جست‌وجوی استاد و پژوهشگر

Burkhard Heerمشاهده پروفایل

استاد

• Public Economics
• Distributional Macroeconomics
• Optimal Taxation
• +۳ مورد دیگر

Burkhard Heer is a full Professor of Public Finance at the University of Augsburg 's Faculty of Business and Economics . He previously held academic positions at the Universities of Bolzano (2004-2012), Bamberg (2001-2004), Innsbruck (2001), and Ludwig Maximilian University of Munich (2000-2001). He earned his Ph.D. and habilitation from the University of Cologne in 1996 and 2000 respectively. Research Affiliations : CESifo (Munich), Netspar (Tilburg) Research Interests span public economics , distributional macroeconomics , and dynamic general equilibrium (DSGE) modeling . His work explores optimal taxation , social security systems , business cycles , and macroeconomic policy analysis through computational methods. Recent Publications demonstrate expertise in DSGE modeling (3rd ed., 2024), demographic economics , taxation-automation dynamics , and pension systems across aging economies. He frequently employs computational methods for macroeconomic analysis and policy simulation . Scientific Recognition : Listed among top 100 German international economists by Handelsblatt (2010, 2011). Affiliated with leading research networks: CESifo and Netspar . Teaching includes masters-level macroeconomics , public finance , and predictable generational models at undergraduate/graduate levels. The chair offers thesis supervision in public economics and macroeconomic policy topics.

• Computerized Tomography
• Radon Transform
• Mathematical Imaging
• +۴ مورد دیگر

Matthias Beckmann is an active researcher specializing in mathematical imaging, with a strong focus on the Radon Transform and its applications in computerized tomography and image processing. His work spans theoretical developments, algorithm design, and practical implementations in medical and computational imaging. He has established significant collaborations with researchers across multiple institutions, particularly with Ayush Bhandari, Felix Krahmer, and Robert Beinert. Beckmann's research primarily centers on the Modulo Radon Transform, a specialized area within mathematical imaging that addresses challenges in high-dynamic-range tomography and limited data scenarios. His work bridges theoretical mathematics with practical computational methods, developing novel inversion formulas, reconstruction algorithms, and classification techniques. He has made significant contributions to understanding the properties of the Modulo Radon Transform, developing Fourier-domain inversion methods, and creating normalized transforms that provide invariance and robustness in image classification tasks. Analysis of Beckmann's publication trends reveals a consistent progression from theoretical foundations to practical applications. His early work established the mathematical framework for the Modulo Radon Transform, while more recent publications demonstrate applications in machine learning, optimal transport theory, and specialized imaging scenarios like thermogram analysis of watermarks in manuscripts. His research shows increasing integration of neural network approaches with traditional mathematical imaging techniques, particularly in addressing indirect measurement problems. Beckmann has contributed to multiple prestigious journals including SIAM Journal on Imaging Sciences, SIAM Journal on Mathematics of Data Science, and IEEE Transactions on Computational Imaging, demonstrating the significance and recognition of his work within the mathematical imaging community. His publications span conference proceedings, journal articles, and technical reports, showing versatility in communicating research findings to different academic audiences. Through his collaborations and publication record, Beckmann appears to be actively involved in research teams focused on computational imaging and mathematical methods for image processing. His work on lecture notes suggests involvement in educational activities related to computerized tomography, though specific teaching roles or institutional affiliations are not explicitly documented in the available publication records.

Klaus von Schwartzenbergمشاهده پروفایل

پژوهشگر

• Plant Physiology
• Phycology
• Aquatic Ecophysiology
• +۳ مورد دیگر

Klaus von Schwartzenberg serves as a Research Group Leader in Aquatic Ecophysiology and Phycology at the University of Hamburg's Faculty of Mathematics, Computer Science and Natural Sciences, Department of Biology, Institute of Plant Sciences and Microbiology (IPM). He works from the Otto Warburg House, Room 2.124, and leads research focused on algae, plant physiology, and cytokinin metabolism. His research interests center on aquatic ecophysiology and phycology, with particular expertise in algae collections (especially the Microalgae and Zygnematophyceae Collection Hamburg - MZCH), plant hormone research (particularly cytokinins), moss biology (especially Physcomitrella patens ), and the evolutionary relationships between algae and land plants. His work bridges fundamental plant physiology with ecological and evolutionary perspectives. Analysis of his recent publications reveals a strong focus on Zygnematophyceae (a group of streptophyte algae closely related to land plants), algal genomics, plant hormone signaling, and the development of molecular tools for studying non-model algal systems. His research demonstrates how algae collections serve as critical resources for evolutionary and ecological studies. Dr. von Schwartzenberg has received significant recognition through his extensive publication record spanning multiple decades, though specific awards are not listed in the available materials. His work appears in high-impact journals across plant science, molecular biology, and evolutionary biology. He mentors doctoral students, including Atiqur Rahaman, and collaborates with technical staff like Sigrid Körner. His research group works closely with Prof. Dr. Dieter Hanelt's group, indicating strong collaborative networks within the department. The Microalgae Collection (MZCH) serves as a central resource for his research program.

Jochen Fründمشاهده پروفایل

استاد

• Ecological network analysis
• Mutualistic interactions
• Antagonistic interactions
• +۸ مورد دیگر

Professor Jochen Fründ is a Professor of Zoology specializing in Organismic Interactions at the University of Hamburg, where he leads the Animal Network Ecology research unit within the Institute of Animal Cell and Systems Biology. His work focuses on understanding complex ecological networks and species interactions across various ecosystems. Dr. Fründ's educational background includes a Diplom in Biology from the University of Würzburg (2007) and a Dr. rer. nat. from the University of Göttingen (2008-2011), supported by a DBU scholarship. His academic journey includes postdoctoral positions at the University of Göttingen (2012), UC Davis (2013), University of Guelph (2013-2015), and the University of Freiburg (2015-2023) before becoming a professor at the University of Hamburg in 2023. Professor Fründ's research centers on ecological network analysis and modeling, with particular expertise in mutualistic and antagonistic interactions of animals including pollinators, seed dispersers, herbivores, parasitoids, and predators. His work spans multiple areas of community ecology with a special focus on insect biodiversity and the relationship between biodiversity and ecosystem function . His innovative approaches to studying species interactions across vertical and horizontal spatial dimensions have significantly advanced our understanding of ecological networks. His publication record demonstrates expertise across multiple dimensions of ecological network theory and application. Key research themes include plant-pollinator interactions, cross-ecosystem comparisons of species interactions, and the effects of biodiversity on ecosystem processes. His work often bridges theoretical ecology with practical conservation applications, particularly in agricultural and forest ecosystems. Professor Fründ has established himself as a leading researcher in ecological network analysis, with contributions spanning methodological advances in network comparison techniques to empirical studies of species interactions across diverse ecosystems. His work on "dissimilarity of species interaction networks" has provided important methodological frameworks for the field. He leads the Animal Network Ecology research unit at the University of Hamburg, where his team investigates complex ecological networks using both empirical and theoretical approaches. His research has important implications for biodiversity conservation and ecosystem management in the face of global environmental change.

Kolja Egerمشاهده پروفایل

استاد

• Distributed Energy Systems
• Smart Grids
• Energy Automation
• +۳ مورد دیگر

Kolja Eger serves as Professor of Information Technology for Distributed Energy Systems at Hamburg University of Applied Sciences, affiliated with the Faculty of Engineering and Computer Science and Department of Information and Electrical Engineering since October 1, 2021. His appointment follows extensive industry experience at E.ON and Siemens where he led critical energy sector initiatives. Eger earned his doctorate from TU Hamburg-Harburg after completing studies in information and communication technology at the University of Duisburg-Essen and University of Brisbane. His research integrates information technology with energy infrastructure, focusing on distributed energy systems, smart grid architectures, and electromobility data analysis. Current projects include EcoCharge and SimCyberGrid, with active supervision of master's theses through industry collaborations in the energy sector. An open thesis topic examines public electromobility datasets. Eger previously held leadership roles including Head of Enterprise Architecture Energy Networks at E.ON Digital Technology, where he directed IT architecture development for energy networks while implementing innovations across meter data analytics, energy automation, and future internet frameworks.

Felix Süttmannمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Bayesian Statistics
• Meta-Research
• +۷ مورد دیگر

Felix Süttmann is an applied statistician affiliated with Georg-August-University Göttingen and works at the German Institute for Economic Research (DIW Berlin) since 2022. He focuses on survey methodology, including nonresponse modeling, mixed-mode effects, and complex weighting, while also engaging with Bayesian statistics and machine learning applications. Doctoral candidate at Berlin Graduate School of Social Sciences Previously worked as a sampling statistician at the International Association for the Evaluation of Educational Achievement (IEA) for TALIS Research interests span natural language processing, Bayesian modeling, and sustainability, with a strong emphasis on methodological rigor in survey research and econometrics. His work at DIW involves improving nonresponse adjustment factors using ML tools and developing stand-alone weights for refugee samples. Recent publications address sampling techniques in SOEP, nonresponse correction, and weighting methodologies for migration studies, alongside his 2020 work on deep learning for NLP. His methodological contributions include copula-based Bayesian hierarchical models for sample selection. Lectures and presentations cover topics like nationwide household sampling, survey mode preferences, and record linkage weighting adjustments at conferences such as the European Survey Research Association (ESRA) and the Society for Longitudinal and Life Course Studies (SLLS).

Winfried Gerlingمشاهده پروفایل

استاد

• Photography theory and practice
• Digital media studies
• Intermedial design
• +۵ مورد دیگر

Professor Winfried Gerling at University of Applied Sciences Potsdam's Design Department specializes in Concept and Aesthetics of New Media. His research explores photography theory and practice, digital media environments, and intermedial design through projects like the Volkswagen Stiftung-funded research college SENSING: Zum Wissen sensibler Medien . As former Dean of the Design Department (2012-2014) and DFG Research Training Group member, he bridges academic leadership with media innovation. Education: Master of Fine Arts (Installation/Photography), Berlin University of the Arts (1994) Research: Screen image analysis, companion technologies, media forensics His publications since 2015 examine digital photography's epistemology, including Environmental Selfies (2022) and Screen-Images (2022). Current work focuses on: Post-photography screen image practices Automated visual documentation Media precarity and paradoxes Companion technology aesthetics Digital spatiality and temporality Self-documentation in crisis contexts Notable award: 1998 Europrix-Multimedia-Art nomination for Martin Luther CD-ROM . He co-founded multimedia produktionen in berlin (1996) and directed 30+ international exhibitions since 1991.

• Theoretical Computer Science
• Algorithms
• Approximation Algorithms
• +۷ مورد دیگر

Shaofeng Jiang is an Assistant Professor at Peking University, affiliated with the School of Computer Science and the Center on Frontiers of Computing Studies. He previously held an assistant professor position at Aalto University and was a postdoctoral researcher at the Weizmann Institute of Science under Robert Krauthgamer. He earned his PhD from the University of Hong Kong under Hubert Chan and completed his bachelor's at Shandong University. PhD: University of Hong Kong, supervised by Hubert Chan Bachelor's: Shandong University His research lies in theoretical computer science, focusing on algorithm design for massive and high-dimensional data. Key interests include approximation algorithms, online algorithms, streaming algorithms, clustering, coresets, and dimensionality reduction. His work often bridges theoretical guarantees with practical applications in distributed and parallel computing environments. The recent publications reveal a strong trend in developing efficient and scalable algorithms for clustering problems, particularly through coreset construction, dimensionality reduction, and distributed models like MPC. There is a growing emphasis on fairness, robustness, and dynamic settings, indicating a forward-looking research agenda in adaptive and responsible algorithmic systems. He actively mentors PhD students and teaches both undergraduate and graduate courses in programming and computational social science. He has served on program committees for top conferences including NeurIPS, ICML, and STOC, and co-organized a Dagstuhl seminar on clustering. Scientific Service and Leadership: Co-organizer, Dagstuhl Seminar on New Trends in Clustering (2026) Area Chair, NeurIPS 2024 and 2025 Program Committee, IPDPS 2019, SWAT 2022, COCOA 2024, ICALP 2026 He has received no explicitly mentioned scientific awards. His grants and funding sources are not detailed in the text. He leads a research group focused on theoretical foundations of data-efficient algorithms, collaborating with students on cutting-edge problems in high-dimensional and streaming data analysis.

• Edge Computing
• 5G Networks
• Serverless Applications
• +۴ مورد دیگر

Dr. Balázs Sonkoly is a researcher specializing in edge computing, serverless applications, and 5G network optimization. His work focuses on latency-sensitive systems, multi-user augmented reality coordination, and cloud-native microservice management across distributed architectures. Key research themes include network function virtualization (NFV), software-defined networking (SDN), and programmable packet-optical networks Recent publications analyze AI-driven autoscaling, P4-assisted serverless migration, and multi-domain service orchestration Article trends reveal expertise in mixed reality frameworks, federated learning for vehicular networks, and edge-cloud convergence. His collaborations span institutions like IEEE, SIGCOMM, and the UNIFY project. Contributions to conferences like NOMS, ISMAR, and GLOBECOM highlight practical implementations of edge cloud platforms, SLAM integration, and latency-constrained resource allocation.

Philipp Wiesnerمشاهده پروفایل

پژوهشگر ارشد

• Carbon-Aware Computing
• Distributed Systems
• Machine Learning Systems
• +۱ مورد دیگر

Philipp Wiesner is a Research Fellow at Technische Universität Berlin in the Distributed and Operating Systems (DOS) group led by Prof. Odej Kao. He completed his PhD at TU Berlin in June 2025 with summa cum laude honors for his thesis on carbon-aware optimization. Prior to academia, he worked as a Software and Data Engineer in Berlin. His research focuses on carbon-aware computing —aligning computational energy use with renewable availability—and intersects with distributed systems, machine learning infrastructure, and sustainable energy systems. Key methodologies include workload shifting, federated learning optimization, and simulation testbeds. Wiesner received the 1st prize in CarbonHack22 (2022) and his PhD distinction (2025). He led the Software Campus project SYNERGY (2022-2024), developing sustainable federated learning ( FedZero ) and carbon-aware testing tools ( Vessim ). He supervised TU Berlin's Master Project on Distributed Systems (2022) and served on the e-Energy 2026 Technical Program Committee. He collaborates internationally with institutions including the University of Glasgow, PUCRS (Brazil), and IRIT (France), and maintains active roles in workshops like LOCO'24.

Björn-Oliver Hartmannمشاهده پروفایل

پژوهشگر

• Computer Science
• Distributed Systems
• Game Theory
• +۳ مورد دیگر

Björn-Oliver Hartmann is a researcher at the Karlsruhe Institute of Technology (KIT), affiliated with the Faculty of Informatics and the Institute of Program Structures and Data Organization. His work focuses on distributed systems, game theory, and social network analysis. Research Areas: Network formation, peer-to-peer systems, strategic interaction, incentive mechanisms, and social network dynamics. Teaching: Served as Übungsleiter (exercise instructor) for courses including Distributed Data Storage and Software Development for Social Networks. Projects: Contributed to the SONAR project, emphasizing user-centric social network visualization.

Mirco Sternمشاهده پروفایل

پژوهشگر

• Sensor Networks
• Database Systems
• Service Composition
• +۲ مورد دیگر

Mirco Stern is a researcher at the Institute of Information Management (IPD Böhm) at Karlsruhe Institute of Technology. His work focuses on sensor networks, database systems, and service composition technologies. Key research areas include distributed query processing, data quality guarantees, and optimization of join operations in resource-constrained environments. Role : Researcher, Institute of Information Management Location : Karlsruhe, Germany Research trends highlight his expertise in sensor network optimization (join processing, wavelet transforms) and service composition (semantic matchmaking, automated integration). Publications span ACM SIGMOD, VLDB, and ECOWS conferences, emphasizing algorithm design and system efficiency.

Patrick Fischerمشاهده پروفایل

پژوهشگر

• Biomedical Engineering
• Machine Learning
• Respiratory Disease Research
• +۳ مورد دیگر

Patrick Fischer, M.Sc., is a Researcher and Doctoral Student at the Department of Health Sciences, Technische Hochschule Mittelhessen (THM), with a focus on biomedical engineering, machine learning, and respiratory disease research. His work spans nocturnal symptom monitoring in COPD and asthma patients, mobile health technology development, and AI-driven medical diagnostics. Key research areas include Biomedical Engineering applications for respiratory monitoring Machine Learning techniques in disease detection Mobile Health Technologies for home-based care Computational Biology in DNA methylation analysis Recent publications highlight graph database applications in nutrition apps, distributed computing for CNS tumor classification, and deep learning for cough detection and plagiocephaly monitoring. All articles demonstrate interdisciplinary approaches combining clinical needs with computational methods. His teaching responsibilities include supervising final thesis and project work. Contact: patrick.fischer@ges.thm.de .

Hagen Lauerمشاهده پروفایل

استاد

• System Security
• Cyber Resilience
• IT Forensics
• +۱ مورد دیگر

Hagen Lauer is a Professor of IT Security at Technische Hochschule Mittelhessen (University of Applied Sciences) . His expertise spans system security, cyber resilience, IT forensics, and formal methods. He teaches courses such as Decentralized Security , Computer Forensics , and Blockchain Fundamentals . Email: hagen.lauer@mni.thm.de Office: A20.1.22, Wiesenstraße 14, Gießen Contact: +49 (0) 641 309 2343 Education: Doctorate in Computer Science from Monash University (2020) . Previous affiliations include the Commonwealth Scientific and Industrial Research Organization (CSIRO) and the Fraunhofer Institute for Secure Information Technology (SIT) , where he served as acting department head until his appointment at THM Mittelhessen in 2022. Research Focus: Lauer's work emphasizes cyber resilience in autonomous systems, security protocols for energy grids, and formal verification of stratified architectures. His contributions address trust in virtualized platforms, decentralized IoT standards, and hypervisor-based attestation mechanisms. Publication Trends: Recent works focus on cyber-physical security in energy systems, formal logic for stratified architectures, and user-centric attestation in distributed environments. Topics include autonomous agents, smart grid protection, and containerization security.

• Computer Science
• Operating Systems
• Compiler Construction
• +۲ مورد دیگر

Michael Jäger is a Professor at Giessen University of Applied Sciences, specializing in Computer Science . He studied and received his doctorate in computer science from the Technical University of Darmstadt in 1983, followed by roles as a software developer, researcher, and lecturer at Technical University of Darmstadt and University of Mannheim before his appointment at Giessen in 1988. His expertise spans Operating Systems , Compiler Construction , Internet Technologies , and Software Architecture . Research Interests Operating Systems: Focused on system design, optimization, and resource management. Compiler Construction: Emphasizing language processing, code generation, and optimization techniques. Internet Technologies: Exploring networking protocols, web systems, and distributed computing. Software Architecture: Addressing scalable design, component integration, and system reliability. Scientific Awards No scientific awards, fellowships, or medals were explicitly mentioned in the provided texts. Advising and Grants There is no information provided about students, advisees, or grant funding in the available texts.