جست‌وجوی استاد و پژوهشگر

• Marine Geochemistry
• Paleoceanography
• Biogeochemical Cycles
• +۳ مورد دیگر

Dr. Walter Geibert is a Researcher in the Marine Geochemistry department at the Alfred Wegener Institute, specializing in naturally occurring radionuclides, nutrient cycles, and paleoceanography. He holds key roles such as Head of the Radiochemistry/Inorganic Chemistry Lab and Deputy Section Head. His research focuses on ocean biogeochemical processes, including trace metal dynamics, sediment geochemistry, and climate-driven changes in marine systems. Education: Not explicitly stated in the provided text. Roles: Radiation Safety Officer, Ombudsperson for PhD students, and Member of the GEOTRACES Scientific Steering Committee. Research interests span radionuclide distributions in oceans, nutrient fluxes, paleoceanographic reconstructions, and development of new proxies for oceanographic studies. He has led numerous expeditions, including PS144 and MOSAiC, contributing to Arctic and Antarctic oceanography. Publications highlight studies on sediment dynamics, carbon burial, and isotopic tracers, with a focus on polar regions and the Southern Ocean. His work integrates lab-based analyses with field data to understand long-term environmental changes.

• Network Science
• Social Influence Modeling
• Control Systems
• +۵ مورد دیگر

Chiara Ravazzi is an accomplished researcher at Politecnico di Torino specializing in network science, social influence modeling, and control systems. Her academic career spans over 15 years with consistent high-impact publications in top-tier venues including IEEE journals and conferences. Dr. Ravazzi's research focuses on understanding complex network dynamics with applications spanning social networks, wireless communications, and pandemic modeling. Her work bridges theoretical network analysis with practical implementations, particularly examining how information and influence propagate through networks. She has developed novel methodologies for analyzing social influence, optimizing network resources, and predicting behavioral patterns in complex systems. Analysis of her recent publications (2023-2025) reveals three major research thrusts: (1) Social network dynamics and influence modeling, particularly examining innovation diffusion and popularity mechanisms; (2) Optimization of communication networks with applications to 5G/6G systems; and (3) Network-based approaches to public health challenges like pandemic intervention planning. Her interdisciplinary work demonstrates strong methodological rigor while addressing contemporary real-world problems. Dr. Ravazzi maintains extensive collaborations with leading researchers including Fabrizio Dabbene, Enrico Magli, Paolo Frasca, and Valentina Breschi. Her publication record shows consistent growth in both quantity and impact, with numerous first-author and senior-author contributions across multiple domains. She serves on program committees for major conferences in control systems and network science.

• Blockchain Technology
• Distributed Systems
• Permissioned Blockchains
• +۳ مورد دیگر

Artem Barger is a researcher specializing in blockchain technology, distributed systems, and database optimization. With affiliations primarily in blockchain development and academic research, he has contributed extensively to Hyperledger Fabric enhancements and decentralized information systems. Research Interests Optimizing state databases for blockchain platforms Byzantine Fault Tolerance in distributed networks Permissioned blockchain architectures Tokenization of real-world assets AI applications in soft skills evaluation Recent Publications Barger's work focuses on improving blockchain scalability and security through techniques like certification blocks, Patricia Merkle tries, and verifiable randomness. He has also explored tokenization applications in charity and energy sectors.

• Machine Learning
• Computer Science
• Medical Informatics
• +۷ مورد دیگر

Yan Li is a researcher with extensive contributions across interdisciplinary domains including Machine Learning , Signal Processing , and Environmental Science . Affiliated with institutions such as the University of Southern Queensland , Hebei University , and Shandong University , Li's work spans applications in Medical Informatics , Remote Sensing , and Operations Research . Recent publications highlight expertise in Deep Learning (e.g., hyperspectral classification, image fusion), Stochastic Modeling (e.g., chemotaxis models), and Federated Learning (e.g., vertical federated fuzzy clustering). Collaborative projects include 3D Reconstruction , Smart Grid Security , and Landslide Monitoring using satellite data. Li's 2025 work demonstrates a focus on Medical Imaging (segmentation algorithms with dual-frequency decoupling), AI in Education (ChatGPT adoption), and Industrial IoT (GPU-accelerated vessel trajectory visualization). While no explicit academic rank is provided, their prolific publication record suggests a Researcher role.

• Smart Grids
• Power System Cybersecurity
• Cyber-Physical Systems
• +۷ مورد دیگر

Peter Palensky is a leading researcher in smart grids, power system cybersecurity, and cyber-physical systems. His recent work focuses on digital twins for power systems, quantum computing applications in energy analysis, and secure blockchain frameworks for distributed energy resources. He collaborates extensively with institutions across Europe, particularly in Dutch and Mongolian grid stability projects. Research areas include Smart grid resilience against cyber attacks Quantum-enhanced power flow analysis Electric vehicle grid integration (V2G) Machine learning for energy systems optimization High-voltage direct current (HVDC) security His publications emphasize practical implementations, such as hardware-in-the-loop testing for photovoltaic systems and real-time simulation models for energy storage. Recent articles explore large-scale synthetic data generation for grid analysis, dynamic tariff impacts on EV charging, and advanced control strategies for offshore MMC grids.

Flemming Dahlkeمشاهده پروفایل

استادیار

• Marine Ecology
• Climate Change Impacts
• Fisheries Science
• +۱ مورد دیگر

Flemming Dahlke leads the Junior Research Group in Ecology of Living Marine Resources at University of Hamburg's Institute of Marine Ecosystem and Fisheries Sciences. His work examines climate change impacts on aquatic ecosystems. Research focuses on: Thermal bottlenecks in fish life cycles Ocean acidification effects Species distribution shifts Sustainable aquaculture solutions Publications demonstrate integrative approaches combining experimental physiology, ecological modeling, and climate projections. Notable contributions include identifying critical thermal thresholds during early developmental stages.

• Mathematical Optimization
• Game Theory
• Mechanism Design
• +۷ مورد دیگر

Max Klimm is an Assistant Professor for Discrete Optimization at Technische Universität Berlin, affiliated with Faculty II – Mathematics and Natural Sciences and the Department of Mathematics. He leads the research group in Discrete Optimization and holds editorial roles at journals like the International Journal of Game Theory and Operations Research Forum . His academic journey includes a PhD in Mathematics from TU Berlin (2012), followed by roles as an Assistant Professor at Humboldt-Universität zu Berlin and Head of the Junior Research Group at the Einstein-Center for Mathematics. His research focuses on mathematical optimization, game theory, and mechanism design applied to multi-agent systems in traffic, telecommunications, and economics. Recent work addresses equilibrium computation in congestion games, stochastic optimization, and algorithmic challenges in network design. Key projects include Combinatorial Network Flow Methods for Gas Markets and the Math+ projects on mechanism design and evolutionary models for networks. Teaching responsibilities include courses on Discrete Optimization, Algorithmic Game Theory, and introductory mathematical courses. His research has been funded by DFG, Einstein Center, and Math+ initiatives. Notable contributions include advancements in parametric flow algorithms, impartial selection mechanisms, and reconstructing historical road networks using cost-benefit models.

• Systematic Zoology
• Evolutionary Biology
• Phylogenetics
• +۳ مورد دیگر

Dr. Katharina M. Jörger is a researcher at Ludwig Maximilian University of Munich, specializing in the phylogeny and evolution of meiofaunal molluscs. Her work focuses on understanding the evolutionary relationships and ecological roles of small marine organisms, particularly within the Mollusca phylum. She holds a Ph.D. from LMU Munich, where her thesis explored molecular phylogeny of Acochlidia, a group of marine and freshwater gastropods. Her research integrates anatomical, genetic, and ecological approaches to address questions in systematic zoology and evolutionary biology. Key areas of expertise include meiofaunal molluscs, molecular systematics, and cryptic species identification. She has contributed significantly to the study of Aplacophora (Solenogastres) and Acochlidimorpha, elucidating their phylogenetic relationships and ecological adaptations. Her work often emphasizes the development of novel methods for studying small, elusive organisms, such as 3D microanatomy and hybridization-based genetic capture techniques. Dr. Jörger has conducted fieldwork in diverse locations, including the Azores, Antarctic regions, and the Caribbean, to document meiofaunal biodiversity. Her publications span topics like mitochondrial genome analysis, freshwater slug invasions, and deep-sea predation dynamics. She collaborates internationally on projects exploring meiofaunal ecology and evolutionary patterns. Her research also addresses broader ecological questions, such as how meiofauna contributes to marine biodiversity and how taxonomic methods can better capture cryptic diversity. Despite no explicitly listed awards, her prolific publication record underscores her impactful contributions to mollusc systematics and evolutionary biology.

• Risk Analysis
• Structural Reliability
• Civil Engineering
• +۵ مورد دیگر

Prof. Michael Beer is the Executive Director of the Institute for Risk and Reliability at Leibniz University Hannover. He holds a professorship in the Faculty of Civil Engineering and Geodetic Science and serves on the Faculty Council. His research focuses on structural reliability, uncertainty quantification, and risk analysis with applications in civil engineering systems. He leads the Collaborative Research Centres (CRC) 871 and 1463, addressing regeneration of complex capital goods and offshore megastructure design, respectively. His work integrates machine learning, Bayesian methods, and stochastic modeling to address challenges in seismic vulnerability, geotechnical systems, and reliability-based design optimization. Beer is also a member of the Leibniz Research Centre Energy 2050, emphasizing interdisciplinary energy systems research. Beer's research interests span probabilistic modeling of dynamic systems, uncertainty propagation in engineering systems, and data-driven methods for reliability assessment. His recent publications emphasize computational methods for reliability, machine learning applications, and seismic risk analysis. He actively contributes to academic leadership roles, including editorial boards and research center management.

Maribel Acostaمشاهده پروفایل

استاد

• Databases
• Semantic Web
• Artificial Intelligence
• +۳ مورد دیگر

Maribel Acosta is a Professor of Databases and Information Systems at Ruhr-Universität Bochum's Faculty of Computer Science. She holds affiliations with the Institut für Neuroinformatik (INI), focusing on interdisciplinary research combining natural and artificial cognitive systems. Her work spans databases, semantic web technologies, artificial intelligence, and machine learning applied to knowledge graphs. Acosta earned her Ph.D. (Summa Cum Laude, 2017) and Master's in Computer Science from Karlsruhe Institute of Technology (KIT). She has held roles including Junior Professor at RUB (2020–present), Deputy Professor at KIT (2019–2020), and Assistant Lecturer at Heidelberg University (2020). Research Interests: Her primary research focuses on efficient querying of knowledge graphs, integration of machine learning in data management, and semantic web technologies. Key areas include knowledge graph population, federated query processing, and stability in neural networks. Recent work explores applications in automotive systems and social science data integration. Awards: Notable recognitions include a 2022 WWW Best Paper nomination, Aminer's Top-100 Influential Scholars (2020–2021), and multiple teaching excellence awards from KIT (2017–2020). Teaching & Labs: She teaches courses on database systems, knowledge graphs, and artificial intelligence at RUB. Her lab contributes to projects like SMART-KG and has pioneered federated SPARQL query frameworks. She actively supervises doctoral research in knowledge graph applications and machine learning.

Zakhar Kabluchkoمشاهده پروفایل

استاد

• Stochastic Processes
• Convex and Integral Geometry
• Random Trees and Branching Processes
• +۵ مورد دیگر

Prof. Zakhar Kabluchko is a faculty member at the University of Münster, affiliated with the Institut für Mathematische Stochastik and the Mathematics Münster cluster of excellence. His research focuses on stochastic processes, convex and integral geometry, and probabilistic number theory. He holds a professorship and has contributed to high-impact publications in areas like random polytopes, stochastic geometry, and extreme value theory. His research interests include the study of random analytic functions, stochastic processes in high dimensions, and geometric probability. Notably, he has explored beta-star polytopes, Poisson zero cells, and the interplay between convex hulls and random walks. Kabluchko has also investigated applications of stochastic geometry in statistical mechanics and number theory. Recent work includes studies on high-dimensional limit theorems, propagation of chaos in spin systems, and the geometry of random simplices. He collaborates actively with researchers like Christoph Thäle and Vladimir Vysotsky, contributing to advancements in geometric probability and stochastic analysis.

Julien Poisatمشاهده پروفایل

مدرس

• Probability Theory
• Statistical Mechanics
• Disordered Systems
• +۴ مورد دیگر

Julien Poisat is a Lecturer (equivalent to Assistant Professor) at CEREMADE, Paris-Dauphine University, where he has been affiliated since 2014. Previously, he was a postdoctoral researcher at Leiden University (2012-2014) and completed his Ph.D. at Lyon 1 University (2008-2012). His research focuses on probability theory and statistical mechanics, with specific interests in disordered systems, polymers, random walks, and large deviations. He investigates phenomena such as localization, pinning, and phase transitions in various models including copolymers, charged polymers, and random environments. His recent publications primarily explore rigorous analyses of stochastic systems, with recurring themes including large deviations for random walks, critical behavior of polymer models, and asymptotic properties of disordered systems. Research often involves mathematical techniques from renewal theory, potential theory, and weak convergence methods. He leads the ANR LOCAL grant (2022-2027) focused on localization phenomena in polymers and random walks. Currently advises two doctoral students: Nicolas Bouchot (2021-2024) and Elric Angot (2022-2025). Active in academic community, recently co-organized the 2023 Workshop on Random Walks, Localization and Reinforcement in Paris.

Setareh Maghsudiمشاهده پروفایل

استاد

• Machine Learning
• Wireless Communications
• Edge Computing
• +۷ مورد دیگر

Dr. Setareh Maghsudi is a Professor in the Learning Technical Systems group at the Faculty of Electrical Engineering and Information Technology at Ruhr-University Bochum. She joined Ruhr-University Bochum in August 2023 after serving as an Assistant Professor at the University of Tübingen (2020-2023) and at the Technical University of Berlin (2017-2020). Her academic journey began with an M.Sc. from Kiel University (2008-2010), followed by her Ph.D. and postdoctoral work at Technical University of Berlin (2011-2015), Yale University (2016-2017), University of Manitoba (2015-2016), and Kyushu University (2019). Dr. Maghsudi's research focuses on the application of machine learning to communication networks and distributed systems, with particular emphasis on bandit algorithms, federated learning, and resource allocation in dynamic environments. Her work bridges theoretical machine learning with practical networking challenges, developing algorithms that can adapt to non-stationary environments with partial information. She has made significant contributions to multi-armed bandit frameworks for wireless communications, edge computing, and network optimization. Her recent publications (2023-2025) demonstrate a strong trend toward addressing challenges in integrated sensing and communication (ISAC), federated learning for edge networks, and non-stationary decision-making problems. The publications show expertise spanning theoretical machine learning foundations, wireless communications engineering, and practical implementation for real-world networked systems. Her work increasingly incorporates causal reasoning and robustness considerations into learning frameworks for communication systems. Dr. Maghsudi leads the Learning Technical Systems research group at Ruhr-University Bochum, where she supervises PhD students and postdoctoral researchers working at the intersection of machine learning and communication systems. Her research is supported by various grants focusing on AI for future communication networks. Current projects include developing AI-driven solutions for next-generation communication systems with emphasis on robustness, efficiency, and adaptability in dynamic environments.

• Probability Theory
• Geometric Random Graphs
• Percolation Theory
• +۳ مورد دیگر

Arne Grauer is a researcher in probability theory at the Department of Mathematics, University of Cologne. His work focuses on geometric random graphs, percolation, and stochastic processes in random environments. He completed his PhD in 2022 under Prof. Peter Mörters, exploring ultrasmallness and chemical distance in scale-free geometric random graphs. Education: PhD in Mathematics (2022, University of Cologne), Master’s in Mathematics (2017, University of Münster), Bachelor’s in Mathematics (2015, University of Münster). Research interests include understanding network structures and dynamics, particularly in scale-free and spatially embedded networks. His studies analyze ultrasmall graph distances, infection spread via contact processes, and preferential attachment models. Publications focus on mathematical physics and network science, with contributions to Communications in Mathematical Physics and Journal of Statistical Physics . He co-organized workshops on random geometric graphs and spatial networks.

Tatjana Wingarzمشاهده پروفایل

پژوهشگر

• Secure Machine Learning
• Privacy-preserving Data Processing

Tatjana Wingarz is a Research Associate and PhD student in the IT-Security and Security Management (ISS) research group at the University of Hamburg's Department of Computer Science (MIN). She holds a Master's degree in IT-Security from Ruhr-University Bochum (2020) and a Bachelor's in Media Communication and Computer Science from Rhine-Waal University of Applied Sciences (2017). Her research focuses on Secure Machine Learning and Privacy-preserving Data Processing , addressing challenges in data integrity, cryptographic protocols, and network security. Recent publications highlight contributions to QUIC-aware load balancing, privacy-preserving data sharing, and edge computing middleware. Team & Collaborations: She collaborates closely with Prof. Mathias Fischer and colleagues like Dr. Heiko Bornholdt, Liliana Kistenmacher, and Kevin Röbert. Her work spans interdisciplinary projects in network security, functional encryption, and educational innovation in computer science pedagogy. Contact: tatjana.wingarz@uni-hamburg.de | Office F 624