جست‌وجوی استاد و پژوهشگر

• Gravitational Waves
• General Relativity
• Compact Binaries
• +۴ مورد دیگر

Dr. Jan Steinhoff is a Group Leader leading the research group Astrophysical and Cosmological Relativity at the Max Planck Institute for Gravitational Physics (Albert Einstein Institute) in Potsdam. He holds a diploma in Physics (2006) and PhD (2010) from Friedrich-Schiller-Universität Jena, with doctoral research on canonical formulations of spin in general relativity under Prof. Gerhard Schäfer. Following postdoctoral positions at Instituto Superior Técnico (Lisbon) and AEI, he established his independent research group in 2019. His primary research focuses on analytical predictions for compact binary dynamics and gravitational wave emissions. Key areas include: Spin-induced spacetime twisting and orbital precession effects Tidal deformation and oscillation modes in neutron stars Deviations from Einstein's gravity in gravitational wave signatures Effective field theory frameworks for binary systems Waveform modeling (especially effective-one-body approaches) Steinhoff's publications demonstrate consistent focus on analytical relativity methods applied to gravitational wave astrophysics. Recent work emphasizes: Tidal interactions in neutron stars within modified gravity theories High-precision post-Newtonian calculations Waveform development for next-generation detectors Tests of general relativity using LIGO-Virgo observations He leads the AEI's efforts in developing perturbative solutions to gravitational two-body problems, leveraging synergies with high-energy physics techniques including scattering amplitudes and effective field theories.

• Molecular Physics
• Ultrafast Dynamics
• X-ray Imaging
• +۳ مورد دیگر

Mai S. is a researcher at Deutsches Elektronen-Synchrotron (DESY) working in the Photon Science division. Their research focuses on using X-ray free-electron lasers to study ultrafast molecular dynamics and photochemical processes, with particular emphasis on molecular imaging techniques and photo-protection mechanisms relevant to biological systems. Mai S. specializes in Coulomb explosion imaging , a cutting-edge technique that enables direct observation of molecular structural changes during photoexcitation events. Their work bridges physics and chemistry to investigate how heterocyclic molecules like 2-thiouracil redistribute photoenergy into electronic and nuclear degrees of freedom. This research has significant implications for understanding DNA photo-protection from UV damage and developing organic photocatalysis applications. Recent publications demonstrate expertise in capturing symmetry reduction during internal conversion processes using advanced X-ray methodologies. The 2025 Nature Communications paper provides unprecedented insights into ultrafast molecular dynamics, representing a major contribution to the emerging field of attosecond chemistry. Mai S.'s work exemplifies the application of DESY's world-class X-ray facilities to solve complex problems in molecular science. Mai S. is part of an international collaborative team utilizing DESY's photon science infrastructure to push the boundaries of molecular imaging. Their research contributes to the development of new methodologies for visualizing molecular processes with both high temporal ( femtosecond ) and spatial ( atomic ) resolution, enabling scientists to observe previously inaccessible quantum mechanical phenomena in complex molecular systems.

Walter Binderمشاهده پروفایل

استاد

• Performance Analysis
• Java Virtual Machine
• Parallel Computing
• +۵ مورد دیگر

Walter Binder is a Professor at the University of Lugano, Switzerland, specializing in performance analysis and optimization of Java-based and parallel systems. He has actively contributed to academic committees in conferences such as GPCE, CGO, and ‹Programming›, focusing on virtual machine efficiency, compiler design, and benchmarking methodologies. His research centers on performance profiling tools for the Java Virtual Machine (JVM), including the development of the P3 profiler suite for parallel applications and the Renaissance benchmark suite. Key areas of interest include concurrency, synchronization, dynamic compilation, and multi-language program analysis, with applications in big data processing and stream computing frameworks. Recent publications highlight trends in compiler-level event profiling, AST interpreter optimization, and SQL-to-stream benchmark generation. These works span subfields like SIMD vectorization, task granularity analysis, and native-image startup performance, emphasizing platform independence and low overhead. Notable tools and methodologies developed by Binder have been instrumental in advancing JVM-based parallel computing research. His contributions extend to automated large-scale analysis of public code repositories and performance coaching for fork/join applications.

Simone Brodersمشاهده پروفایل

استاد مهمان

• English Literature of the 'Long' Eighteenth Century
• Contemporary British Literature and Culture
• Digital Humanities
• +۹ مورد دیگر

PD Dr. Simone Broders is a Visiting Professor at the University of Koblenz for the summer semester 2024 and teaches English Literature and Culture at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). She has held interim professorships at the University of Cologne and University of Koblenz , and works as a Visiting Researcher at OVGU Magdeburg since 2023. Current Affiliation: FAU Erlangen-Nürnberg (Chair of English Studies: Literature) Academic Credentials: Dr. phil. habil (2018), Dr. phil. (2007), Magister Artium (2004) Her research focuses on English literature and culture across historical periods from the 'Long' Eighteenth Century to 21st-century works, with special emphasis on: Curiosity as epistemological driver in Enlightenment and Romanticism Digital Humanities methodologies Transfer processes between literature and other media (film, television, graphic novels) Parallel and alternative societies in contemporary literature Memory studies and post-imperialism Gender representation and knowledge boundaries Key publication: The Age of Curiosity (De Gruyter, 2021) analyzing curiosity's role in 18th-century literature. She co-edited Paragesellschaften (2021) examining alternative social formations. Scientific Awards DAAD Grant 2019 for 'The Curious Self' research DAAD Grant 2014 for 'Shakespeare in Science Fiction' Alfred-Vinzl-Stiftung Grant 2012 Konrad-Adenauer-Stiftung PhD Scholarship 2004-2006 Dr. Broders contributes to the DFG-funded 'Para-Societies' research network (2018-2021) and serves as peer-reviewer for academic journals. She organizes conferences like 'The Ethics and Narratives of Non-Knowledge' (2022) and contributes to public science events like the Lange Nacht der Wissenschaften.

Karsten Rinkمشاهده پروفایل

پژوهشگر

• Environmental Informatics
• Geospatial Data Visualization
• Hydrological Modeling
• +۳ مورد دیگر

Karsten Rink is a researcher at the Helmholtz Centre for Environmental Research - UFZ in Leipzig, Germany. He leads the "Data Integration and Visualisation" project group within the Department of Environmental Informatics . His work focuses on environmental data visualization , geospatial data management , and software development for OpenGeoSys - a simulation framework for environmental processes. Key projects: OpenGeoSys Data Explorer , TESSIN VISLab , MEVA (Meteorological Data Visualization) Major collaborations: Mont Terri Underground Research Laboratory , Poyang Lake Basin , Dead Sea Water Resources Research Highlights include developing Virtual Geographic Environments for analyzing: Hydro-Meteorological Extremes in urban systems Multi-Compartment Water/Solute Dynamics in large catchments Energy-Water Nexus challenges Groundwater Balance in arid regions Technical Innovations feature Unity-based 3D visualization workflows, multi-device meteorological data validation , and cross-platform data conversion tools between OpenGeoSys, ParaView, and VTK. Publications (2023-2014) demonstrate expertise in: Environmental software frameworks Scientific visualization Hydrogeological modeling Climate-urban interactions Subsurface energy systems Water management digitization Collaborative Projects span from German Unity Anniversary visualization to Dead Sea groundwater studies , integrating with initiatives like MOSES (Modular Observation Solutions for Earth Systems) and Digital Earth .

• Satellite Geodesy
• Earth Gravity Field
• GRACE-FO Mission
• +۳ مورد دیگر

Grigorios Kalimeris is a researcher at the Chair of Astronomical & Physical Geodesy within the Engineering Institute for Astronomical and Physical Geodesy at Technical University of Munich. His work focuses on satellite geodesy and Earth gravity field analysis, with particular expertise in processing data from the GRACE-FO mission. His research interests center on Earth gravity field modeling, with specific focus on the impact of Laser Ranging Interferometer (LRI) technology on gravity field solutions. His work examines how LRI measurements affect the high-frequency domain and higher harmonic degrees of static Earth gravity field models, contributing to improved understanding of Earth's mass distribution and its temporal variations. Dr. Kalimeris' publication record shows a consistent trajectory of research from 2022 through 2025, with multiple conference presentations at major geodetic events including the IAG Scientific Assembly and IUGG General Assembly. His work demonstrates increasing sophistication in analyzing the interplay between different instrument systems on the GRACE-FO mission. He is actively involved in several major research initiatives including the DFG Research Unit NEROGRAV, DFG Research Training Group UPLIFT, and multiple ESA projects (Baltic+ Project Theme 5, MAGIC/Science, and QSG4EMT). These projects focus on advancing geodetic techniques for Earth observation and gravity field modeling. Dr. Kalimeris serves as a supervisor for graduate students, currently guiding Master's research including Shirui Yan's 2025 thesis on GRACE-FO Line-of-Sight Gravity Differences. His research has practical applications for monitoring Earth system mass variations related to climate change and geophysical processes.

• Data Science
• Network Science
• Computational Social Science
• +۵ مورد دیگر

Yu-Ru Lin is an Associate Professor at the School of Computing and Information , University of Pittsburgh , and serves as Research & Academic Director at the Institute for Cyber Law, Policy and Security (Pitt Cyber) . With secondary appointments in Political Science, Computer Science, and the Intelligent Systems Program, their interdisciplinary work bridges computational methods with social science inquiry. Research interests focus on: Social and political network analysis Computational social science Data mining and visualization Digital accountability in political communication Policy diffusion analytics Trust-distrust dynamics in networked societies Key research themes include: Developing network theories for misinformation and extremism Designing visual analytics for policy diffusion and group bias detection Studying collective behavior during emergencies Creating computational tools for social data analysis Major grants include NSF awards for: Public policy diffusion analytics COVID-19 misinformation mitigation Urban mobility and smart city initiatives Understanding extremism in cyber-social spaces Scientific leadership roles: Editor-in-Chief of ICWSM Editorial board member at Frontiers in Big Data, EPJ Data Science, PLOS ONE, and Nature Scientific Reports Co-chair roles at KDD Humanitarian Mapping Workshop, WWW Web & Society Track, and multiple SBP-BRiMS graduate programs As founder of the Pitt Computational Social Dynamics Lab (PICSO LAB) , they lead research on social media analysis, network modeling, and urban informatics through projects like PittSmartLiving – a $1.4M NSF-funded initiative exploring real-time transit incentives and community engagement.

Alexander von Rohrمشاهده پروفایل

پژوهشگر

• Robotics
• Machine Learning
• Bayesian Optimization
• +۴ مورد دیگر

Alexander von Rohr is a postdoctoral researcher at the Technical University of Munich , affiliated with the Learning Systems and Robotics Lab . Previously, he was a doctoral researcher at the Max Planck Institute for Intelligent Systems and RWTH Aachen University , supported by IAV . His educational background spans Computer Science (RWTH Aachen), Electrical Engineering (BHT Berlin), and University of Lübeck . Research Focus : Embodied AI, Bayesian optimization, risk-aware reinforcement learning, robust control, probabilistic models, data-driven controller synthesis. His recent publications (2024-2025) emphasize event-triggered learning for time-varying systems, diffusion models with constraints , and robust safety via entropy regularization in RL. These works demonstrate applications in robot manipulators , digital twins , and underactuated systems . Awards include the Best Reviewer Award at AISTATS 2025 . Collaborations include Prof. Sebastian Trimpe and Angela P. Schoellig , with co-authorships on 15 recent articles. His lab focuses on probabilistic control for dynamical systems with formal guarantees.

Birgit Terhorstمشاهده پروفایل

استاد

• Soil Geography
• Landscape Change
• Quaternary Landscape Development
• +۵ مورد دیگر

Univ.-Prof. Dr. Birgit Terhorst is Professor of Physical Geography and Soil Science at the Institute of Geography and Geology, University of Würzburg, where she has held this position since 2008. She serves as the trusted advisor for the German Research Foundation (DFG), Women's Representative of the Philosophical Faculty, and member of the doctoral committee of the Philosophical Faculty. Her research focuses on soil geography, landscape development, and natural hazards with a particular emphasis on Quaternary processes. Professor Terhorst's research interests span multiple interconnected fields including soil geography , landscape change , Quaternary landscape development , natural hazards (particularly slope stability and landslides) , loess stratigraphy , and paleosols . Her work integrates field studies with laboratory analyses to reconstruct past environmental conditions and understand contemporary geomorphological processes. She has made significant contributions to understanding periglacial cover beds, loess-paleosol sequences, and their implications for paleoclimate reconstruction. Her recent publications demonstrate a strong focus on mid-latitude slope deposits, loess chronology, and climate change impacts on geomorphological processes. The research spans from detailed micromorphological studies of paleosols to large-scale assessments of natural hazards under changing climatic conditions. Her work shows increasing integration of remote sensing, GIS technologies, and interdisciplinary approaches to address complex questions in physical geography and soil science. Since 2018: Deputy Chair of the Association for Geography at German-speaking Universities and Research Institutions (VGDH) Since 2011: Member of the German Stratigraphic Commission, 'Quaternary Subcommission' Since 2007: Chair of the Paleopedology Working Group, German Soil Science Society 2014-2018: Co-Editor of the journal 'Landslides', Springer-Verlag 2014-2017: Member of the DFG Senate Commission for Future Tasks in Earth Sciences (SK ZAG) Professor Terhorst leads the Geomorphological-Soil Science Laboratory at the University of Würzburg, which recently expanded with new equipment for measuring carbon and nitrogen in soil samples. Her research group conducts fieldwork in various locations including the university forest (Uniwald), where they study soil carbon storage, retention basins for flood management, and soil hydrological properties. The team collaborates with municipal authorities, other university departments, and international partners on projects addressing climate change adaptation and natural hazard management.

• Cybersecurity
• Internet of Things (IoT)
• Machine Learning
• +۵ مورد دیگر

Andrea Bernardini is an Associate Professor in the Department of Computer Science at the University of Udine, Italy. With a research career spanning over 15 years, Bernardini has established himself as a prominent researcher in cybersecurity, machine learning, and medical applications of AI. His work bridges theoretical computer science with practical applications in healthcare, IoT security, and wireless sensing technologies. Dr. Bernardini's research focuses on applying artificial intelligence techniques to solve complex problems in cybersecurity and medical diagnostics. His work spans several key areas including IoT security, where he develops methods for analyzing vulnerable internet-connected devices; medical AI, where he applies deep learning to diagnose conditions like sleep apnea and Parkinson's disease; and wireless sensing technologies that use Wi-Fi signals for person identification and monitoring. His approach often combines multiple technical domains to create innovative solutions for real-world problems. His recent publications demonstrate a strong trend toward interdisciplinary research that combines cybersecurity with healthcare applications. Bernardini's work on 5G network security, Wi-Fi based person identification, and EEG analysis for Parkinson's disease diagnosis shows his ability to bridge multiple technical domains. His research often involves collaboration with medical professionals and industry partners to ensure practical applicability of theoretical advances. Dr. Bernardini has been actively involved in several significant research projects focused on cybersecurity frameworks for emerging technologies. His work with the ITASEC and SERICS conferences indicates strong engagement with the European cybersecurity research community. Recent projects include developing meta-search engines for IoT device posture analysis and ontological approaches to 5G service cybersecurity, addressing critical infrastructure protection needs.

• Distributed Stream Processing
• Data Stream Analytics
• Database Optimization
• +۳ مورد دیگر

Dr. Boris Novikov is a prominent Russian computer scientist affiliated with St Petersburg University and the Higher School of Economics . His research focuses on distributed stream processing, temporal databases, and XML query optimization. Key collaborators include Artem Trofimov , Elena Mikhailova , and Anna Yarygina . Research Areas : Distributed Systems (stream processing, substream management) Database Optimization (vertical partitioning, XML caching) Temporal Data Management Machine Learning (concept drift detection) His recent work on distributed stream processing (2023-2022) explores substream bounding, deterministic models, and resource allocation strategies. Earlier contributions (2012-2008) focused on XML query performance, similarity indexing, and access control frameworks. Technical Trends : Event time alignment in distributed architectures Dynamic residual projection for cybersecurity Bi-objective optimization in database systems Speculative execution with conflict resolution Incremental Lagrangian dual solutions Matrix clustering for partitioning problems

• Database Systems
• Query Processing
• Data Stream Management
• +۵ مورد دیگر

Mirek Riedewald is a Professor in the Department of Computer Science at Northeastern University's College of Engineering. With a prolific publication record spanning from 1999 to 2025, he has established himself as a leading researcher in database systems, particularly in query processing, join algorithms, and exploratory search. His work bridges theoretical database foundations with practical applications in data visualization and data lake management. Dr. Riedewald's research focuses on innovative approaches to database query processing, with recent work emphasizing ranked enumeration algorithms, relational diagram visualization, and data lake disambiguation. His publications in top-tier venues like SIGMOD, VLDB, and ICDE demonstrate his significant contributions to the field. He has developed novel techniques for efficient computation of quantiles over joins, any-k algorithms for ranked enumeration, and relationship-based semantic table union search through his SANTOS system. His recent publications reveal a growing interest in the intersection of database systems with fairness considerations, as seen in his work on fixing top-k rankings that lack individual fairness. He also explores the visualization of complex database queries through relational diagrams, making query understanding more accessible. His research has evolved from traditional database topics like data cubes and stream processing to more contemporary challenges in large-scale data management and analysis. Dr. Riedewald has maintained a strong collaborative network, with frequent co-authors including Wolfgang Gatterbauer (31 papers), Johannes Gehrke (23 papers), and Nikolaos Tziavelis (15 papers). His work demonstrates both theoretical depth and practical relevance, addressing real-world challenges in data management systems. His research group has made significant contributions to exploratory search in databases through the ExploreDB workshop series, which he co-organized for multiple years. He has also contributed to important reference works, including chapters in the Encyclopedia of Database Systems on topics like event and pattern detection over streams and database techniques for scientific simulations.

Nicholas Gaoمشاهده پروفایل

پژوهشگر

• Graph Neural Networks
• Quantum Chemistry
• Machine Learning
• +۳ مورد دیگر

Nicholas Gao is a researcher at the Technical University of Munich (TUM) within the Department of Computer Science's Data Analytics and Machine Learning group (I26), working under Prof. Stephan Günnemann. His research bridges machine learning and quantum chemistry, specializing in graph neural networks for molecular simulations and ab-initio quantum computations. His academic background includes: M.Sc. in Computer Science from TUM (2017-2020), thesis: Fast and Flexible Temporal Point Processes using Triangular Maps (top 10%, high distinction) B.Sc. in Computer Science from Technical University of Brunswick (2014-2017), thesis: Visualizing the IoT with Mixed Reality (top 10%) Gao's research centers on graph-based machine learning for quantum chemistry , developing novel approaches to solve many-electron Schrödinger equations and model potential energy surfaces. His work integrates graph neural networks with neural wave functions to enable efficient ab-initio simulations, addressing fundamental challenges in computational chemistry through deep learning innovations. His 2020-2024 publications reveal a clear trajectory toward solving quantum chemistry problems using geometric deep learning, with increasing focus on many-body physics and electronic structure theory. Key contributions include neural Pfaffians for Schrödinger equations (NeurIPS 2024 oral) and sampling-free potential energy surface networks (ICLR 2023), demonstrating consistent innovation at the ML-chemistry intersection. Scientific recognition includes: Deutschlandstipendium from TUM (2019) Deutschlandstipendium from TU Brunswick (2016) Gao currently focuses on research without listed advisees or grants. As a core member of TUM's I26 research group, he contributes to projects in robust machine learning, graph analytics, and efficient ML systems for scientific computing, maintaining active collaboration within the group's quantum chemistry and molecular modeling initiatives.

Ulrike Grittnerمشاهده پروفایل

استاد

• Medical biometrics
• Public Health
• Stroke research
• +۴ مورد دیگر

Ulrike Grittner serves as Deputy Acting Director of the Institute and Head of the Observational Studies and Registry Data Working Group at the Institute of Biometry and Clinical Epidemiology, Charité – University Medicine Berlin. She has been a scientific employee at the Institute since 2002 and has also held positions at Centogene AG (2016-2022) and the Center for Stroke Research Berlin (2012-2017). Dr. Grittner completed her Habilitation at the Institute for Public Health, Charité – University Medicine Berlin in 2017 with her thesis titled "Methodological Problems in Observational Studies: Measuring Socio-economic Status and Alcohol Consumption." She earned her Doctor of Philosophy (Dr. phil.) from Humboldt-University Berlin in 2006 (magna cum laude) and completed her First State Examination for the office of Studienrat in Mathematics and Visual Arts in 1999. Her research expertise spans medical biometrics and public health, with specific focus on stroke and alcohol epidemiology. Dr. Grittner's methodological specialties include long-term studies, analysis of clustered data/mixed models, and propensity score matching. She is proficient in statistical programming with R, SAS, STATA, and SPSS. Her work demonstrates a strong commitment to both theoretical methodological development and practical application in clinical settings. With 294 publications documented in PubMed, her research output shows consistent productivity from 2005 through 2025, with increasing publication rates in recent years. Her work spans multiple disciplines including neurology, public health, biostatistics, and epidemiology, with particular emphasis on stroke research, alcohol epidemiology, and methodological approaches to observational studies. Dr. Grittner is actively involved in professional societies including the Kettil Bruun Society for Social and Epidemiological Research on Alcohol and the International Biometric Society (German Region). She also serves on ethics committees for Charité and the State of Berlin, contributing her methodological expertise to ethical review processes. Her leadership as Deputy Acting Director of the Institute reflects her standing in the academic community. Through her work in biometric consulting, study planning and evaluation, she plays a crucial role in supporting clinical research at Charité. Her research has evolved from early work in educational psychology to her current focus on medical biometrics and clinical epidemiology, demonstrating both breadth and depth of expertise.

• Political Culture Research
• Political Attitude Research
• Participation Research
• +۶ مورد دیگر

Toralf Stark is a researcher and Managing Director of the Faculty of Social Sciences at the University of Duisburg-Essen. He holds a doctorate in Social Sciences and has been working in the field of Political Science with a focus on Comparative Politics since 2009 under Prof. Dr. Susanne Pickel. Education: Doctorate in Social Sciences, University of Duisburg-Essen (2015), dissertation: 'Determinants of Political Behavior - (Un)conventional Participation and Behavior-shaping Attitudes' Master's degree in Political Science, Communication Science, and Economics, University of Greifswald (2002-2009) Studies in Political Science and Economics, University of Ljubljana (2006) Dr. Stark's research focuses on political culture, political attitudes, and participation patterns across different political regimes. His work examines how democratic legitimacy is constituted discursively and how complex legitimation processes operate within social and political structures. He has made significant contributions to understanding the erosion of traditional legitimacy patterns and their consequences for governance capacity in contemporary political systems. His recent publications reveal an evolving research trajectory from foundational studies on political participation toward more sophisticated analyses of democratic configurations and their normative dimensions. Stark's work increasingly integrates methodological innovation with theoretical depth, particularly in measuring democratic understanding across diverse cultural contexts. As an active member of the German Political Science Association (DVPW), Stark serves on the Speakers' Council of the Working Group 'Democracy Research' and the Section 'Comparative Politics.' His academic service includes editorial contributions to major publications in the field and organization of international scholarly events. Dr. Stark teaches courses in comparative politics, European integration, and methodology, emphasizing both theoretical frameworks and empirical analysis. His teaching materials reflect his research expertise, particularly in political participation and democratic quality assessment.