received significant research funding from the Japan Society for the Promotion of Science, including current projects on price discovery processes using generative adversarial networks (2023-2028) and previous projects on deep learning applications in finance theory evaluation (2019-2023). His work demonstrates a consistent focus on understanding how information flows through financial markets and affects price formation, with increasing emphasis on computational methods in recent years. He actively contributes to the academic community through teaching courses in International Economics and International Finance at both graduate and undergraduate levels, and serves as a member of the Japan Society of Finance and Japanese Economic Association. His research has been published in top finance and economics journals including Journal of International Money and Finance, International Review of Financial Analysis, and Journal of International Financial Markets, Institutions & Money.

• Educational technology
• Second Language Acquisition
• Artificial Intelligence in Education
• +۴ مورد دیگر

John Maurice Gayed is an Associate Professor at the Global Education Center of Waseda University . Holding a PhD from Tokyo Institute of Technology (2023) , he specializes in Educational Technology , focusing on AI-driven tools for language learning and metacognitive strategies. Research Themes : AI writing assistants, equity in educational technology, cognitive load reduction for EFL learners. Grants : Japan Society for the Promotion of Science (JSPS) Grant (2022.04–2025.03) for AI-based writing assistant studies. Courses Taught : Academic Writing and Discussion in English (Alpha/Beta) for undergraduate and retaker students. His publications (9+3) span Computer Science , Linguistics , and Education , with key trends including: AI-based writing tools (e.g., AI KAKU, Grammarly) for EFL learners. Metacognitive training in online learning environments. Equity implications of educational technology (Matthew effect in CALL). Twine for nonlinear educational storytelling. Climate risk mitigation tools for elderly populations. MOOCs and blended learning in cross-cultural contexts. Grant Details : His JSPS-funded project investigates AI writing assistants' long-term impact on EFL writing proficiency. Collaboration with May Kristine Jonson Carlon and Jeffrey S. Cross is frequent, with tools like AI KAKU and metacognitive tutors being central to his work.

• Software Engineering
• Human-Computer Interaction
• Artificial Intelligence
• +۳ مورد دیگر

Jialong Li is an Assistant Professor (non-tenure-track) at the Waseda Institute for Advanced Study. His research focuses on dynamic responsibility allocation in human-software collaboration, with applications in autonomous driving, robotics, and adaptive systems. He employs techniques such as discrete controller synthesis and large language models to address runtime environmental changes. Key research themes: human-robot collaboration, self-adaptive software, autonomous systems Technical approaches: Discrete Controller Synthesis, LLM integration, reinforcement learning Recent publications emphasize multimodal human-AI collaboration, prompt engineering for software development, and ethical considerations in adaptive systems. His work bridges theoretical modeling (e.g., requirements analysis, stochastic control) with real-world applications like warehouse robotics and color-blind accessibility tools. While no formal awards are listed, his research has been presented at top conferences in software engineering and autonomous systems.

• High Performance Computing
• Entertainment and Game Informatics
• Human Interface and Interaction
• +۳ مورد دیگر

Dr. Tsukasa Fukusato is an Assistant Professor at the School of Fundamental Science and Engineering , Waseda University since April 2023. His work spans Human Interface and Interaction , Entertainment Informatics , and High-Performance Computing , with a focus on interactive systems for digital art and animation. Current Research: Developing interactive tools for 2D/3D animation, workflow systems in bioinformatics, and AI-assisted artistic creation Technical Expertise: Latent diffusion models, motion segmentation, sketch-based interfaces, garment transfer, and aerodynamic design His recent publications (2022-2024) demonstrate advancements in: Animation and motion design (15+ papers) Workflow execution services AI-guided facial synthesis Interactive garment/textile modeling Biomechanical simulation systems Visual language interfaces Scientific Awards: 2024 Best Poster Award (NICOGRAPH) 2023 Honorable Mention (Computational Visual Media) Multiple Best Paper/Poster awards (2014-2023) 2014 Nishida Award from the Institute of Image Information and Television Engineers of Japan Teaching Activities (2025): Lecturer for Computer Graphics, Media Science, and Project-Based Learning Supervising graduation theses and advanced digital media projects

• Quantum Computing
• Geospatial Information Processing
• Text Mining

Siya BAO is an Assistant Professor at Waseda University's Faculty of Science and Engineering, focusing on quantum computing applications in combinatorial optimization and geospatial information processing. Currently affiliated with the Green Computing Systems Research Organization, her work bridges theoretical computer science with practical implementations in travel planning, indoor localization, and financial forecasting. Key research interests include: Quantum Computing Geospatial Information Processing Text Mining Based on 15 recent publications, her research trajectory demonstrates: Quantum annealing solutions for multi-day trip planning Machine learning applications in financial time series analysis Advancements in smartphone-based pedestrian dead reckoning Innovations in QUBO model formulation for constrained optimization Scientific recognition includes: DICOMO 2023 Outstanding Paper Award IEEE ICSC 2020 Best Student Opponent 2017 Telecommunications Advancement Foundation Travel Aid Research activities span: Principal investigator for JSPS-funded geospatial optimization projects (2021-2024, 2024-2027) Contributing author to Springer's 'Machine Learning for Indoor Localization and Navigation' (2023) Extensive conference presentation history including IPSJ-ONE 2024 invited talk on quantum computing applications

• Natural Language Processing
• Automated Text Summarization
• Computer Assisted Language Learning
• +۶ مورد دیگر

Professor Manabu Okumura is affiliated with the Advanced Information Processing Division at Tokyo Institute of Technology, leading the Precision and Intelligence Laboratory. His research focuses on natural language processing (NLP), automated text summarization, and speech dialogue systems, emphasizing real-time, user-friendly interaction. Key areas include incremental language understanding, robustness in ill-formed input analysis, and semi-automatic lexical acquisition. His work addresses challenges like syntactic-semantic integration using case frame analysis, ellipse resolution in Japanese, and associative lexical relations extraction from corpora. Research projects include communication assistive technologies for disabled individuals and natural language-driven animation control. Publications span foundational NLP topics such as word sense disambiguation via semantic networks, zero pronoun resolution using centering theory, and incremental discourse processing. The lab collaborates on bilingual corpus analysis for lexicon development and maintains a focus on practical applications of theoretical advances.

• Social Psychology
• Industrial and Organizational Psychology
• Organizational Behavior
• +۵ مورد دیگر

Toshio Murase is an Associate Professor at the School of Commerce, Waseda University, where he has taught Organizational Behavior and related courses since 2017. His academic journey includes postdoctoral research at Northwestern University's Engineering Department and Georgia Institute of Technology's School of Psychology, followed by an Assistant Professor role at Roosevelt University's Psychology Department. Ph.D. in Industrial Organizational Psychology (2011), University of Central Florida M.S. in Psychology (2006), California State University, San Bernardino M.A. in Psychology with sociology minor (2002), California State University, Stanislaus His research spans Social Psychology , Industrial Organizational Psychology , and Organizational Behavior , focusing on team cognition, multiteam systems, and network analysis. Recent work examines cognitive versatility in hospital teams and cross-functional team dynamics through scale development. Key contributions include pre-publication replication frameworks and behavioral sequence analysis for team processes. He has received multiple awards, including the 2015 NCA Top Paper Award and 2008 UCF Social Sciences Award. 2024–2028: JSPS Grant on Innovation Processes and Prohibitive Voice 2018–2023: JSPS Grant on Shared Cognition and Leadership 2018–2020: Special Research Project on Cognitive Gaps in Organizations As a concurrent researcher at Waseda's Research Institute of Business Administration, he explores leadership mechanisms for inter-departmental collaboration and psychological safety in nursing education.

Qi Fengمشاهده پروفایل

استادیار

• Deep Learning
• Computer Graphics
• Computer Vision
• +۵ مورد دیگر

Qi Feng is an Assistant Professor at the Faculty of Science and Engineering, Waseda University, specializing in deep learning applications for computer graphics and vision, with a focus on virtual and augmented reality. He holds a Doctor of Engineering (2022), Master of Engineering (2019), and Bachelor of Engineering (2017) from Waseda University. Research Interests: His work spans 3D reconstruction, depth estimation, occlusion handling, and multimodal systems integrating eye tracking and speech recognition. Notable projects include SyncViolinist for audio-driven motion generation and the Depth360 dataset for omnidirectional imaging. Publications: Qi's research has been featured in top conferences like CHI, ISMR, ICCVW, and journals such as The Visual Computer. His articles emphasize practical solutions for immersive environments, language learning, and synchronized audio-visual editing. Contact: Email: fengqi@ruri.waseda.jp

• Intelligent Machine
• Human Symbiotic Humanoid Robot
• Anthropomorphic Robotic Hand
• +۵ مورد دیگر

Hiroyasu Iwata is Professor at Waseda University's Faculty of Science and Engineering, School of Creative Science and Engineering. He serves as Director of the Frontier Mechanical Engineering Research Institute and Director of Global Robot Academia Institute. Holding a Dr. Engineering degree from Waseda University, his research spans intelligent machines, medical robotics, and rehabilitation engineering, with over 256 publications and an h-index of 22. His research focuses on human-robot symbiosis with emphasis on humanoid robotics, tactile perception, and medical applications. Iwata develops systems for rehabilitation, tele-operated medical procedures, and human-coordinated machine systems that enhance human capabilities. His recent work explores VR applications for cognitive rehabilitation, particularly for stroke patients with spatial neglect, and human augmentation through supernumerary robotic limbs. Iwata's publications reveal strong interdisciplinary trends across medical robotics, virtual reality applications, and human augmentation technologies. His research bridges engineering and medical fields with particular focus on stroke rehabilitation, echocardiography robotics, and VR training systems for cognitive and physical rehabilitation. Best Paper Award, Robotics Society of Japan (2018) Multiple Outstanding Presentation Awards from Society of Instrument and Control Engineers (2017) Grand Prize, System Control Fair 2017 Executive Committee (2017) The Young Scientists' Prize from Minister of Education, Culture, Sports, Science and Technology (2009) Distinguished Achievement Award from Waseda University (2007) Iwata actively collaborates with medical institutions including Nippon Medical School through joint symposia on medical-science-engineering collaboration. His laboratory conducts research on robotic echocardiography, VR rehabilitation systems, and supernumerary robotic limbs, securing funding for projects that translate engineering innovations into medical applications. He directs the Frontier Mechanical Engineering Research Institute and Global Robot Academia Institute at Waseda University, fostering interdisciplinary collaboration between engineering and medical fields. Through the Nippon Medical School and Waseda University Joint Symposium series, his work promotes the integration of robotics, medicine, and engineering for clinical applications.

• Computational linguistics
• Hesitation phenomena
• Fluency
• +۵ مورد دیگر

Ralph Leon Rose is an Associate Professor at Waseda University's Faculty of Science and Engineering, specializing in computational linguistics and second language acquisition. Holding a Ph.D. in Linguistics from Northwestern University (2005), his career spans over 30 years in language education across Japanese institutions including Gunma Prefectural Women's University and Notre Dame Seishin Women's Junior College. His research focuses on hesitation phenomena , speech fluency measurement , and computer-assisted language learning . Recent work analyzes filled pauses across languages, develops AI-powered vocabulary assessment tools (VocQGen), and investigates ethical implications of disfluencies in AI speech. His publications reveal consistent exploration of how temporal speech variables affect second language perception and production. AY2018 e-Teaching Award from Waseda University Cognitive Science Fellow at Northwestern University Rose leads multiple research projects including Automatic generation of vocabulary quiz items and Modeling speech fluency for e-learning . His lab develops practical tools like Fluidity (real-time fluency feedback), JESPR (self-paced reading tasks), and the Crosslinguistic Corpus of Hesitation Phenomena . As an active member of ISCA, IEEE, and EUROCALL, he contributes to shaping ethical standards in AI speech applications while maintaining strong industry connections through regular media appearances and conference keynotes.