جست‌وجوی استاد و پژوهشگر

Matthias Schefflerمشاهده پروفایل

استاد

• Kinetic Monte Carlo simulation
• ab initio DFT
• electronic structure theory
• +۵ مورد دیگر

Prof. Dr. Matthias Scheffler is the Director of the Theory Department at the Fritz-Haber-Institut der Max-Planck-Gesellschaft. His research focuses on predictive multiscale modeling in catalysis and energy conversion, integrating electronic structure theory, kinetic Monte Carlo simulations, and machine learning. He leads a diverse team (25+ nationalities) exploring processes in catalysts and energy devices. Research Interests: Computationally modeling materials properties, electrochemical interfaces, and energy conversion. Specializes in density-functional theory (DFT), ab initio methods, and data science for accelerating materials discovery. Current projects include understanding electron spillover effects in electrocatalysis and developing self-driving labs for catalysis research. Recent Highlights: Pioneered the Automatic Process Explorer (APE) for atomic dynamics analysis, revealed quantum mechanical electron spillover in water interfaces, and secured funding renewal for the e-conversion Cluster of Excellence. Collaborates with institutions like TU Berlin, FZ Jülich, and Brown University. Labs/Teams: Heads the Theory Department with subgroups like Light-Matter Interactions (Dr. Matthias Kick) and Machine Learning Interatomic Potentials (Dr. Hendrik Heenen). Hosts retreats and international collaborations, including EU-funded projects and Humboldt Professorships.

Christoph Clephasمشاهده پروفایل

استاد

• Sports Governance & Leadership
• Youth Competitive Sports Development
• Bio Banding Systems
• +۳ مورد دیگر

Christoph Clephas is a Professor of Sports Science at the DHGS German University of Health and Sport since 2021, serving as site manager for the university's Hamburg campus. His academic journey includes a sports science degree (focus: competitive sports) from DHGS (until 2014) and a PhD at Kiel University (2016-2019), researching 'Performance variability as a prognostic factor in elite sports' using swimming as a case study. Professional Background Former national youth performance coach and head coach of a state-level swimming facility (2012) Academic leader at spomedis Verlag publishing house Key role in the German Olympic Sports Confederation's performance sport reform (2019–2021), managing scientific networks and liaising with training scientists at Olympic training centers Research Focus Clephas specializes in leadership governance within sports organizations, bio banding systems for youth athletes, and performance variability analysis in elite sports. His work bridges applied sport science with organizational structures, emphasizing evidence-based approaches to talent development and competitive success. Publications His recent work explores Olympic success prediction models, swimming performance metrics in adolescents, and paralympic start dynamics. He serves as a peer reviewer for international journals. Grants & Teams Active in collaborative projects with the German Sports Science Institute (BISp) and International Association of Trainers (IAT). His expertise supports national sports federation strategies through interdisciplinary research partnerships.

Christian Gawronمشاهده پروفایل

استاد

• Internet Technologies
• Software Engineering
• Natural Language Processing
• +۳ مورد دیگر

Prof. Dr. Christian Gawron is a Professor of Internet Technologies at the University of Applied Sciences Südwestfalen since 2019. He leads the Master's program in Applied Computer Science and has held roles as Department Head and Practice Group Leader at IBM Global Business Services (2014–2018), focusing on Watson AI, chatbots, and text mining. Previously, he was a Senior IT Architect at IBM (1999–2014), specializing in business process digitalization for the insurance sector. He earned his Dr. rer. nat. in 1999 with a dissertation on Simulation-Based Traffic Assignment , and held research roles at the Center for Applied Computer Science (ZAIK) and the Universities of Cologne and Bonn. His research spans internet technologies, software engineering, natural language processing (NLP), and traffic simulation. His academic journey includes a physics degree from the Universities of Cologne and Bonn (1989–1995). His work bridges theoretical computer science and practical AI applications, including projects like BERT-DE-NER for NLP and traffic simulation models for large networks. He advises students on theses and projects, emphasizing real-world applications of technology. Prof. Gawron’s research trends reflect a shift from foundational traffic simulation (1990s) to modern AI-driven solutions (2020s), with notable contributions to transformer models and toxic comment detection. His IBM experience underscores practical IT architecture and AI implementation. Consultations are arranged via Calendly or email. He is a prolific researcher, with key contributions in traffic flow theory (e.g., dynamic user equilibrium algorithms) and NLP (e.g., BERT-based models). His work frequently addresses interdisciplinary challenges, such as environmental impact modeling in traffic simulations (FVU cooperative, 1998). Advising & Grants: Supervised numerous theses in internet technologies and AI. Prior IBM projects included grants for AI-driven insurance process optimization and real-time traffic simulation infrastructure. Labs/Teams: Leads the Internet Technologies research group at FH Südwestfalen, collaborating with industry partners on AI and NLP applications.

Knut Tielkingمشاهده پروفایل

استاد

• Prevention and health promotion across the lifespan
• Addiction prevention
• Addiction counseling
• +۷ مورد دیگر

Prof. Dr. Knut Tielking is a Professor at the University of Applied Sciences Emden/Leer, College of Social Work and Health. His roles include Vice Dean of the Department of Social Work and Health (2022-2024), Head of the Master's program Social Cohesion in the Context of Social Work and Health, and member of the research focus 'Resource Orientation in the Tension Field of Individual and Society (RoSiG)'. He also serves on the board of the doctoral program 'Social Work: Deviance and Social Cohesion' and leads the Society for Support of At-Risk and Addicted People in Leer/Emden/Norden. University of Applied Sciences Emden/Leer Vice Dean (2022-2024) Head of Master's Program 'Social Cohesion' Research Focus 'RoSiG' Doctoral Program Board Member His research spans prevention and health promotion across the lifespan, addiction counseling, health education, and corporate health management. He specializes in participatory evaluation methods and inclusive prevention strategies for marginalized groups, including people with mental impairments and migrants. Current projects like SEMRES (Rehabilitation Compass) and SRK (Addiction Rehabilitation Compass) focus on improving access to treatment through digital tools and community networks. Selected trends from his 15 most recent articles include: 1) Integrated approaches to addiction rehabilitation accessibility (2024); 2) Inclusive school-based prevention programs for adolescents (2024); 3) Participatory quality development in social institutions (2006); and 4) Cultural adaptation in addiction care for migrants (2011). As head of the Center for Alcohol & Drug Studies at San Diego State University (2016-2020), he led international collaborations. His expertise informs policy for the Federal Ministry of Health (BMG) and the German Federal State of Lower Saxony. He advocates for community-based participatory research and cross-sector health partnerships in projects like LGFP (Leeraner Health Promotion Program) and PRINOR (regional health statistics).

• Probabilistic Forecasting
• Statistical Evaluation
• Climate Science
• +۳ مورد دیگر

Prof. Tilmann Gneiting is a Professor of Computational Statistics at Karlsruhe Institute of Technology (KIT) and Head of the Computational Statistics Working Group at the Heidelberg Institute for Theoretical Studies (HITS). His research focuses on probabilistic forecasting, statistical evaluation of predictive models, and applications in environmental science, epidemiology, and renewable energy. He has held academic roles in mathematics and statistics departments across multiple institutions. His work emphasizes rigorous statistical methodology for forecasting systems, including ensemble models, uncertainty quantification, and validation frameworks. Notable contributions include developing scoring rules for probabilistic predictions, Bayesian model averaging techniques, and geostatistical methods for weather and climate modeling. Courses taught include Forecasting: Theory and Practice and Time Series Analysis . Prof. Gneiting’s research spans diverse areas such as earthquake forecasting, solar energy prediction, and pandemic modeling. He has contributed to R packages like ensembleMOS and ProbForecastGOP , advancing computational tools for statistical analysis. His work bridges theoretical statistics with practical applications in environmental and public health domains. Professional awards and recognitions are not explicitly listed in the provided texts. His advising and grants involve collaborations in interdisciplinary projects, though specific student names or grant details are not mentioned. He leads computational statistics teams at HITS and actively publishes in top-tier statistical and applied journals.

Tilmann E. Kuhnمشاهده پروفایل

پژوهشگر

• Solar Energy
• Building Integrated Photovoltaics (BIPV)
• Thermal Engineering
• +۴ مورد دیگر

Dr. Tilmann E. Kuhn is the Deputy Head of the Department Energy Efficient Buildings at Fraunhofer ISE, specializing in energy-efficient building systems and solar technologies. He holds a PhD in Physics from the National and Kapodistrian University of Athens and has been with Fraunhofer ISE since 1999. His research focuses on building-integrated photovoltaics (BIPV), solar thermal systems, and smart building technologies. He has led the Solar Building Envelope Group (2004-2022) and coordinated numerous national and international projects. His work emphasizes interdisciplinary collaboration, standardization, and practical implementation of renewable energy solutions. Education: PhD in Physics: Design, Development, and Testing of Innovative Solar-Control Facade Systems (University of Athens) Studies in Physics (University of Heidelberg) Research Interests: Dr. Kuhn’s work spans BIPV integration, thermal performance of building envelopes, and digital tools for energy-efficient design. His innovations include anti-glare PV modules, solar thermal facade systems, and semantic web-based building data frameworks. He advocates for standardized methodologies to bridge research and industry needs, ensuring practical adoption of sustainable technologies. Projects & Grants: He has coordinated projects like SolConPro and contributed to initiatives like BIPV Baden-Württemberg . His teams develop prototypes (e.g., MorphoColor PV modules) and testing protocols (e.g., GWERT-TRACKER) to advance BIPV and solar thermal applications. Labs & Teams: His division collaborates across Fraunhofer ISE’s R&D infrastructure, focusing on energy-efficient building systems, materials science, and digital simulation tools. Key areas include facade innovation, thermal management, and interdisciplinary energy solutions.

• Database Systems
• Information Systems
• Conceptual Modeling
• +۵ مورد دیگر

Ivan Lukovic is a Professor at the Faculty of Technical Sciences, University of Novi Sad, specializing in database systems, information systems, and conceptual modeling. His research spans over two decades with consistent publication output, demonstrating expertise in domain-specific languages, business process modeling, and data science education. His educational background isn't explicitly detailed in the provided sources, but his extensive publication record and editorial roles suggest advanced academic training in computer science. His research primarily focuses on database systems, information modeling, and applications of these technologies in various domains including education and industry. Lukovic's research interests center around database systems, conceptual modeling, and domain-specific languages. His work demonstrates particular expertise in form-based modeling approaches, integrity constraints, and model-driven development methodologies. He has made significant contributions to the understanding of business application modeling, production process modeling in Industry 4.0 contexts, and educational approaches in computer science. His recent publications show a strong focus on practical applications of database and information systems research, particularly in the areas of production process modeling, educational technologies, and data integration. The articles demonstrate increasing sophistication in methodology and application scope, with recent work addressing contemporary challenges in AI-powered literature review assistance and explainable AI methods. Lukovic has served as guest editor for multiple journal issues, including special editions on computer science applications in management and sustainability, and explainable AI methods. His editorial work reflects recognition of his expertise by the academic community. His collaborative work spans numerous projects with colleagues at the University of Novi Sad and international partners. He has contributed to educational initiatives in data science, particularly through the development of academic study programs at his institution. His work on students' preferences in computer science education indicates active engagement with educational research and curriculum development. Lukovic's research has practical applications in industry settings, particularly in manufacturing and business process domains. His recent work on production process modeling for Industry 4.0 demonstrates how his theoretical research translates into real-world applications that address contemporary industrial challenges.

• Software Engineering
• Formal Methods
• Model-Driven Development
• +۳ مورد دیگر

Alexander Raschke is a Professor at the University of Ulm, affiliated with the Institute of Software Engineering and Compiler Construction. His research focuses on formal methods, model-driven engineering, software safety and security, and abstract state machines. He has authored/co-authored over 50 publications, including works on collaborative modeling frameworks, security analysis techniques, and programming by demonstration. He holds a PhD in Computer Science from the University of Ulm (2009). As an academic, he has organized and chaired conferences such as ABZ (2020, 2021), demonstrating leadership in the formal methods community. His work bridges theoretical foundations with practical applications in software systems, emphasizing safety-critical and self-adaptive systems. Notable contributions include the development of EditQL—a textual query language for evolving models—and frameworks for attack-tree generation in cybersecurity.

Martin Fröhlichمشاهده پروفایل

پژوهشگر

• Machine Learning in Education
• Mathematics Education
• Statistics Didactics
• +۳ مورد دیگر

Dr. Martin Fröhlich is a Researcher at the University of Regensburg 's Faculty of Mathematics , affiliated with the Chair of Mathematics Education under Prof. Dr. Stefan Krauss since 2021. His work focuses on integrating machine learning with mathematics education , particularly in predicting academic performance and optimizing teaching strategies. He has presented at international conferences including ICOTS11 (Rosario, Argentina) GDM-Tagung (Frankfurt) GEBF-Tagung (Essen) and co-authored educational textbooks like Lambacher Schweizer 12 . His research interests include Statistical learning applications Educational data mining Didactics of stochastics Data-driven teaching methods Online learning analytics Adaptive learning systems He teaches seminars on statistics didactics and mathematical exercises for teacher training candidates.

• Data Analytics
• Distributed Systems
• Query Optimization
• +۵ مورد دیگر

Jorge-Arnulfo Quiané-Ruiz is a researcher at Qatar Computing Research Institute , with affiliations at institutions like Technical University of Berlin and University of Nantes (PhD, 2008). His work focuses on data analytics , distributed systems , and query optimization , particularly in cross-platform environments and trusted execution frameworks . Research Interests : Data analytics across heterogeneous platforms Secure and compliant data processing in trusted environments Efficient query allocation and optimization Scalable algorithms for big data and streaming graphs Machine learning in data management Table extraction and data cleaning Publications : Recent work includes benchmarks for TEE-based joins and cross-database query frameworks (2023). Explores space-efficient graph algorithms and ML-driven revenue optimization (2022). Developed RHEEMix , a cost-based optimizer for cross-platform systems (2018). Collaborations : Regularly partners with Volker Markl and Zoi Kaoudi on unified analytics frameworks. Contributed to projects like Apache Wayang and AgoRA .

Mathias Klierمشاهده پروفایل

استاد

• Big Data Analytics
• Data Quality
• Artificial Intelligence
• +۳ مورد دیگر

Prof. Mathias Klier holds the Péter Horváth Endowed Professorship for Business Administration with a Focus on Business Information Management at the University of Ulm's Department of Business Analytics. His research focuses on big data analytics, data quality, AI explainability, and social impact of information systems. Klier has held previous academic roles at the Universities of Augsburg, Innsbruck, and Regensburg, where he contributed to data quality metrics and enterprise systems research. He has authored over 100 peer-reviewed articles in journals like MIS Quarterly and Decision Support Systems, and serves as a track chair for ICIS and ECIS conferences. Education: PhD in Business Administration (2008), University of Augsburg (Dissertation: 'Designing Customer-Centric Information Systems') MSc in Business Mathematics (2005), University of Augsburg Research Interests: Klier’s work bridges technical data quality challenges with societal impacts. Key themes include probabilistic metrics for data currency/consistency, ethical AI design, and leveraging peer networks for unemployment support. His recent projects apply explainable AI to public services and workforce development. Key Achievements: Recipient of Research Prize of the Swabian Economy (2008) Winner of Vodafone Foundation Award (2005) Awarded Ciborra Award (2018) for innovative research on event-driven duplicate detection Advising & Grants: Klier’s team has secured funding for projects on future skills forecasting and refugee integration via digital peer groups. He advises on AI literacy initiatives in K-12 education and collaborates with industry partners like German car manufacturers. Labs/Teams: Leads the Business Analytics Institute at Ulm, focusing on data-driven decision making and AI ethics. Active in interdisciplinary research networks including the German Information Quality Management Initiative.

• Business Process Management
• Process Mining
• Business Process Simulation
• +۴ مورد دیگر

Marlon Dumas is a leading researcher in business process management and process mining at the University of Tartu, Estonia. With over 467 publications spanning from 1997 to 2025, his work has significantly advanced methodologies in business process analysis, simulation, and optimization. His research bridges theoretical foundations with practical applications, developing tools and frameworks that enable organizations to analyze and optimize operational processes. Dumas's primary research interests include business process management, process mining, business process simulation, prescriptive process monitoring, and data-aware business processes. He has pioneered methods for modeling resource availability, activity delays, and waiting times in business processes. His work on prescriptive process monitoring addresses critical challenges such as resource constraints, uncertainty in predictions, and causal effect estimation for interventions. Recent publications reveal a strong trend toward integrating artificial intelligence with business process management, particularly exploring the application of large language models to process optimization, monitoring, and redesign tasks. His research demonstrates consistent innovation, with publications appearing in top venues including Information Systems, Data & Knowledge Engineering, and the International Conference on Business Process Management. Dumas has developed several influential tools including SIMOD for automated discovery of business process simulation models, Optimos for simulation-driven process optimization, and Kairos for prescriptive monitoring. His collaborative network is extensive, featuring frequent co-authorship with prominent researchers including Marcello La Rosa, Luciano García-Bañuelos, Fabrizio Maria Maggi, and Wil M. P. van der Aalst. His work on privacy-preserving process mining, particularly regarding differentially private release of event logs, addresses critical challenges in applying process mining techniques while maintaining data privacy and compliance with regulations like GDPR. Dumas's research continues to push boundaries, with recent work exploring the integration of large language models with business process management systems, suggesting an ongoing commitment to advancing the field through innovative applications of emerging technologies.

• Cell Biology
• Structural Biology
• Biophysics
• +۳ مورد دیگر

Dr. Martin Beck is a Research Professor and Director at the Max Planck Institute of Biophysics, focusing on the structural and functional analysis of large macromolecular complexes such as nuclear pore complexes (NPCs). His research employs advanced techniques including cryo-electron tomography, live-cell imaging, and computational modeling to study NPC dynamics, HIV capsid transport, and cellular membrane integrity. Beck has received three prestigious ERC grants (Starting, Consolidator, and Advanced) for his groundbreaking work. His interdisciplinary approach bridges structural biology, cell biology, and biophysics, with applications in virology and drug discovery. Education highlights include a PhD from Technical University of Munich (2006) and postdoctoral research at ETH Zurich and EMBL Heidelberg. He leads a lab investigating nuclear transport mechanisms, membrane interactions, and the mechanical properties of cellular organelles. Key achievements include uncovering NPC dilation dynamics and elucidating HIV capsid-nuclear pore interactions. Scientific awards include ERC grants and contributions to structural biology methodologies. Ongoing projects explore nuclear pore safeguarding mechanisms, drug action at the cellular level, and AI-driven structural analysis. Beck collaborates extensively with institutes worldwide, advancing both fundamental science and translational applications.

• Social Inequality
• Educational Sociology
• Genetic Influences on Behavior
• +۳ مورد دیگر

Mirko Ruks is a Researcher at Bielefeld University's Faculty of Sociology, Department of Social Structure and Social Inequality, affiliated with the Diewald Research Group. He specializes in sociological research combining genetic and social factors influencing educational outcomes and social mobility. His work focuses on twin studies, molecular genetic data analysis, and interdisciplinary approaches to understanding inequality. Project Lead: DFG-funded study on genetic/social determinants of life success and educational mobility using twin family data. Key areas: Gene-environment interactions, social stratification, educational achievement disparities, and longitudinal research methods. Recent publications analyze genetic influences on educational attainment, neighborhood effects on life satisfaction, and mechanisms of SES-driven educational expectations. Active in TwinLife panel study methodology and data analysis.

• Computational Economics
• Agent-Based Modeling
• Innovation Economics
• +۹ مورد دیگر

Herbert Dawid is a Professor of Economic Theory and Computational Economics at the Faculty of Business and Economics , Bielefeld University , Germany. He holds multiple roles including Chair Holder, Subproject Manager for SFB 1283, and Founding Director of the Center for Uncertainty Studies (CeUS) . His research focuses on Computational Economics , Agent-Based Modeling , and Innovation Dynamics , with emphasis on uncertainty management and digitalization. Current Appointments Professor (W3), Faculty of Business and Economics, Bielefeld University (since 2010) Subproject Manager, SFB 1283 (Innovation Dynamics in Market Uncertainty) Founding Director, Center for Uncertainty Studies (CeUS) Research Themes Digitalization and Intelligent Products Investing Under Uncertainty Agent-Based Modeling in Economics Dynamic Analysis of Economic Policy Control Theory and Differential Games His work spans economic policy modeling , technological innovation , and financial constraint analysis , with notable publications on AI integration in economic systems and autonomous vehicle policy frameworks. He contributes to interdisciplinary initiatives like AI*IM (Interactive Inclusive AI for People with Cognitive Disabilities) through economic expertise.