جستجوی استاد راهنمای دانشگاهی

• Organizational Economics
• Theory of the Firm
• Corporate Governance
• +۴ مورد دیگر

Prof. Dr. rer. pol. Bernd Frick is a full Professor of Economics at the University of Paderborn , Faculty of Business Administration and Economics, where he heads the Department of Economics – Institute Department 1: Management. Active and born in 1959, he is based in Paderborn, Germany, and his research spans Organizational Economics , Corporate Governance , Personnel Economics , Law & Economics , and Sports & Cultural Economics . Education & Academic Focus: Although specific degrees are not listed, his title "Dr. rer. pol." (Doctor of Economics and Social Sciences) indicates advanced training in economics. His work integrates microeconomic theory with empirical analysis, focusing on labor markets, firm governance, and the economics of professional sports. Research Interests: Organizational Economics & Theory of the Firm: Analyzing internal labor markets, co-determination, and governance structures. Personnel Economics & Labor Policy: Examining incentive systems, wage determination, and employment practices. Sports Economics: Extensive studies on player remuneration, coaching careers, doping, and the economic impact of regulations like the Bosman ruling. Law & Economics: Evaluating the economic effects of legal frameworks, including disability employment laws and co-determination statutes. Cultural Economics: Investigating art markets, reputation, and value creation in creative industries. Publication Trends: Over 100 peer-reviewed articles and monographs reveal a consistent focus on empirical sports economics (e.g., Bundesliga performance, marathon incentives), labor market institutions (works councils, co-determination), and governance issues. Recent work explores gender competitiveness in athletics and the longevity of coaching careers under performance pressure. Scientific Awards & Honors: While no major named awards are listed, his extensive publication record, editorship of academic volumes (e.g., Economics of Grassroots Sports ), and frequent policy-oriented commentary establish him as a leading voice in applied economics. Advising & Grants: Details on specific doctoral students or funded projects are not provided, but his role as editor, co-author with international scholars (e.g., Robert Simmons, Joachim Prinz), and policy consultant (e.g., Federal Ministry of Labour) imply active supervision and grant involvement. Labs & Teams: While no dedicated lab is mentioned, his institutional affiliation with the Institute Department 1: Management suggests collaboration within a multidisciplinary team of economists and management scholars at Paderborn.

Tassilo Pellegriniمشاهده پروفایل

استاد

• Semantic Web
• Linked Data
• Digital Business
• +۴ مورد دیگر

FH-Prof. Mag. Dr. Tassilo Pellegrini is a Professor at the University of Applied Sciences St. Pölten , leading the Institute for Innovation Systems within the Department of Digital Business and Innovation . His work bridges semantic technologies with digital business strategies. Education : Business Economics, Communication Studies, Political Science Research Focus : Semantic Web, Linked Data, Digital Media Economics, Network Neutrality, Data Licensing His publications highlight trends in Semantic Metadata for news production, Linked Data Integration , and Cloud-based Business Models under network neutrality constraints. Recent work explores thesaurus-driven knowledge organization and the economic implications of Big Data. Scientific Awards : Best Paper Award at I-Semantics 2012 Key Projects : ECO-TCO (Digital Data for Sustainability), Corporate Semantic Web initiatives Contact: tassilo.pellegrini@fhstp.ac.at

Florian Diekertمشاهده پروفایل

استاد

• Environmental Economics
• Resource Economics
• Socio-ecological Systems
• +۷ مورد دیگر

Professor Florian Diekert is a Professor of Environmental Economics at the University of Augsburg's Faculty of Business and Economics and a member of the Centre for Climate Resilience. He leads the Environmental Economics Lab, which focuses on designing, analyzing and testing strategies for sustainable and resilient development, with particular emphasis on socio-ecological systems under pressure and group decisions under strategic and natural uncertainty. Professor Diekert received his education from the Technical University Dresden (International Relations) and the University of Oslo (MPhil in Economics, PhD in Economics in 2011). His research employs economic experiments, theoretical modeling, and statistical analysis, often in interdisciplinary collaborations with natural scientists. Prior to joining the University of Augsburg in 2023, he was a Junior Professor in Heidelberg and conducted research visits at Columbia University and UC Santa Barbara. His research spans Environmental Economics , Resource Economics , and Behavioral Economics , with specific focus on socio-ecological systems, group decision-making under uncertainty, lab-in-the-field experiments, social norms, and early warning systems for ecological tipping points. His work integrates theoretical insights with practical applications for sustainable development policy, often through interdisciplinary collaborations with natural scientists. Professor Diekert's publication record reveals a consistent trajectory of high-impact research on climate resilience, fisheries management, and collective action problems. His recent work increasingly incorporates experimental methods to investigate how environmental conditions shape economic behavior across different cultural contexts (Chile, Norway, Tanzania), and how policy interventions can improve sustainability outcomes through behavioral insights. ERC Starting Grant 'NATCOOP' for research on how nature shapes preferences and incentives of economic agents and how this affects common-pool resource management Professor Diekert advises multiple doctoral students and leads a vibrant research team including postdoctoral researchers and doctoral candidates. His Environmental Economics Lab actively participates in major international conferences such as the Global Tipping Points Conference, Nordic Annual Environmental and Resource Economics Workshop, and European Association of Environmental and Resource Economists conference, demonstrating strong international engagement in his field. The Environmental Economics Lab at the University of Augsburg brings together economists, natural scientists, and policy experts to address pressing sustainability challenges through interdisciplinary research. The lab conducts both theoretical and experimental work, with field studies in various international contexts including Chile and Tanzania, and maintains strong connections with other research institutions across Europe and beyond.

Frederik Stalschusمشاهده پروفایل

پژوهشگر

• Bayesian Learning
• Bayesian Optimization
• Uncertainty Estimation
• +۱ مورد دیگر

Frederik Stalschus is a doctoral researcher and full-time academic affiliated with the Technical University of Berlin and the Berlin Institute for the Foundations of Learning and Data (BIFOLD) . Since 2025, he has pursued his PhD in the Machine Learning Group under the supervision of Shinichi Nakajima, focusing on Bayesian learning and uncertainty-driven optimization for real-world applications. Education : M.Sc. in Information Systems (2025), TU Berlin Industry Experience : Adaptive multi-model reinforcement learning at IBM, cloud engineering observability at SAP His research interests include Bayesian learning , uncertainty estimation , and probabilistic machine learning , with a specific emphasis on enhancing Bayesian optimization techniques through uncertainty modeling. His work bridges theoretical advancements with practical implementations in data science and cloud systems.

• Case-Based Reasoning (CBR)
• Artificial Intelligence
• Multi-Agent Systems
• +۴ مورد دیگر

Dr. Pascal Reuss is a Researcher at the Intelligent Information Systems (IIS) Division within the Institute of Computer Science , University of Hildesheim . His work focuses on Case-Based Reasoning (CBR) systems, Multi-Agent Systems , and Knowledge Management applications. Active in CBR framework development and game-based AI research Teaching Computer Science III (Databases) for winter 2025/26 Participating in university sustainability initiatives like Stadtradeln 2024/25 Reuss contributes to AI education through practical implementations in gaming environments and has developed visualization tools for CBR agent behavior. His research spans multi-agent collaboration , dynamic case bases , and domain-specific language implementations for knowledge maintenance. Notable contributions include: Co-developing the FEATURE-TAK framework for knowledge extraction Designing case factories for distributed CBR systems Implementing finite state machines for tactical game agents Creating CBR-based fitness planning systems His work appears in various CBR and Game Development publications from 2011-2024. The research demonstrates practical applications of CBR in aircraft maintenance diagnostics , training plan generation , and educational technology contexts.

Barbara Namerمشاهده پروفایل

استاد مدعو

• Translational Pain Research
• Neurophysiology
• Peripheral Nervous System
• +۶ مورد دیگر

Barbara Namer is an Adjunct Professor at Friedrich-Alexander University Erlangen-Nuremberg and leads the IZKF-funded "Neuroscience: translational pain research" group at RWTH Aachen University Hospital. Her career spans 20+ years in neurophysiological pain research with clinical translations. Doctor of Medicine (2000-2004), Erlangen-Nuremberg Venia Legendi (Habilitation) in Physiology (2010) Adjunct Professor title (2018) Her research focuses on nociceptor mechanisms in diabetic neuropathy, migraine pathophysiology, and TRPA1 channel dynamics . Computational modeling and human microneurography techniques are central to her work. Key publication trends show expertise in peripheral nerve sensitization , diabetic pain mechanisms , translational pain modeling , and ion channel pharmacology . She has received multiple DGSS and German Neurology Society awards for her pain research. 2019 - DGSS Poster Award 2015 - DGSS Poster Award 2010 - EFIC Grünenthal Grant 2003 & 2018 - German Neurology Society Awards National and international collaborations include research stays in Norway and Sweden, with extensive grant funding from DFG and IZKF projects.

• Information Systems
• Databases
• Knowledge Graphs
• +۷ مورد دیگر

Stefan Decker is a full University Professor (Universitätsprofessor) at RWTH Aachen University, Germany, where he heads the Chair of Information Systems and Databases (Informatik 5) within the Faculty of Mathematics, Computer Science and Natural Sciences. He is actively involved in teaching, research, and the supervision of numerous ongoing and completed doctoral, master’s, and bachelor theses. Education & Academic Background Doctorate (Dr. rer. pol.) – field of Information Systems or related (exact institution/year not stated in text). Appointed as University Professor and Chair of Information Systems and Databases at RWTH Aachen University. Research Interests Prof. Decker’s work lies at the intersection of databases, knowledge graphs, semantic web technologies, data science, and cybersecurity . He investigates architectures and algorithms for large-scale, privacy-preserving, decentralized data analytics , develops ontology-driven information systems , and explores the use of large language models (LLMs) for educational technology, anomaly detection, and incident-response playbooks. Additional focal areas include smart energy systems, mixed-reality learning environments, FAIR data principles, and federated machine learning . Scientific Contributions & Trends His recent publications (2022-2025) demonstrate a clear trend toward explainable AI, LLM-enhanced systems, secure data spaces, and semantic interoperability . Key contributions include novel anomaly-detection frameworks for encrypted power-grid communications, knowledge-graph-driven chatbots for higher-education support, and methodological advances in decentralized analytics and FAIR data sharing. These works are disseminated in top-tier venues such as AAAI, IEEE ISGT Europe, ESWC, IDEAL, and various Springer LNCS and IEEE Transactions. Supervision & Grants Doctoral Theses Advised: A. T. Neumann – “Chatbots as professional companions in large-scale community information systems” (2024) S. M. Welten – “Methods for practical data sharing and decentralized analytics” (2025) Master’s Theses Co-Advised: A. R. Küsters – “Object-centric process constraints using variable bindings” (2025) Additionally supervising more than 30 ongoing bachelor, master, and doctoral projects covering topics such as LLM-driven cybersecurity playbooks, knowledge-graph construction for German law, privacy-preserving analytics in smart grids, and mixed-reality learning agents. Principal investigator or senior researcher in large collaborative projects including NFDI4DS, WestAI, champI4.0ns and several EU/national initiatives on sovereign data spaces and AI services. Labs & Teams Prof. Decker leads the Information Systems & Databases (DBIS) Research Group . The group operates well-equipped laboratories for knowledge-graph engineering, mixed-reality applications, privacy-enhancing technologies, and secure distributed analytics . Current team size exceeds 30 researchers including PhD candidates, postdocs, and scientific programmers, supported by national and EU funding streams.

Leif Kobbeltمشاهده پروفایل

استاد

• Computer Graphics
• Geometry Processing
• Interactive Visualization
• +۳ مورد دیگر

Leif Kobbelt serves as a University Professor at RWTH Aachen University, leading the Computer Graphics Group within the Department of Computer Science (Informatik 8). His research focuses on advancing geometry processing, interactive visualization, and computer graphics through innovative algorithmic solutions and interdisciplinary collaborations. Professor Kobbelt's research program centers on geometry acquisition and processing, with significant contributions to mesh generation, surface reconstruction, and neural rendering techniques. His work bridges theoretical geometry with practical applications in computer vision, photo-realistic image synthesis, and multimedia data transmission, often involving collaborations with industry partners and international research teams funded by DFG and EU sources. Recent publications (2023-2025) reveal a strategic integration of deep learning with traditional geometry processing, particularly in Gaussian splatting for real-time rendering, NeRF-based 4D content generation, and robust mesh Boolean operations. His group maintains leadership in quad mesh optimization and surface mapping while expanding into immersive visualization techniques for complex data analysis. The group has earned recognition through prestigious awards: Günter Enderle Best Paper Award at Eurographics 2023 Best Paper Award (1st place) at Symposium on Geometry Processing 2022 Honorable Mention for Best Paper at ACM Symposium on Virtual Reality Software and Technology Funding from Deutsche Forschungsgemeinschaft and European Union programs supports the group's research infrastructure and international collaborations. The team actively supervises graduate theses while developing open-source software tools that translate theoretical advances into practical industry applications, particularly in digital fabrication and immersive visualization systems. The Computer Graphics Group operates as a central hub for visual computing research at RWTH Aachen, maintaining strong ties with both academic institutions and technology companies. Their recent work on virtual reality educational tools and high-fidelity 3D reconstruction systems demonstrates commitment to knowledge transfer and real-world impact beyond traditional publication venues.

Dominique Unruhمشاهده پروفایل

استاد

• Quantum Computing
• Quantum Cryptography
• Post-Quantum Cryptography
• +۵ مورد دیگر

Dominique Unruh is a Professor at RWTH Aachen University , leading the Chair for Quantum Information Systems . Additionally, they hold a Professorship in Cryptography at the Institute of Computer Science of the University of Tartu , Estonia. Their research spans quantum computing , quantum cryptography , post-quantum cryptography , and formal verification of cryptographic protocols and programs. Research Focus : Quantum programs, zero-knowledge proofs, lattice-based cryptography, and quantum random oracle model. Key Contributions : Advancements in NTRU encryption efficiency, quantum Hoare logic, and rewinding techniques for security proofs. Tools : Active development in the EasyCrypt framework for cryptographic verification. Email : unruh@cs.rwth-aachen.de

• Machine Learning
• Control Systems
• Robotics
• +۳ مورد دیگر

Sebastian Trimpe is a Full Professor and Head of the Institute for Data Science in Mechanical Engineering at RWTH Aachen University, concurrently serving as Co-Executive Director of the RWTH Center for Artificial Intelligence since 2023. Previously, he led a Max Planck Research Group at the Max Planck Institute for Intelligent Systems from 2018 to 2022. His educational background includes: Ph.D. in Dynamic Systems and Control from ETH Zurich (2013) Dipl.-Ing. (M.Sc.) in Electrical Engineering from TU Hamburg (2007) MBA in Technology Management from TU Hamburg (2007) B.Sc. in General Engineering from TU Hamburg (2005) Professor Trimpe's research integrates machine learning with control theory to address safety and efficiency challenges in autonomous systems. His work spans theoretical frameworks for robust decision-making under uncertainty and practical implementations in robotics, with particular emphasis on event-triggered control, distributed systems, and data-efficient learning methodologies. Key contributions include novel approaches to safe reinforcement learning and model predictive control with guaranteed stability. Analysis of his recent publications reveals a pronounced focus on bridging machine learning with control engineering, especially in safety-critical robotics applications. Common themes include distribution-aware learning for medical diagnostics, diffusion-based control approximation, and hardware-in-the-loop validation of theoretical frameworks, demonstrating strong alignment between algorithmic innovation and real-world deployment. His scientific achievements have been recognized with prestigious honors: IFAC World Congress Interactive Paper Prize (2011) Klaus Tschira Award for public understanding of science (2014) Best Paper Award at International Conference on Cyber-Physical Systems (2019) Future Prize by Ewald Marquardt Stiftung (2020) As institutional leader, he directs the Institute for Data Science in Mechanical Engineering and co-leads the RWTH AI Center, overseeing strategic research initiatives and industry collaborations. His academic service includes editorial roles for IEEE Control Systems Society conferences and participation in the Cluster of Excellence 'Internet of Production'. The Institute for Data Science in Mechanical Engineering operates as a multidisciplinary hub where fundamental research in learning-based control meets industrial applications. Current projects focus on drone swarm coordination, deformable object manipulation, and medical diagnostics systems, leveraging both simulation environments and physical testbeds like the Mini Wheelbot platform.

• Heterogeneous Serverless Computing
• Deep Learning
• Real-time Autonomous Driving Systems
• +۳ مورد دیگر

Jianfeng Gu is a Ph.D. Candidate and researcher at the Technical University of Munich (TUM), affiliated with the Department of Computer Science and specifically the Chair of Computer Architecture and Parallel Systems led by Prof. Martin Schulz. He maintains an active research profile with numerous publications and contributes to the academic community through teaching seminars on Cloud Computing. His academic path began with a Bachelor of Software Engineering from Sun Yat-sen University in China (2014-2018), followed by a Master of Engineering from the same institution (2018-2020). Since April 2021, he has been pursuing his Ph.D. at TUM, advancing research in computing systems and architectures. Gu's research focuses on Heterogeneous Serverless Computing for Deep Learning applications, specializing in GPU, FPGA, and NPU technologies within serverless environments. His work addresses critical challenges in resource allocation, auto-scaling, and performance optimization for serverless inference systems. Additionally, he investigates Real-time Autonomous Driving Systems , developing advanced perception techniques through sensor fusion (particularly stereo-LiDAR fusion) for high-precision depth sensing and object detection in autonomous vehicles. His interdisciplinary approach bridges hardware acceleration, cloud infrastructure, and AI applications. His publication trajectory shows a progression from foundational computer vision and autonomous driving research (2018-2020) toward increasingly sophisticated work on serverless computing and federated learning (2021-2025). Recent publications focus on efficient resource sharing in heterogeneous serverless environments, with particular attention to GPU and FPGA allocation strategies that maintain service level objectives while optimizing costs. His work demonstrates strong technical depth across multiple computing domains. Best Paper Award at IEEE/ACM DATE 2021 15+ publications with 185+ citations Research featured in top venues for computer architecture and cloud computing As a Ph.D. researcher, Gu teaches seminars on Cloud Computing (IN2107) and contributes to multiple research projects at TUM's Chair of Computer Architecture and Parallel Systems. His work is supported by the department's research infrastructure and collaborations with faculty including Prof. Martin Schulz and Prof. Michael Gerndt. Gu works within TUM's advanced computing research environment, contributing to projects related to high-performance computing, serverless architectures, and autonomous systems. His research group maintains specialized hardware and software infrastructure for evaluating modern HPC architectures and accelerators, including FPGA clusters and GPU resources for deep learning research.

• Development Economics
• Digitalization
• Economic Growth
• +۸ مورد دیگر

Prof. Dr. Wim Naudé is a Visiting Professor at the TIME Research Area of RWTH Aachen University , Germany. He holds multiple affiliations, including Distinguished Visiting Professor at the University of Johannesburg, Fellow at the Africa Study Centre (University of Leiden, Netherlands), Research Fellow at the IZA Institute of Labor Economics (Germany), and KI-Experte at the OECD AI Policy Observatory (France). His work spans technology, entrepreneurship, and planetary habitability, with a focus on the unsustainability of growth-based economic systems. Research Interests: Wim investigates Artificial Intelligence (AI) economics, ecological economics, and the decline of entrepreneurial dynamism in the West. His research highlights the interplay between energy centrality, growth constraints, and AI's role in post-growth societies. He critiques the illusion of perpetual economic growth and explores societal collapse narratives. Publication Trends: Recent work centers on AI's economic impacts, degrowth theories, and entrepreneurship in conflict zones. His articles and books analyze AI's dual role as both a solution and contributor to global challenges like climate change and inequality. Scientific Awards: Top 2% of global scientists (Stanford University/Elsevier) Top 25 economist in Big Data (IDEAS/RePEC) Highly Ranked Scholar™ in AI (#32 globally) Projects & Collaborations: He co-led a Volkswagen Stiftung project on AI and societal futures, contributed to the OECD AI Observatory, and authored influential books such as The Economic Decline of the West and Economic Growth and Societal Collapse . His affiliations include the IZA Institute of Labor Economics and the TIME Research Area at RWTH Aachen.

• Process Management
• Business Process Optimization
• Agile Methodologies
• +۳ مورد دیگر

Professor Matthias Lederer serves as a faculty member at the Weiden Business School of Ostbayerische Technical University Amberg-Weiden, specializing in Business Informatics with a focus on Process Management. His academic position is complemented by extensive industry experience across multiple sectors including IT services, manufacturing, and consulting. Dr. Lederer's research spans four interconnected domains: process analysis and optimization, IT process management, agile process transformation, and didactics for process digitization. His work bridges theoretical frameworks with practical applications, particularly in business process management (BPM), digital transformation, and the integration of agile methodologies into organizational structures. His research demonstrates a clear trajectory toward increasingly sophisticated applications of data science and artificial intelligence in process optimization. Analysis of his recent publications reveals a strong focus on practical implementations of business process management, with particular emphasis on agile transformations, data-driven process design, and the application of AI in business contexts. His work consistently addresses the intersection of academic research and industry practice, with publications appearing in both academic journals and professional conference proceedings. The research demonstrates growing attention to digital platforms, smart manufacturing applications, and sustainable business practices. His scientific recognition includes: Best Program Director award from ISM International School of Management Project Award 'Innovative LernOrte' from OTH Award for Good Teaching from the Bavarian State Ministry Best Paper Award at the 2014 International Conference on Information Systems Multiple professional certifications including Lean Six Sigma Black Belt and OMG-Certified Expert in Business Process Management Professor Lederer has developed significant academic leadership through his role as Chairman of the Institute of Innovative Process Management. His teaching approach integrates practice-integrated methodologies, reflecting his belief in connecting academic concepts with real-world applications. His extensive consulting background with organizations like REHAU AG + Co. and the Bavarian Ministry of Justice informs his academic work and student mentorship.

Thomas Eckertمشاهده پروفایل

استاد

• Adult Education
• Educational Equity
• School Quality Research
• +۵ مورد دیگر

Prof. Dr. Thomas Eckert holds a professorship at the Faculty of Psychology and Education, Ludwig-Maximilians-Universität München (LMU Munich), specializing in historical socialization research and qualitative methods since 2003. His career spans from 1987-2002 as an employee at Freiburg University's Institute of Educational Sciences, followed by habilitation (1999) and promotion to full professor. Research Focus: Professionalization in pedagogical fields School quality research Educational equity and inclusion Quantitative/qualitative social research methods Lifelong learning systems Recent Publications: Address inclusion monitoring (2021-2025), educational equity frameworks (2022), and methodological innovations in statistical modeling (2019). His work bridges empirical pedagogy with policy analysis, examining transitions in educational systems and regional learning structures. Teaching Contributions: He has developed curriculum materials for distance learning courses and contributed to handbooks on adult education, educational statistics, and teaching practice organization.

Susanne Kugerمشاهده پروفایل

استاد

• Educational Research
• Comparative Educational Studies
• Child Development
• +۵ مورد دیگر

Prof. Dr. Susanne Kuger is a Professor for Empirical Social and Educational Research in Childhood and Adolescence at the Faculty of Psychology and Education, Ludwig-Maximilians-Universität München (LMU). She serves as Research Director and Acting Head of Department at the Center for Continuous Monitoring and Methods , German Youth Institute (DJI). Her work focuses on educational processes in life-course-specific learning environments, survey methodology in cross-national comparative studies, and pandemic-related educational adaptations. Key academic roles: LMU Professor (2022–present), DJI Research Director (2023–present) Research areas: Educational contexts, early childhood development, international comparative studies Current projects: "Growing Up in Germany: Everyday Worlds" (AID:A), "Corona-KiTa Study", "EarlyMath" Research Highlights : Her 15+ recent publications (2016–2023) address pandemic impacts on childcare quality, instructional practices, home learning environments, and methodological innovations in educational surveys. Collaborative projects span Germany-wide studies on daycare infection patterns, mathematical development, and policy frameworks for educational equity. Leadership : She leads the NEPS research group "Educational Processes in Life-Course-Specific Learning Environments" and chairs multiple methodological advisory boards. Her methodological expertise includes anchoring vignettes, thin slices technique, and longitudinal data analysis.