جست‌وجوی استاد و پژوهشگر

Jürgen Kurtzمشاهده پروفایل

استاد

• Teaching English as a Foreign Language (TEFL)
• Creativity and Improvisation in Education
• EFL Textbook Analysis and Development
• +۷ مورد دیگر

Jürgen Kurtz is a full Professor of Teaching English as a Foreign Language (TEFL) at Justus Liebig University Giessen since 2011, after holding a full professorship at Karlsruhe University of Education (2001-2011). He served as chair of the English department at JLU Giessen (2013-2015) and has been a visiting professor at Saint Mary’s University (Halifax, Canada). His work bridges theory and practice in EFL education. Education: Dr. phil. in Cognitive Psychology/First Language Acquisition (1989, summa cum laude), Habilitation in TEFL (2000) Research Focus : Improvisation and creativity in structured EFL learning environments Textbook analysis, development, and digital innovation Hybrid learning models for pre-service EFL teacher education Standards-based instruction and neoliberal critiques in language education Publications & Editorial Work : Author of books and articles on EFL pedagogy, textbook use, and digital learning. Speaker of the editorial board for Gießener Beiträge zur Fremdsprachendidaktik (since 2013), overseeing over 50 publications in the series. Professional Contributions : Founder of the TEFLhybrid@JLU project, developer of innovative EFL courses, and active in in-service teacher training through The English Academy (TEA) . His work explores augmented reality applications and critical approaches to textbook use.

Ivo Steiningerمشاهده پروفایل

استاد

• Foreign Language Education
• Literary Competence Development
• Teacher Professionalization
• +۳ مورد دیگر

Prof. Ivo Steininger serves as Professor of Teaching Anglophone Literatures and Cultures at Justus Liebig University Giessen, Germany. He heads the Department of English – Teaching Anglophone Literatures and Cultures and maintains an active research profile in foreign language pedagogy. His academic journey includes state examinations for teaching (2007, 2012), a summa cum laude doctorate (2013), and interim professorships at the University of Paderborn (2016–2018) and Giessen (2019–2021). In 2024, he was a visiting scholar at Saint Mary’s University, Canada. Research focuses include: Literary text comprehension in EFL contexts Digitalization and sustainability in language education Teacher professionalization processes Anglophone cultural representations in media His work bridges theoretical frameworks with classroom applications, emphasizing multimodal literacy and critical cultural awareness. Publications demonstrate strong trends in: Digital pedagogy and critical media analysis (2020–2025) Sustainability integration in curricula (2023–2024) Teacher development research (2018–2021) Multimodal literary interpretation (2018–2025) Awards and projects: Piepho-Prize (2015) for advancing foreign language education research Current projects: Second-phase teacher training, ambiguity in picture books, and Education for Sustainable Development (ESD) in EFL

Stefan Blügelمشاهده پروفایل

استاد

• Theoretical Condensed Matter Physics
• Electronic Structure Theory
• Density Functional Theory (DFT)
• +۱۲ مورد دیگر

Stefan Blügel is a Professor of Theoretical Physics at RWTH Aachen University and a leading scientific staff member at the Peter Grünberg Institute (PGI-1), Forschungszentrum Jülich. His research focuses on the electronic properties of solids, quantum materials, spintronics, and advanced computational methods in condensed matter physics. He plays a central role in developing and applying density-functional theory (DFT) to complex magnetic and topological systems. His research interests lie at the intersection of theoretical physics and materials science, particularly in magnetism at surfaces and interfaces , spin-orbit coupling phenomena , topological spin textures such as skyrmions and Hopfions, and electronic structure methods . He has pioneered the understanding of the Dzyaloshinskii-Moriya interaction at interfaces, enabling the discovery of chiral domain walls and skyrmion lattices. His work underpins key advances in spintronics, including spin-orbit torque and terahertz generation. He is also active in emerging fields like orbitronics and cryo-spintronics, and continues to innovate in many-body theory and spectral DFT. The body of his recent publications reveals a strong focus on topological quantum materials , 2D magnetism , spin dynamics , and first-principles modeling of novel physical phenomena . His work consistently bridges fundamental theory with experimental relevance, especially in the context of next-generation memory and computing devices. Stefan Blügel has made foundational contributions to computational materials science, including the development of constraint DFT and key implementations in the FLEUR code. He has advised numerous researchers and led major collaborative projects in theoretical condensed matter physics. His group leverages high-performance computing for simulating complex quantum systems, and he is deeply involved in advancing electronic structure methodologies. He leads research at the Quantum Theory of Materials (PGI-1) division, which is part of the interdisciplinary Peter Grünberg Institute, known for its cutting-edge work in nanoelectronics, quantum materials, and spintronics. The institute fosters strong collaboration between Forschungszentrum Jülich and RWTH Aachen University, where Blügel holds a joint professorship.

Gyunam Parkمشاهده پروفایل

پژوهشگر

• Process Mining
• Action-Oriented Process Mining
• Object-Centric Process Analysis
• +۱۲ مورد دیگر

Gyunam Park is a Research Group Lead and Process and Data Scientist at Fraunhofer FIT and a Scientific Assistant at the Chair of Process and Data Science at RWTH Aachen University, a leading institution in computer science and engineering. He is actively involved in both research and teaching, contributing to the advancement of process mining, data science, and artificial intelligence. His work bridges academic research and industrial applications, particularly in SAP ERP systems and digital twins of organizations. Research Interests: Gyunam Park’s research focuses on Action-Oriented Process Mining (AOPM) , Object-Centric Process Analysis , and Responsible Machine Learning . He aims to transform process mining insights into actionable management decisions, ensuring transparency, fairness, and compliance. His work enables organizations to monitor operational constraints, generate corrective actions, and assess their impact using data-driven methods. Publication Trends: His recent publications emphasize object-centric approaches to process mining, predictive monitoring, constraint checking, and integration with AI planning. There is a strong trend toward preserving structural information in event logs, improving machine learning performance, and applying these techniques to real-world systems like SAP ERP and after-sales service processes. Scientific Awards: No awards are explicitly mentioned in the provided text. Advising and Grants: While no formal students are listed, Gyunam Park leads research projects and collaborates with industry partners such as Samsung Electronics and SAP. His projects involve root cause analysis, resource optimization, and educational data mining. He has developed open-source tools like ProAct and OCPA , indicating active grant or institutional support for software development and research dissemination. Labs and Teams: He is a core member of the Process and Data Science (PADS) group led by Prof. Wil van der Aalst at RWTH Aachen University and leads a research group at Fraunhofer FIT. These teams focus on cutting-edge research in process mining, data science, and AI, with strong industry collaborations and regular contributions to top conferences and journals.

Philip Nakashimaمشاهده پروفایل

دانشیار

• Transmission Electron Microscopy
• Quantitative Convergent-Beam Electron Diffraction
• Electron Crystallography
• +۱۵ مورد دیگر

Philip Nakashima is an Associate Professor in the Department of Materials Science & Engineering within the Faculty of Engineering at Monash University. He is an active researcher with a PhD in Physics from the University of Western Australia (2002) and has over 25 years of experience in advanced transmission electron microscopy (TEM) and quantitative convergent-beam electron diffraction (QCBED). He is currently accepting PhD students and is involved in cutting-edge research in materials characterization and quantum information technology. His research focuses on the development and application of advanced electron microscopy techniques to study the structure, bonding, and properties of materials such as metals, alloys, ceramics, and nanostructures. Key areas include quantitative CBED, electron crystallography, digital image restoration, noise quantification, and multi-parameter optimization. He has made seminal contributions to understanding chemical bonding in aluminum and has extensive experience in high-performance computing for materials analysis. His most recent publications demonstrate a strong trend toward integrating machine learning with materials design, particularly for magnesium alloys, while maintaining core expertise in electron diffraction and microscopy. He continues to publish in high-impact journals such as Science , Physical Review Letters , and Acta Materialia . Philip Nakashima has received several prestigious awards for his research excellence: John Sanders Medal (2012) : Awarded by the Australian Microscopy and Microanalysis Society for excellence in electron microscopy techniques. Barry Inglis Medal (2011) : Awarded by Australia’s National Measurement Institute for outstanding achievement in measurement research. The Cowley-Moodie Award (2006) : Recognizing research excellence in electron microscopy in the physical sciences. He has been a visiting researcher at the ARC Future Fellowship (2012–2016) and is currently an Associate Investigator in the Quantum Information Technology project (2023–2027). He teaches advanced crystallography to undergraduate and postgraduate students and has been invited to lecture at international schools on electron and quantum crystallography. His research involves collaboration with leading scientists in Australia and internationally, and he leads work on advanced microscopy for materials engineering applications.

Mats Küssnerمشاهده پروفایل

پژوهشگر

• Multimodal perception of music
• Music and mental imagery
• 4E music cognition
• +۳ مورد دیگر

Mats Küssner is a Researcher at Humboldt University of Berlin's Department of Musicology, specializing in Transcultural Musicology and Historical Anthropology of Music. Previously, he held a Peter Sowerby Research Associate position at the Royal College of Music in London. He earned his doctorate from King's College London, focusing on cross-modal mappings between sound and visual forms. His work bridges music psychology, cognitive science, and cultural studies, emphasizing how music shapes human thought and emotion through multi-method approaches. Research interests include multimodal perception, music-induced mental imagery, 4E cognition (embodied/embedded/enactive/extended), and performance science. Notable awards include the Aubrey Hickman Award for music psychology research and a teaching excellence award. He teaches courses like 'Diversity in Berlin's Sound Scene' and 'Emotions in Music' at both BA and MA levels. His publications span over 40 peer-reviewed articles across journals like Music & Science , Psychomusicology , and Frontiers in Psychology , with a focus on visual-aural interplay, music cognition disorders (e.g., aphantasia), and cross-cultural performance dynamics. He co-edited the landmark volume Music and Mental Imagery (Routledge, 2022). Recent work explores environmental ecomusicology education and music's role in mitigating social isolation. Küssner leads projects on music-induced emotion prediction using cross-modal correspondences and is part of Berlin's interdisciplinary music psychology scene, collaborating with neuroscientists and cultural anthropologists. His lab employs eye-tracking, EEG, and behavioral experiments to study embodied music cognition processes.

Shlomo Dubnovمشاهده پروفایل

استاد

• Music Technology
• Audio Signal Processing
• Machine Learning for Audio
• +۳ مورد دیگر

Shlomo Dubnov is a Professor in the Department of Music at the University of California, San Diego. With an h-index of 36 and over 4,803 citations, his research spans the intersection of music, audio processing, and machine learning, making significant contributions to music information retrieval, sound synthesis, and speech recognition technologies. Dr. Dubnov's primary research interests focus on Music Technology and Audio Signal Processing , with particular expertise in: Machine learning applications for music and audio analysis Sound texture synthesis and modeling Music improvisation systems and computational creativity Audio adversarial examples and security Pitch tracking in noisy environments Multimodal learning for audio-text alignment His recent work demonstrates a strong trend toward applying transformer architectures and contrastive learning techniques to audio processing tasks, with publications in top conferences like IEEE International Conference on Acoustics, Speech, and Language Processing. Dr. Dubnov's research bridges theoretical music concepts with practical audio engineering applications, creating innovative solutions for music generation, analysis, and security. Dr. Dubnov has established productive collaborations with researchers across disciplines, particularly with: G. Assayag (102 Publications • 2,475 Citations) - music technology and improvisation systems Taylor Berg-Kirkpatrick (31 Publications • 1,459 Citations) - machine learning applications K. Chen (18 Publications • 1,150 Citations) - audio transformer models Cheng-i Wang (21 Publications • 305 Citations) - music information retrieval His work is supported by grants focused on advancing the state-of-the-art in music technology, audio processing, and machine learning applications for creative domains. Dr. Dubnov leads research in the Music Technology laboratory at UC San Diego, where his team develops innovative systems for music analysis, synthesis, and human-computer interaction in musical contexts. The lab focuses on creating intelligent systems that can understand, generate, and interact with musical content in real-time applications.

• Sports Management
• Digital Transformation in Sports
• Sports Entrepreneurship
• +۷ مورد دیگر

Sascha L. Schmidt is a Professor and Chairholder at WHU – Otto Beisheim School of Management, where he leads the Center for Sports and Management (CSM). He is also the Academic Director of the European Sports Business Program and holds affiliations with the Massachusetts Institute of Technology (MIT) and Harvard Business School. His work bridges academic research and practical application in sports and management. WHU – Otto Beisheim School of Management, Chair for Sports and Management Academic Director, European Sports Business Program Lecturer, MIT Sports Entrepreneurship Bootcamp Member, Digital Initiative, Harvard Business School Schmidt’s research centers on the future of sports, with a focus on digital transformation, technology adoption, fan engagement, and strategic innovation in professional sports. His interdisciplinary work integrates insights from economics, psychology, and management to understand how emerging technologies are reshaping the sports industry. He has led multiple Delphi studies forecasting the future of football, winter sports, and sports sponsorship. His recent publications span topics including the metaverse in football, digital transformation in national associations, and eSports strategy. These works, published in journals like Technological Forecasting and Social Change and MIT Sloan Management Review , reflect a strong trend toward technology-driven change and data-informed decision-making in sports. His research often employs foresight methodologies and behavioral insights. Schmidt has made significant contributions beyond traditional academia. He is the editor of 21st Century Sports and developed an online course with MIT xPRO. He also contributes regular columns to Focus and Manager Magazin , translating academic insights for a broader audience. Editor, 21th Century Sports: How Technologies Will Change Sports in The Digital Age Co-developer, MIT xPRO course: Transformational Technologies: Applied Lessons from Sports Author of multiple WHU CSM Delphi studies and industry reports Schmidt advises on strategic initiatives and has collaborated with major sports organizations. His work with Harvard Business School on case studies—such as Bayern Munich in China and TSG Hoffenheim’s analytics revolution—highlights his impact on teaching and real-world strategy. He is actively involved in research funding and collaborative projects, though specific grants are not detailed. He leads the Center for Sports and Management at WHU, which serves as a hub for research, industry collaboration, and executive education in sports business. The center produces influential studies and fosters innovation in sports management practices.

• Information Retrieval
• Digital Libraries
• Informetrics
• +۵ مورد دیگر

Philipp Mayr-Schlegel is a Professor at the University of Göttingen’s Institute of Computer Science, leading the team 'Information & Data Retrieval' at GESIS - Leibniz-Institute for the Social Sciences. His research focuses on interactive information retrieval systems, scholarly recommendation mechanisms, and the integration of bibliometric methods with digital library technologies. University of Göttingen - Institute of Computer Science GESIS - Leibniz-Institute for the Social Sciences His work spans information retrieval , digital libraries , and applied informetrics , with particular emphasis on: Interactive search systems Non-textual ranking algorithms Scholarly document processing Knowledge representation Semantic search technologies User behavior analysis Recent research outputs (2025) include studies on LLMs for scholarly search, bibliometric reproducibility tools, scientific uncertainty annotation, and preprint adoption disparities. He has published extensively in Scientometrics , International Journal on Digital Libraries , and top conference proceedings like ACL and ECIR . As organizer of the International Workshop on Bibliometric-enhanced Information Retrieval (BIR) and Scholarly Document Processing (SDP) series, he has shaped academic discourse through editorial roles at ISSI , JCDL , and SocInfo conferences. His projects have attracted significant national and European funding.

• Information Retrieval
• Large Language Models
• Evaluation Methodologies
• +۳ مورد دیگر

Charles L. A. Clarke is a Professor at the University of Waterloo, Canada, with a focus on Information Retrieval and Large Language Model evaluation . He actively contributes to research in search algorithms, human-computer interaction, and computational linguistics. Recent Research Trends : His work examines LLM limitations in relevance assessment, adversarial robustness in legal domains, and hybrid human-AI evaluation frameworks. Workshop Leadership : Co-organizer of the Search Futures Workshop (ECIR 2024/2025) and LLM4Eval@SIGIR. Collaborations : Works with researchers from NII, Microsoft, and ACM SIGIR on testbed development and evaluation methodologies. Key Article Trends : His 2024-2025 publications analyze LLM vulnerabilities, develop evidence retrieval systems, and create metrics for human-AI alignment in generative applications. Subfields include adversarial attacks, prompt sensitivity, and semantic graph frameworks. Scientific Contributions : Focuses on bridging algorithmic performance with human judgment validity, emphasizing ethical AI deployment and robust information access systems.

• Database Systems
• Data Mining
• Social Network Analysis
• +۳ مورد دیگر

Eric Leclercq is a researcher at the University of Burgundy, affiliated with the LE2I Lab in Dijon, France. His work spans database systems, social network analysis, and biomedical data integration. He has contributed extensively to polystore systems, tensor decompositions, and category theory applications in data modeling. Fields of Interest : Database Systems, Data Mining, Social Network Analysis, Big Data Analytics, Semantic Web Leclercq's recent research focuses on formal frameworks for data lakes using category theory, multi-level tensor decomposition for social network stratification, and schema migration in multi-model systems. He has published in venues like CAiSE, IDEAS, and RCIS. His collaborations include Annabelle Gillet, Marinette Savonnet, and Nadine Cullot. Notable works include Lambda+ architecture for data processing, polarization analysis in social networks, and tools for tweet collection and biomedical data integration.

• Software Performance Engineering
• Microservice Architectures
• Cyber-Physical Systems
• +۳ مورد دیگر

Catia Trubiani is a faculty member at the Gran Sasso Science Institute in L'Aquila, Italy, specializing in software performance engineering, architectural analysis, and cyber-physical systems. Her work bridges theoretical modeling with practical applications, focusing on performance antipatterns, uncertainty quantification, and DevOps practices. In research , she explores performance modeling of microservices, federated learning systems, and cyber-physical systems, with a strong emphasis on architectural decision-making under uncertainty. Her recent articles analyze performance regression testing, aging detection in networks, and anti-pattern correlation in distributed systems, reflecting her interest in robust, scalable software solutions. She collaborates extensively with researchers like Raffaela Mirandola , Alberto Avritzer , and Riccardo Pinciroli , contributing to tools and frameworks such as PLUS (Performance Learning for Uncertainty of Software) and VisArch (Visualisation of Performance-Based Architectural Refactorings). Her work has been published in journals including IEEE Transactions on Software Engineering and Future Generation Computer Systems , as well as conferences like ICSE, ECSA, and ICPE.

• Database Systems
• Information Retrieval
• Probabilistic Databases
• +۴ مورد دیگر

Martin Theobald is a Professor in the Department of Computer Science at the University of Luxembourg's Faculty of Science, Technology and Communications. Previously affiliated with University of Ulm, Germany, his research spans database systems, information retrieval, and knowledge extraction with over 120 publications since 2002. His work bridges theoretical database foundations with practical applications in large-scale data processing. His research focuses on: Probabilistic and uncertain database systems Stream processing frameworks (notably the AIR architecture) Knowledge extraction from heterogeneous data sources Integration of machine learning with database systems Efficient query processing for structured and semi-structured data Recent publications demonstrate an evolving research trajectory toward real-time data stream processing with machine learning integration. His work on the AIR (Asynchronous Iterative Routing) framework and its extensions (TensAIR, OPTWIN) addresses critical challenges in concept drift detection, neural network training on streaming data, and efficient resource utilization. These contributions sit at the intersection of database systems, distributed computing, and machine learning, with applications in knowledge graph construction and question answering systems. Martin Theobald has mentored numerous researchers including Mauro Dalle Lucca Tosi, Alessandro Temperoni, and Vinu E. Venugopal, who have become active contributors to the database community. His collaborative network spans institutions across Europe, with frequent partnerships with researchers from University of Ulm, Max Planck Institute, and other European universities. His laboratory work focuses on developing scalable systems for processing evolving data streams, with particular emphasis on creating lightweight architectures that maintain high performance while minimizing resource consumption. Current projects involve integrating knowledge graphs with real-time analytics and developing adaptive systems that can handle concept drift in streaming environments.

Wolfgang Maennigمشاهده پروفایل

استاد

• Economic Policy
• Real Estate and Urban Economics
• Sport Economics
• +۱ مورد دیگر

Prof. Dr. Wolfgang Maennig holds the Professorship of Economics at the University of Hamburg , Faculty of Business, Economics and Social Sciences. His work focuses on Sport Economics , Real Estate and Urban Economics , and Transport Economics , with extensive media engagement on Olympic Games impacts, urban policy, and sports governance. Affiliations : Department of Economics, University of Hamburg Research Themes : Olympic legacy, urban mobility, real estate markets, mega-event economics Research Trends from 2023-2025 highlight his analysis of Olympic Games' political effects, corporate governance impacts, and transportation policy. Notable publications include Centralization in high-performance sports and Olympic Games and democracy . Public Engagement : Regular media contributor on Hamburg Contemporary Economic Discussion Papers , with 30+ interviews on Olympic economics, housing markets, and urban development (e.g., NDR , rbb , Der SPIEGEL ).

Roderich Großمشاهده پروفایل

استاد

• swarm robotics
• multi-robot-systems
• modular and reconfigurable robotics
• +۱ مورد دیگر

Professor Roderich Groß is a faculty member at Technical University of Darmstadt, where he serves as Head of the RCPS Lab (Robotics, Control, and Physical Systems Laboratory). His extensive research career spans over two decades with publications dating back to 2006, establishing him as a leading figure in swarm robotics. His work appears in top-tier robotics journals including IEEE Transactions on Robotics, Nature Communications, and The International Journal of Robotics Research. Professor Groß's research focuses on swarm robotics, multi-robot systems, modular and reconfigurable robotics, and human-robot interaction. His work explores how groups of relatively simple robots can collectively perform complex tasks through decentralized control mechanisms. He investigates modular systems that can adapt their physical structure to different tasks and develops human-robot interaction paradigms that enable effective collaboration between humans and robot swarms. His research has practical applications in search and rescue, environmental monitoring, construction, and industrial automation. Analysis of Professor Groß's recent publications reveals a clear evolution from foundational swarm behaviors toward increasingly sophisticated applications. His work addresses critical challenges including energy management in robot swarms (CapBot), multi-operator control interfaces, heterogeneous systems for industrial applications, and bio-inspired collective behaviors. His research bridges theoretical swarm intelligence principles with practical implementation on physical robot platforms like Kilobots, with recent work integrating artificial intelligence techniques such as language models for swarm control. As Head of the RCPS Lab, Professor Groß leads a productive research group with extensive international collaborations. The lab works with various robot platforms focusing on both theoretical modeling and practical implementation of swarm behaviors, contributing significantly to advancing the field of swarm robotics from theoretical foundations to real-world applications.