جست‌وجوی استاد و پژوهشگر

Sebastian Canzlerمشاهده پروفایل

پژوهشگر

• Computational Systems Biology
• Multi-omics Data Analysis
• Systems Toxicology
• +۵ مورد دیگر

Dr. Sebastian Canzler is the Head of the Computational Systems Biology group at the Helmholtz Centre for Environmental Research (UFZ) in Leipzig, Germany. He is affiliated with the Department of Computational Biology & Chemistry and contributes to projects such as multiGSEA software development, XomeTox, and chemical grouping frameworks. Education: Diploma & PhD in Bioinformatics (University of Leipzig, 2011 & 2017) Professional Roles: PostDoc (University of Leipzig, 2017); PostDoc & Head (UFZ, 2018–Present) Research Interests: His work focuses on multi-omics data integration for chemical risk assessment, pathway enrichment analysis, single-cell transcriptomics in systems toxicology, and development of FAIR data management practices. He specializes in refining adverse outcome pathways (AOP) and applying explainable AI to predict chemical effects. Scientific Trends: Recent publications emphasize thyroid toxicity mechanisms, retinal organoid modeling, and computational frameworks for evaluating chemical mixtures. His software tools (multiGSEA, ProteinPrompt) address pathway analysis and protein interaction prediction. Collaborations: Works with Prof. Jörg Hackermüller, Prof. Martin von Bergen, and teams across bioinformatics, ecotoxicology, and exposure science.

Ilhan Mutluمشاهده پروفایل

پژوهشگر

• Environmental Informatics
• Machine Learning
• Graph Databases
• +۴ مورد دیگر

Dr. İlhan Mutlu is a postdoctoral researcher at the Helmholtz Centre for Environmental Research - UFZ in the Department of Computational Biology and Chemistry since 2023. Previously, he worked at TU Dresden (2021-2023) and IAV GmbH (2017-2021). He holds a PhD in Control and Automation Engineering (Istanbul Technical University, 2017) and focuses on data integration , graph databases , and machine learning models for toxicology prediction . His research bridges environmental data analysis with automated systems , particularly in freshwater toxicity assessment and optimal control techniques . Recent projects include ChEOS (toxicity prediction in European waters) and SafePol (pollinator protection). His technical expertise spans Neo4j , CleanGeoStreamR , and ecoKI platform development. Publications emphasize data curation for environmental monitoring, graph-based toxicity tools , and ML-driven chemical risk assessment . His work also involves automated driving systems , including model-free trajectory planning and robust control algorithms . Though no scientific awards are listed, his contributions span interdisciplinary domains combining environmental science with computational engineering .

• 5G/6G Networks
• Wireless Networks
• Mobility Management
• +۵ مورد دیگر

M.Sc. Anna Prado is a Research and Teaching Associate at the Chair of Communication Networks (Prof. Kellerer) at the Technical University of Munich. She holds a B.Sc. in Information Systems and Communication Engineering from Bauman Moscow State Technical University (2017) and an M.Sc. in Communication Engineering from TUM (2020). She is currently pursuing her Ph.D., focusing on mobility management in 5G/6G networks, simulation of wireless systems, and digital twins for 6G. Her research emphasizes minimizing handover occurrences while ensuring smooth user connectivity through optimization and reinforcement learning techniques. Anna's academic role involves contributing to projects like the BMBF-funded 6G-ANNA initiative, which aims to develop holistic 6G systems prioritizing security, sustainability, and flexibility. She collaborates on network architecture design, resource allocation strategies, and resilient communication frameworks. Her work aligns with German technological sovereignty goals, addressing industrial and societal needs through advanced network technologies. Her research interests span 5G/6G networks, wireless resource management, digital twins, and machine learning applications in networks. She has authored/co-authored peer-reviewed papers on topics like admission control, slice dimensioning, energy-efficient edge orchestration, and secure 6G architectures. Her contributions enhance network efficiency, reliability, and adaptability for future communication systems. Anna is actively involved in the FlexComNetsLab and 6G-IP Lab, testing and demonstrating innovative 6G concepts. She participates in conferences and collaborates with industry partners to bridge academic research and real-world deployment.

Marcus Müllerمشاهده پروفایل

استاد

• Polymer Physics
• Soft Matter Physics
• Biophysics
• +۳ مورد دیگر

Prof. Marcus Müller is a Professor of Theoretical Physics at the University of Göttingen's Faculty of Physics, Department of Theoretical Physics. His research employs advanced computational methods to investigate fundamental phenomena in polymer systems, soft matter, and biological membranes, with significant contributions to understanding non-equilibrium dynamics and self-assembly processes. His research portfolio spans: Polymer Physics : Dynamics of polymer melts, block copolymer self-assembly, and phase separation mechanisms Soft Matter Physics : Active matter systems, membrane biophysics, and dissipative structures Computational Physics : Development of specialized simulation techniques including peridynamic-enhanced Fourier spectral methods and slip-spring models Analysis of his 15 most recent publications (2023-2025) reveals a dominant focus on the interplay between processing conditions and nanostructure formation in block copolymers, with expanding applications to battery electrolytes and biological systems. Key trends include the investigation of non-equilibrium pathways in spinodal decomposition, membrane fission/fusion mechanisms, and reaction-driven organization in active liquids, demonstrating strong integration of theoretical modeling with experimental validation. No scientific awards were documented in the available source material. While specific advising relationships and grant details were not provided, his extensive publication record suggests active mentorship of graduate students in computational soft matter physics. The research direction indicates ongoing investigation of fundamental transport phenomena in polymeric systems with applications to energy storage and cellular biophysics. His work appears conducted within computational research groups at the Department of Theoretical Physics, focusing on molecular simulations and theoretical modeling of complex soft matter systems, with particular emphasis on membrane dynamics and polymer self-assembly under non-equilibrium conditions.

Daniel Büscherمشاهده پروفایل

پژوهشگر

• Autonomous Robot Navigation
• Deep Learning
• Computer Vision
• +۱ مورد دیگر

Daniel Büscher is a post-doctoral researcher at the Robot Learning Lab of the University of Freiburg. His work focuses on autonomous robot navigation , deep learning , and probabilistic state estimation . He has contributed to robotics research through projects involving mobile manipulation and audio-visual navigation . Research Interests : Autonomous navigation, deep learning, computer vision, probabilistic estimation Teaching : Lecturer and tutor for Introduction to Mobile Robotics and Robot Mapping (2017–2023) Publication Trends : Recent work emphasizes robot design optimization , language-grounded scene graphs , and uncertainty-aware perception . His research connects reinforcement learning with mobile manipulation and cross-domain navigation challenges.

Dominik Baumannمشاهده پروفایل

استادیار

• Systems and Control Theory
• Machine Learning
• Communication Networks
• +۳ مورد دیگر

Dominik Baumann is an Assistant Professor at the Department of Electrical Engineering and Automation at Aalto University in Espoo, Finland. His research focuses on the interplay of systems and control theory with machine learning and communication networks, with a current emphasis on causal inference in control systems. Education: Diploma in Electrical Engineering from TU Dresden, Germany (2016) PhD from KTH Stockholm, Sweden (2020), supervised by Sebastian Trimpe (Max Planck Institute) and Karl H. Johansson Postdoctoral positions at RWTH Aachen University (1 year) and Uppsala University with Thomas Schön (1 year) Dr. Baumann's research bridges theoretical foundations with practical applications in robotics, wireless networks, and decision-making systems. His work spans safe reinforcement learning, event-triggered control systems, causal inference in dynamical systems, and ergodicity economics perspectives on long-term decision-making. He applies mathematical rigor to address challenges in resource-constrained environments, particularly focusing on safety guarantees and computational efficiency for real-world implementation. His recent publication record demonstrates a strong trajectory in safe learning-based control, with increasing focus on ergodicity economics in reinforcement learning, multi-agent coordination, and human-robot interaction. The research consistently balances theoretical guarantees with practical implementation constraints, particularly in bandwidth-limited wireless control systems and robotics applications. Scientific Awards: Best Paper Award for 'Feedback control goes wireless: Guaranteed stability over low-power multi-hop networks' at ACM/IEEE International Conference on Cyber-Physical Systems (2019) Dr. Baumann maintains extensive international collaborations, evidenced by numerous seminar invitations worldwide including Oxford University, ETH Zürich, University College London, and institutions across Asia. His research program addresses fundamental challenges in cyber-physical systems with applications in industrial automation, robotics, and the Internet of Things, securing research funding for projects focused on safe learning in control systems and wireless cyber-physical systems. His research group at Aalto University develops both theoretical foundations of learning-based control and practical algorithms for real-world deployment, with active software repositories on GitHub related to predictive triggering, causal structure identification, and ergodic reinforcement learning.

• Building Energy Systems
• Machine Learning Applications
• Model Predictive Control
• +۳ مورد دیگر

Martin Rätz is a researcher and team leader at the Institute for Energy Efficient Buildings and Indoor Climate of RWTH Aachen University , where he leads the Building Automation research team since January 2025. His work focuses on integrating advanced technologies like machine learning, IoT, and cloud computing into building automation systems to enhance energy efficiency and operational transparency. M.Sc. in Mechanical Engineering (Energy Engineering specialization), RWTH Aachen University Erasmus studies at Instituto Superior Técnico in Lisbon His research interests include: Model predictive control for building systems Energy-efficient control algorithms Machine learning applications in energy systems IoT integration for smart buildings Cloud computing in building automation Demand-controlled ventilation systems His recent publications demonstrate expertise in: Machine learning model validation Fault detection in district heating networks Energy weather data generation tools AI-driven building system optimization Dynamic ventilation strategies for healthcare settings Scientific honors include: Springorum Denkmünze for academic excellence (2018) Dean's List recognition (2018, 2019) As team leader, he directs projects such as: Monitoring 120 buildings in the OM4ABDO initiative Developing the BUDO standard for data point naming Advancing cloud-based building automation frameworks

• Virtual Reality
• Computer Vision
• Human-Computer Interaction
• +۴ مورد دیگر

Joe K. Kearney is a Professor in the Department of Computer Science at the University of Iowa and the University of Minnesota. His career spans over three decades, focusing on virtual reality, computer vision, and human-computer interaction research. Key affiliations: University of Iowa (Iowa City, IA, USA), University of Minnesota (Minneapolis, MN, USA) Research domains: Virtual environments, perception-action coupling, motion capture systems, pedestrian behavior simulation Research trends show sustained contributions to immersive visualization , autonomous navigation , and human factors in virtual reality . His 2014-2025 work explores AR-based pedestrian safety systems, while earlier studies (1986-2006) established foundational frameworks for virtual environment simulation and optical flow analysis. Long-term collaborations with Jodie M. Plumert (1986-2021), James F. Cremer (1986-2009), and Pooya Rahimian (2015-2017) demonstrate consistent team research in VR cognition and autonomous systems.

• Cybersecurity
• Cyber-physical systems security
• Social network analysis
• +۷ مورد دیگر

Andrey Chechulin is a Professor at the St. Petersburg Federal Research Center of the Russian Academy of Sciences, Institute of Informatics Problems, where he leads research in cybersecurity within the Information Security Department. His work spans over 15 years with more than 80 publications in top-tier security conferences and journals. Dr. Chechulin's primary research interests include cybersecurity, cyber-physical systems security, social network analysis, and bot detection. His work focuses on developing practical methodologies for incident investigation, access control, and vulnerability assessment. He has pioneered approaches for analyzing social media bots, particularly on the VKontakte platform, and developed innovative frameworks for cryptocurrency transaction anomaly detection using neural networks. His publication record shows consistent contributions to major security venues including PDP, COMSNETS, and Sensors, with a notable increase in output since 2018. Recent work demonstrates his adaptation to emerging security challenges in AI-generated content detection and blockchain security. Best Paper Award at PDP 2021 Cybersecurity Research Excellence Award (2019) Dr. Chechulin maintains strong collaborative relationships with Igor V. Kotenko (60 joint publications), Dmitry Levshun, and Maxim Kolomeets. His research often bridges theoretical security concepts with practical implementations for real-world systems, including smart city infrastructure and automotive security applications.

• Set Theory
• Mathematical Logic
• Ontologies
• +۶ مورد دیگر

Domenico Cantone is a Professor in the Department of Mathematics and Computer Science at the University of Catania, Italy. With an extensive publication record spanning from 1987 to 2025, he has established himself as a leading researcher in mathematical logic, set theory, and their applications to computer science problems. His research bridges theoretical foundations with practical applications in ontologies, blockchain technology, and quantum computing. Professor Cantone's research interests primarily focus on set theory and mathematical logic, with significant contributions to computational aspects of these fields. His work has evolved from foundational set theory to practical applications in semantic web technologies, blockchain systems, and quantum algorithms. He has made substantial contributions to decidability problems in set theory fragments, developing decision procedures that have applications in automated reasoning systems. His recent work demonstrates a strategic expansion into interdisciplinary areas, particularly the application of formal methods to blockchain technology and the exploration of quantum computing for string algorithms. The trajectory of Cantone's publication record shows a consistent focus on theoretical foundations while gradually incorporating more applied research directions. His early work concentrated on pure set theory and logic, then expanded to include applications in automated reasoning and ontology representation, and more recently has embraced emerging technologies like blockchain and quantum computing. This evolution reflects both his theoretical depth and ability to identify promising intersections between formal methods and cutting-edge technologies. Professor Cantone has maintained exceptionally productive collaborations throughout his career, most notably with Marianna Nicolosi Asmundo (58 joint publications), Simone Faro (54 publications), Daniele Francesco Santamaria (35 publications), and Eugenio G. Omodeo (35 publications). These long-standing collaborations demonstrate his ability to build and sustain research teams focused on complex theoretical problems. His work has appeared in prestigious venues including Theoretical Computer Science, Journal of Automated Reasoning, and Fundamenta Informaticae, among others.

• Circadian Rhythms
• Chronobiology
• Bioinformatics
• +۱۲ مورد دیگر

Pal Westermark is a researcher and Head of the Department of Bioinformatics and Biomathematics at the Research Institute for Farm Animal Biology (FBN) in Dummerstorf, Germany, a position he has held since 2016. He leads the Chronobiology and Bioinformatics Working Group and has previously held research and leadership roles at the Institute of Theoretical Biology, Charité – Universitätsmedizin Berlin. Doctorate (2005): Models of the Metabolism of the Pancreatic β-Cell, KTH Stockholm, Sweden Master's Degree (1999): Molecular Biotechnology, Uppsala University, Sweden His research focuses on circadian rhythms in animals, regulation of gene expression and metabolic pathways, tissue homeostasis, biogerontology, and the application of time series analysis, control theory, and biostatistics to biological systems. He employs mathematical modeling and bioinformatics to understand the dynamics of biological clocks and their impact on metabolism and physiology. The trends in his recent publications reveal a strong focus on circadian biology, particularly in muscle and liver tissues, using transcriptomic, proteomic, and phosphoproteomic approaches. His work integrates computational modeling with experimental data to dissect the mechanisms of circadian regulation, including promoter architecture, rhythmic degradation, and the effects of exercise. He has also contributed methodological tools like the RAIN algorithm and Seagull for analyzing biological rhythms and high-dimensional data. While no specific scientific awards are mentioned in the provided text, his extensive publication record in high-impact journals such as PNAS , PLoS Genetics , and The Journal of Physiology underscores his significant contributions to the field. Dr. Westermark mentors researchers within his working group and leads a research team focused on chronobiology and bioinformatics. His work is supported by institutional funding, though specific grants are not listed. His research program combines theoretical and computational approaches to advance understanding of biological timing systems. He is actively involved in leading the Chronobiology and Bioinformatics Working Group at FBN, which conducts interdisciplinary research at the intersection of biology, mathematics, and computer science. The team develops and applies computational models and bioinformatics tools to study circadian rhythms and their implications for animal and human health.

Felix Rempeمشاهده پروفایل

پژوهشگر

• Mobility Systems
• Machine Learning
• Data Exploration and Analyses Methods
• +۱ مورد دیگر

Felix Rempe is a Rudolf Diesel Industry Fellow at the Technical University of Munich Institute for Advanced Study (TUM-IAS) , affiliated with the BMW Group in the field of Autonomous Driving . He holds a PhD in Computational Science and Engineering from TU Munich, awarded summa cum laude in 2018, and an M.Sc. in Mechatronics from DHBW Stuttgart in 2014 with Honours. His research focuses on data-driven approaches to traffic engineering and control , leveraging machine learning and sensor data from vehicles for real-time traffic state estimation and prediction. His work explores the intersection of mobility systems and artificial intelligence , particularly in the domains of traffic flow theory and digital twin development for transportation infrastructure. Felix’s publications highlight advancements in data fusion techniques , deep learning architectures , and statistical modeling applied to autonomous driving and urban mobility challenges. 2018: PhD thesis awarded summa cum laude 2014: M.Sc. with Honours award for completing the Honour’s track at TUM 2012: BayLat grant for study exchange program Latin America

Rudolf Weeberمشاهده پروفایل

مدرس ارشد

• Magnetic Gels and Elastomers
• Soft Matter Simulations
• Computational Physics
• +۶ مورد دیگر

Rudolf Weeber is a Senior Lecturer at the Institute for Computational Physics, University of Stuttgart. He specializes in computational physics and soft matter simulations, with a focus on magnetic gels, elastomers, and nanoparticle dynamics. PhD in Physics (2015) from University of Stuttgart Diplom in Physics with specialization in simulation methods His research explores magnetic field-controlled materials, fluid-particle coupling, and simulation software development. He is a key contributor to the ESPResSo molecular dynamics package. Recent publications highlight his work on magnetic gel deformation, nanoparticle transport, and multiscale simulation frameworks. Trends include computational physics, soft matter, and high-performance computing. Weeber's projects span magnetic materials, micro-rheology, and sustainable software development. He has collaborated on EuroHPC systems and stochastic reaction modeling. He is affiliated with the Stuttgart Research Center for Simulation Technology and has developed open-source tools for soft matter research.

Pia Domschkeمشاهده پروفایل

استاد

• Numerical Analysis
• Partial Differential Equations
• Gas Network Simulation
• +۳ مورد دیگر

Pia Domschke is a Professor of Mathematics & Statistics at the Frankfurt School of Finance & Management since 2024, previously serving as a lecturer (2019-2024). Her research focuses on numerical methods for partial differential equations, particularly in gas network simulation and tumor growth modeling. She has held leadership roles in research projects at TU Darmstadt and contributed to DFG-funded Transregio 154 work. Education : Studied mathematics at TU Darmstadt, completed PhD there, and worked as a postdoc at the University of Dundee. Research interests center on hierarchical model adaptation for compressible flow networks and multiscale biological modeling . Her publications demonstrate expertise in adjoint-based error control, entropy-preserving coupling, and computational approaches to cancer invasion. Recent article analysis reveals dual expertise in gas network optimization and biomedical simulations , with methodological contributions to transient modeling, stochastic collocation methods, and multiscale tumor growth analysis. She led the Athene Young Investigator research group at TU Darmstadt and collaborated with international teams on both energy systems and cancer research. Her work spans theoretical developments and real-world applications in engineering and medical sciences.

Sebastian Leviمشاهده پروفایل

پژوهشگر

• Climate Change Politics
• Public Attitudes toward Climate Policy
• Quantitative Methods
• +۳ مورد دیگر

Dr. Sebastian Levi is a Postdoctoral Researcher at the Hertie School ’s Centre for Sustainability , focusing on climate change politics and public attitudes. He holds a doctorate from the Berlin Graduate School of Transnational Studies, an MPhil in International Relations from the University of Oxford, and a BA in Political Science from Freie Universität Berlin. His research examines how political developments shape public preferences on climate policy. Key areas include the influence of social and political contexts on belief in human-made climate change and the design of effective climate policies. He contributes to the ARIADNE project, a BMBF-funded initiative analyzing Germany’s climate policy response, with a focus on public attitudes and institutional capacity for emission neutrality. Dr. Levi employs quantitative and computational methods , including machine learning, to study policy effectiveness and public opinion dynamics. His work has been cited in the UN IPCC report, underscoring its impact on global climate discourse. Prior roles include a Visiting Assistant in Research at Yale Program on Climate Change Communication and a researcher at the Mercator Research Institute on Global Commons and Climate Change (MCC). His research spans topics such as carbon pricing determinants, climate policy instrument mixes, and regional disparities in climate policy acceptance. He collaborates with interdisciplinary teams to address systemic challenges in climate governance and sustainable development.