جست‌وجوی استاد و پژوهشگر

• Database Systems
• Data Management
• Query Optimization
• +۳ مورد دیگر

Jan Kossmann is a researcher affiliated with the Hasso Plattner Institute at the University of Potsdam, Germany. His work focuses on database systems, query optimization, and autonomous database management. He earned his PhD in 2023 with a thesis on unsupervised database optimization, including efficient index selection and data dependency-driven query optimization. His research explores topics like workload-aware indexing, reinforcement learning applications in database systems, and the development of frameworks for evaluating autonomous database technologies. Key collaborations include projects with Rainer Schlosser, Thorsten Papenbrock, and others, emphasizing experimental evaluations and system design. Notable contributions include the SWIRL reinforcement learning-based index selection framework and the 'Magic Mirror' tool for comparing index selection approaches. His publications span venues like VLDB, EDBT, and ICDE, reflecting his deep engagement with database theory and practical system implementation.

• Recommender Systems
• Context-aware Recommendation
• Explainable AI
• +۵ مورد دیگر

Markus Zanker is a Professor in the Department of Knowledge Engineering within the Faculty of Computer Science at Free University of Bozen-Bolzano, Italy. With an extensive publication record spanning over two decades, he has established himself as a leading expert in recommender systems research, with particular expertise in context-aware, group, and knowledge-based recommendation approaches. His work bridges theoretical foundations with practical applications across diverse domains including tourism, healthcare, and e-commerce. Zanker's research interests center on advancing the theoretical underpinnings of recommender systems while addressing practical challenges in real-world deployments. His recent work has focused on causal decision-making frameworks for recommendation, intent-aware systems, and the integration of generative AI in group recommendation scenarios. He has made significant contributions to explainable recommendation systems, medical recommendation applications, and tourism recommendation systems, demonstrating both theoretical rigor and practical impact. His recent publication portfolio reveals a strong trend toward addressing fundamental challenges in recommendation science, including the growing emphasis on causal reasoning to move beyond correlation-based approaches, the integration of generative AI capabilities for more sophisticated group decision support, and the development of frameworks for ethical and socially beneficial recommendation systems. His work increasingly bridges the gap between traditional recommendation algorithms and emerging AI paradigms while maintaining focus on real-world applicability. Zanker is actively involved in the academic community as a workshop organizer, having co-chaired the Knowledge-aware and Conversational Recommender Systems (KaRS) workshop and the Recommenders in Tourism (RecTour) workshop for multiple consecutive years at major conferences including RecSys. His research has been supported through collaborations with numerous international researchers and institutions, focusing on both theoretical advances and practical implementations of recommendation technology across multiple application domains.

• Materials Science
• Corrosion Engineering
• Electrochemistry
• +۵ مورد دیگر

Prof. Robert Meißner is a Professor at the Department of Surface Physics and Technology at TUHH. His research focuses on molecular simulation techniques applied to corrosion processes, energy storage systems, and nanomaterials. He develops computational tools like ELECTRODE and i-PI for electrochemical and advanced molecular dynamics simulations. His work addresses challenges in magnesium battery performance, structural health monitoring of composite materials, and interfacial phenomena in nanoscale systems. Education details are not explicitly provided in the text, but his professional trajectory reflects extensive academic and industrial experience in materials science. Research interests span from fundamental studies (e.g., water imbibition in nanopores, magnetite oxidation dynamics) to applied innovations (e.g., corrosion protection via layered double hydroxides, data-driven electrolyte design). His recent publications highlight trends in data-driven materials discovery, structural health monitoring via vibro-acoustic methods, and computational prediction of corrosion inhibitors. He collaborates on projects involving graphene-based supercapacitors, epoxy resin curing dynamics, and peptide-surface interactions. Advising and grants: While student names are not listed, his research group actively explores corrosion engineering, battery technology, and nanomaterials. Projects include EU-funded initiatives and industry partnerships. Technical expertise includes ATR-FTIR spectroscopy, molecular dynamics, and machine learning for sparse data scenarios. He leads teams focused on surface science and energy storage, maintaining lab facilities for in situ electrochemical analysis and advanced computational modeling. His work bridges theoretical insights with practical applications in materials durability and energy systems.

• Combinatorial Optimization
• Approximation Algorithms
• Online Algorithms
• +۳ مورد دیگر

Prof. Dr. Sven Oliver Krumke is a Full Professor of Mathematics and currently serves as Dean of the Faculty of Mathematics at the Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau (RPTU). His research focuses on Combinatorial Optimization, Approximation Algorithms, Online Algorithms, Complexity, Algorithmic Game Theory, and Graph Theory with Applications. He leads the Optimization Group (AG Optimierung) within the Department of Mathematics. Education and Academic Path: PhD (Dr. rer. nat.) in Mathematics, University of Würzburg (1997) Habilitation in Mathematics, Technische Universität Berlin (2002), Thesis: 'Online Optimization: Competitive Analysis and Beyond' Professor at RPTU since 2004 Research Projects: Principal investigator in the Research Training Group (GRK 2982) 'MIMO: Mathematics of Interdisciplinary Multiobjective Optimization' Project lead for 'ONE PLAN: Optimization in Emergency Medical Services in Rhineland-Palatinate' Teaching includes courses on Analysis, Mathematical Modeling in Economics, and Reading Courses. He supervises Bachelor's and Master's theses in Optimization-related topics. He has held roles such as Scientific Researcher at the Konrad-Zuse-Zentrum Berlin (1998–2004), and has extensive international collaborations, including a Fulbright-funded stay at SUNY Albany (1992–1993). His work emphasizes practical applications in healthcare logistics, emergency services optimization, and algorithmic solutions for real-world problems.

Pan Huiمشاهده پروفایل

استاد

• Ubiquitous Computing
• Data-driven Systems
• Human-Data Interaction
• +۳ مورد دیگر

Pan Hui is Chair Professor of Computational Media and Arts at Hong Kong University of Science and Technology, where he serves as Director of the Center for Metaverse and Computational Creativity and HKUST-DT Systems and Media Laboratory. He concurrently holds the Nokia Chair in Data Science position at the University of Helsinki. His interdisciplinary research spans ubiquitous computing, mobile systems, and social networks. Research interests focus on: Data-driven systems design for mobile/cloud platforms Immersive human-data interaction through AR/VR Social network analysis using big data analytics Energy-efficient mobile computing architectures Publications show strong focus on augmented reality systems, cloud computing optimization, and human-computer interaction, with recent work advancing real-time visualization and low-latency tracking techniques. Awards and honors include: Fellowship in Royal Academy of Engineering (2020) Membership in Academia Europaea (2019) IEEE Fellow (2018) ACM Distinguished Scientist (2016) Leads multiple research initiatives including H2O (Hong Kong-Helsinki Oasis for Innovation) and supervises doctoral students working on metaverse technologies. Directs laboratories focusing on systems/media integration and computational creativity.

• Catalysis
• Heterogeneous Catalysis
• Mechanochemistry
• +۳ مورد دیگر

Prof. Ferdi Schüth is a renowned chemist and director at the Max Planck Institute for Coal Research since 1998. He serves as Second Vice President of the Society of German Natural Scientists and Physicians (GDNÄ), set to become its president in 2027. His research focuses on catalysis, mechanochemistry, and sustainable energy solutions. He pioneered high-throughput experimentation (HTE) and founded hte GmbH in 1999. Schüth has received prestigious awards including the Alwin Mittasch Prize (2025) and Wilhelm Exner Medal (2024), recognizing his contributions to catalysis and industrial applications. His work spans nanostructured catalysts, mechanochemical ammonia synthesis, and recycling innovations. Research interests include heterogeneous catalysis, mechanochemical processes, and energy transition technologies. Key areas involve catalyst design for fuel cells, hydrogen storage, and polymer recycling. His interdisciplinary approach bridges fundamental science and industrial applications, emphasizing cross-disciplinary collaboration. Recent studies explore catalyst stability, electrochemical nitrogen synthesis, and scalable catalytic materials. Schüth’s labs develop novel catalysts using mechanochemical methods and advanced characterization techniques. Scientific awards highlight his impactful contributions: the Alwin Mittasch Prize for catalysis fundamentals, the Wilhelm Exner Medal for industrial applicability, and an honorary fellowship from the Chinese Chemical Society. His leadership roles in scientific societies underscore his commitment to fostering interdisciplinary science and public engagement. Ongoing projects focus on sustainable chemical processes, including mechanochemical recycling of plastics and optimizing catalysts for renewable energy systems.

Rayna Dimitrovaمشاهده پروفایل

استادیار

• Verification
• Reactive Systems Synthesis
• Control and Robotics
• +۳ مورد دیگر

Rayna Dimitrova is a Tenure-track faculty member at the CISPA Helmholtz Center for Information Security in Saarbrücken, Germany. Previously, she held positions as Lecturer (Assistant Professor) at the University of Sheffield and University of Leicester, and postdoctoral roles at the University of Texas at Austin and the Max Planck Institute for Software Systems. She earned her PhD from Saarland University. Her research focuses on formal methods, including verification and synthesis of reactive systems, applications to control and robotics, quantitative analysis of probabilistic systems, and information-flow security. Key interests include strategic synthesis under partial observability, probabilistic uncertainty, and continuous dynamics, with applications to autonomous systems. She has served in numerous prestigious roles, including PC co-chair for VMCAI 2024, HYPER 2023, and SMT 2018. Her awards include the RS3 Best Paper Award (VMCAI 2012) and nominations for ETAPS (TACAS 2015) and EMSOFT (2014) Best Paper Awards. Her research group includes PhD students Rafael Dewes, Philippe Heim, and Saleh Soudijani. She has taught courses on reactive synthesis, program analysis, and decision procedures at multiple institutions, including the University of Sheffield and TU Kaiserslautern.

Kun-Han Linمشاهده پروفایل

دانشیار

• Organic Electronics
• Organic Semiconductors
• Photovoltaics
• +۳ مورد دیگر

Kun-Han Lin is an Associate Professor at National Tsing Hua University since June 2022. Previously, he served as a Postdoctoral Fellow in the theory group at the Max Planck Institute for Polymer Research (MPI-P) from October 2020 to 2022. His research focuses on computational design of organic semiconductors for applications in organic light-emitting diodes (OLEDs), perovskite solar cells, and photovoltaic materials. Lin holds a Ph.D. in Chemistry from École Polytechnique Fédérale de Lausanne (EPFL) and a Master’s in Materials Science from National Taiwan University. His research interests emphasize structure-property relationships in organic materials, virtual screening for optimal molecular candidates, and understanding charge transport mechanisms. Key projects include predicting molecular ordering in thin films and developing non-fullerene acceptors for balanced charge transport. In 2023, he was awarded a prestigious Max Planck Partner Group to advance collaborative research. Publications highlight innovations in high-entropy alloy catalysts for hydrogen production, molecular design for charge-carrier trapping elimination, and computational approaches to predict glass transition temperatures. His work bridges theoretical simulations with experimental validation, targeting sustainable energy technologies.

Michael Baakeمشاهده پروفایل

استاد

• Aperiodic Order
• Dynamical Systems
• Combinatorics
• +۴ مورد دیگر

Michael Baake is a Professor of Mathematics at Bielefeld University, affiliated with the Faculty of Mathematics. His research focuses on Aperiodic Order, Dynamical Systems, Combinatorics, and Mathematical Physics. He leads multiple research projects, including the SFB/TR 358 'Integral Structures in Geometry and Representation Theory' and SFB 1283 'Taming Uncertainty'. His work bridges pure mathematics with applications in crystallography and stochastic systems. Affiliations: Representative for the Faculty Library, Co-Director of the Research Focus on Mathematical Modeling. Cooperations: Collaborates with international experts like Uwe Grimm, Daniel Lenz, and Nicolae Strungaru on topics such as aperiodic tilings and spectral theory. Research Groups: Leads a vibrant research group with members including Anna Klick, Daniel Luz, and Timo Spindeler, focusing on quasicrystals, combinatorial structures, and number theory applications. His contributions include co-editing the book 'Aperiodic Order: Crystallography and Almost Periodicity' and organizing workshops on spectral theory and dynamical systems. He actively engages in academic service, including editorial roles and conference organization.

• Cybersecurity
• Internet of Things (IoT)
• Blockchain Technology
• +۳ مورد دیگر

Yuan Liu is a faculty member affiliated with Guangzhou University's Cyberspace Institute of Advanced Technology. Their research focuses on cybersecurity, blockchain technology, federated learning, and IoT systems. They have held roles at multiple institutions, including Northeastern University (Software College) and Nanyang Technological University (PhD in Computer Engineering). Liu's work emphasizes secure communication, edge computing, and distributed systems, with contributions to protocols like blockchain-based redactable systems and quantum federated learning frameworks. They have collaborated extensively on projects addressing IoT security, smart healthcare, and privacy-preserving technologies. Key research trends include leveraging AI for enhanced security (e.g., watermarking frameworks, attack detection) and optimizing resource allocation in edge computing environments. Their publications span journals like IEEE Communications Surveys & Tutorials and conferences such as GLOBECOM.

Jürgen Melznerمشاهده پروفایل

استاد

• Construction Management
• Occupational Health and Safety
• Building Information Modeling (BIM)
• +۴ مورد دیگر

Prof. Dr.-Ing. Jürgen Melzner is a Professor at the Faculty of Civil and Environmental Engineering at Bauhaus-Universität Weimar. His research focuses on construction operations, occupational health and safety, and BIM integration. He leads projects in lean construction management, noise pollution modeling, and safety planning using BIM. His work emphasizes digital transformation in construction processes and legal aspects of building permits. Education includes a Dr.-Ing. (Doctor of Engineering) with extensive career contributions to construction safety and process optimization. His teaching and research involve BIM applications, IoT integration, and interdisciplinary methods in construction education. Research interests span BIM-based safety systems, predictive noise simulation, ontology networks for construction data, and lean principles in project management. Recent articles address stakeholder management in permits, machine learning for site monitoring, and metaverse applications in urban planning. Notable advising includes guidance of master's students like Mahshid Birkholz and Nasim Babazadeh. His work bridges academic research with practical implementation through projects like BIMwissT and DROHNIS. Labs/teams: Active in the Chair for Construction Management and BIM, focusing on digital tools and safety innovation.

Regina Palkovitsمشاهده پروفایل

استاد

• Heterogeneous Catalysis
• Renewable Energy Conversion
• Biomass Utilization
• +۵ مورد دیگر

Prof. Regina Palkovits is a Full Professor of Heterogeneous Catalysis & Chemical Technology at RWTH Aachen University's Institute of Chemical Technology & Macromolecular Chemistry (ITMC). She serves as Acting Director of ITMC since 2015 and holds a Max Planck Fellowship at the MPI for Chemical Energy Conversion (since 2019). Her research focuses on sustainable catalytic processes for renewable energy and biomass conversion, including photocatalytic CO2 reduction, electrochemical water splitting, and biorefinery pathways. Key projects involve developing solid molecular catalysts, immobilized heteropolyacids, and single-atom catalysts on covalent triazine frameworks. Palkovits leads a research group with ongoing projects in catalytic hydrogenation, bio-based tandem reactions, and hydrogen production technologies. Education: Diploma in Chemical Engineering, Technical University Dortmund (1998–2003) PhD, Max Planck Institute for Coal Research (2003–2006) Postdoc, Utrecht University (2007) Group Leader, Max Planck Institute for Coal Research (2008–2010) Research Interests: Palkovits’ work bridges heterogeneous catalysis and materials innovation to address global challenges. Key areas include: Electrochemical hydrogen production and water splitting Biomass conversion to platform chemicals (e.g., xylitol) CO2-to-fuel processes using photocatalytic systems Immobilized catalyst design for recyclability and stability Awards: Max Planck Fellow (2019) EFCATS Young Researcher Award (2019) DECHEMA Award (2017) Robert Bosch Junior Professorship (2010) Hendrik Casimir–Karl Ziegler Award (2006) Grants & Collaborations: Active in interdisciplinary projects with MPI-CEC and Hamburg University. Her group seeks students for research in catalytic hydrogenolysis, electrochemical conversions, and biorefinery pathways. Labs/Teams: Leads the “Solid Molecular Catalysts” group, focusing on sustainable chemical processes and material synthesis for green energy applications.

Claudia Klüppelbergمشاهده پروفایل

استاد

• Applied Probability
• Mathematical Statistics
• Financial Risk Management
• +۳ مورد دیگر

Claudia Klüppelberg is a Professor and Chair of Mathematical Statistics at the Center for Mathematical Sciences, Technische Universität München (TUM). Her academic journey includes positions at ETH Zurich, University of Mainz, and TUM since 1997. She holds a Carl von Linde Senior Fellowship at TUM-IAS, focusing on Risk Analysis and Stochastic Modeling. Her research bridges applied probability, statistics, and their applications in finance and insurance, emphasizing extreme value theory, risk processes, and stochastic networks. She has received prestigious awards such as the New Frontiers in Risk Management Award (2007) and Cross of Merit (2001). Her work addresses real-world challenges in financial risk management, including systemic risk in networks and operational risk modeling. Her recent publications explore causal analysis of extreme risks in networks, max-linear models, and Bayesian networks for extreme events. She contributes to academic leadership as an editorial board member and advisor, promoting interdisciplinary stochastic sciences.

• Climate Dynamics
• Atmospheric Science
• Oceanography
• +۳ مورد دیگر

Dr. Tido Semmler is a Senior Scientist in the Climate Dynamics department at the Alfred Wegener Institute (AWI). His research focuses on polar-latitude linkages in the atmosphere and ocean, particularly the response of the climate system to anthropogenic emissions. He contributes to global climate modeling efforts, including CMIP6 simulations with the AWI-CM model, and investigates Arctic amplification effects on mid-latitude weather patterns. Affiliations: AWI Climate Dynamics Department, Helmholtz Association Key Projects: APPLICATE (Arctic Predictability and Prediction of sea ice and climate), HighResMIP (High Resolution Model Intercomparison Project) His work emphasizes high-resolution modeling, data assimilation for sea ice prediction, and understanding mechanisms behind Arctic sea ice decline and its global impacts. Semmler collaborates internationally on climate assessment frameworks and contributes to advancements in coupled ocean-atmosphere modeling systems.

• Climate Modelling
• Paleoclimate Modelling
• Earth System Modelling
• +۳ مورد دیگر

Dr. Jan Streffing is a Scientific Programmer in the Climate Dynamics department at the Alfred Wegener Institute (AWI) in Bremerhaven, Germany. His work focuses on advancing Earth System Models (ESMs) with an emphasis on coupled climate modeling, paleoclimate simulations, and ensuring model scalability while preserving mass and energy conservation. He coordinates Earth System Model development efforts, particularly with the AWI-CM3 climate model framework. His research interests include high-resolution climate projections, atmosphere-ocean coupling mechanisms, and improving model physics through numerical methods. Streffing contributes to global kilometer-scale simulations using frameworks like IFS-FESOM, addressing challenges in resolving ocean eddies and cloud processes. He has developed ESM-Tools infrastructure to modularize climate modeling workflows and enhance computational efficiency. Key projects involve the MOSAiC expedition evaluation, where nudging techniques were applied to align model outputs with in-situ observations, revealing model deficiencies in cloud dynamics and snowpack representation. His work also explores deep-water formation impacts on climate sensitivity and integrates data assimilation techniques to improve sea ice forecasts in the AWI coupled prediction system. Streffing's contributions bridge climate science and computational practices, supporting advancements in model resolution, scalability, and accuracy for understanding future climate scenarios.