Find Academic Supervisors

• 6G Networks
• Telemedicine
• Medical Robotics
• +3 more

Nicolai Kröger is a researcher at the Chair of Communication Networks (Prof. Kellerer) at the Technical University of Munich (TUM). He holds an M.Sc. in Electrical and Computer Engineering from TUM, where his thesis focused on P4 switch performance modeling using queuing theory. His current research centers on 6G networks for critical telemedicine applications, particularly within the 6G-Life project, emphasizing end-to-end communication for medical robotics and surgical systems. He contributes to projects like the 6G Future Lab Bavaria and collaborates with the MITI group at Rechts der Isar Hospital to develop medical testbeds requiring high availability and low latency. Kröger also supervises student theses on 5G/6G security, network optimization, and in-network computing. His technical expertise spans programmable networks (P4), SDN, and performance analysis of network devices. He serves as a supervisor for student projects and internships, including implementations of medical testbeds and security analyses of cellular broadcast messages. His work bridges academic research with practical applications, aiming to advance communication networks for healthcare and future 6G systems.

• Automata Theory
• Formal Methods
• Tree Automata
• +4 more

Christof Löding is an Adjunct Professor at the Department of Logic and Theory of Discrete Systems (Computer Science 7) at RWTH Aachen University. His research focuses on automata theory, formal verification, and logical foundations of computer science, with significant contributions to Büchi automata, tree automata, and stochastic games. Academic affiliation: RWTH Aachen University, Germany Research areas: Automata theory, Formal methods, Game theory, Logic in computer science Contact: loeding@informatik.rwth-aachen.de His recent work spans deterministic parity automata construction, finite-valued transducers, and algorithmic solutions for infinite games. Publications emphasize theoretical foundations and practical applications in program verification and XML processing. Articles analyze automata learning, uniformization problems, and lookahead degrees in infinite games, showing interconnections between automata theory and formal verification.

Volkmar WirthView profile

Professor

• Rossby wave packets
• forecast errors
• tropopause dynamics
• +5 more

Volkmar Wirth is a full Professor of Theoretical Meteorology and Atmospheric Physics at the Institute for Atmospheric Physics, Johannes Gutenberg-University Mainz. His research focuses on Rossby wave packets, forecast error dynamics, tropopause behavior, mountain meteorology, and tropical cyclone processes. Full Professor since 2000 Specialist in midlatitude waveguidability and extreme weather predictability Active in mountain meteorology (banner clouds) and hurricane dynamics Teaching includes graduate courses on atmospheric hydrodynamics, predictability, and potential vorticity applications. He supervises project assignments involving numerical modeling in FORTRAN-90 and leads meteorology practicals with time series analysis experiments. Recent publications analyze Rossby wave propagation in changing climates, temperature extremes, and waveguide limitations. His group collaborates extensively on "Waves to Weather" predictability research. Current affiliations: Johannes Gutenberg-University Mainz , Institute for Atmospheric Physics.

Daniela BeisserView profile

Professor

• Bioinformatics
• Computational Biology
• Microbial Ecology
• +6 more

Prof. Dr. Daniela Beisser is a Professor at the Department of Engineering and Natural Sciences (FB 8) of the Westphalian University of Applied Sciences in Recklinghausen, Germany. Her research focuses on bioinformatics and biostatistical methods for high-throughput 'omics data, applied to biomedicine and freshwater ecology. She previously held academic roles at the University of Duisburg-Essen (2017–2023) and University Hospital Essen. 2004–2008: B.Sc. in Molecular Biology with Bioinformatics focus, FH Gelsenkirchen 2006–2008: M.Sc. in Molecular Biology with Bioinformatics focus, FH Gelsenkirchen 2008–2011: Ph.D. in Bioinformatics, University of Würzburg Her research integrates computational approaches with experimental data to study molecular responses to environmental stressors in freshwater organisms, genome analyses in human and protists, and proteomic studies in plants. She also investigates eco-evolutionary theories in microorganisms and links biodiversity to ecosystem functions. Recent publications highlight her work on amplicon sequencing (Natrix2 pipeline), metatranscriptomic analysis of microbial communities, and machine learning frameworks for environmental data. She contributes to software tools like TaxMapper and BioNet for reproducible workflows. Best Poster Award, German Conference on Bioinformatics (2013) Travel scholarships: DAAD, DAAD PROMOS, German Symposium on Systems Biology E-fellows.net scholarship (2006–2008) She has supervised numerous PhD, Master’s, and Bachelor’s students on topics such as protist community dynamics , fungal degradation processes , and stressor recovery mechanisms . Her lab collaborates on the CRC 1439 'RESIST' project and develops tools for environmental DNA analysis.

Markus SeifertView profile

Senior Lecturer

• Media and Communication Studies
• Health Communication
• Digital Communication
• +2 more

Dr. Markus Seifert serves as Senior Lecturer and Research Assistant at the University of Erfurt within the Seminar for Media and Communication Studies . He coordinates the aptitude assessment process and acts as academic advisor for the Bachelor's degree program in Communication Studies , while also contributing to Master's programs in Health Communication and Global Communication. His academic career spans multiple institutions, including visiting professorships at Chemnitz University of Technology (2022) and Friedrich Schiller University Jena (2023). Research Focus: Health Communication, Digital Communication, Political Communication Methodological Expertise: Quantitative Analysis, SPSS Applications, Experimental Design Academic Roles: Seminar Manager, Research Assistant, Teaching Professor (Acting) His scientific contributions address contemporary communication phenomena across three key domains: Health Communication: Digital patient support, hospital choice behavior, grief processing through online media Political Communication: Internet's mobilizing effects, digital democracy, political self-expression Music Communication: Digital music consumption, embodied listening practices, music taste formation Markus Seifert actively participates in academic governance as elected member of the Senate Committee for Study Affairs and the Study Commission of the Faculty of Philosophy. He serves as peer reviewer for multiple journals including Publizistik and European Journal of Health Communication.

• Database Systems
• Integration of heterogeneous databases
• Data quality and data integrity
• +6 more

Thomas Kudraß serves as Professor for Database Systems at the Faculty of Computer Science, Mathematics and Natural Sciences (IMN) at Leipzig University of Applied Sciences (HTWK Leipzig). With over 25 years of academic and industry experience, he teaches courses including Database Basics, Database Application Programming, Data Warehousing, and Big Data Technologies. His leadership roles include Internship Coordinator for Computer Science since 2001, Member of the Academic Senate since 2011, and Contact person for the IMN faculty alumni association since 2005. Dr. Kudraß earned his Dipl.-Ing. in Computer Science from Technical University of Dresden (1985-1990) and completed his doctorate at Darmstadt University of Technology (1992-1997), where his dissertation received the prestigious Jos Schepens Memorial Award. Prior to academia, he worked as an Information Systems Architect at UBS AG Zurich and Database Specialist at Swiss Bank Corporation Basel. His research spans database technologies with focus on heterogeneous database integration, data quality, data privacy, and modern database concepts. Recent work explores cloud-native billing applications for 5G, NoSQL databases, and privacy-preserving record linkage techniques. His publication record shows continuous evolution from traditional database systems to contemporary challenges in big data and distributed systems. Jos Schepens Memorial Award for doctoral dissertation (1997) Active participation in German Informatics Society (GI) specialist groups Organizer of multiple database-related workshops and conferences Professor Kudraß has significantly contributed to academic governance as E-Learning Officer (2000-02), Faculty Council member (2009-12), and liaison lecturer for the German Society for Computer Science (2001-14). He has coordinated numerous student projects and served on program committees for major conferences including INFORMATIK 2017 and BTW series.

Marius PesaventoView profile

Professor

• Sensor Array Processing
• MIMO Communication
• Adaptive Beamforming
• +4 more

Prof. Marius Pesavento is a Full Professor at the Department of Electrical Engineering and Information Technology, Technische Universität Darmstadt, leading the Communication Systems Group. His research focuses on sensor array processing, MIMO communication systems, adaptive beamforming, and mathematical optimization in networks. He has held academic and industry roles since 2001, including positions at mimoOn GmbH and FAG Industrial Services. Education: PhD (Doktorate) in Electrical Engineering, Ruhr-Universität Bochum (2001–2005) Master of Engineering, McMaster University (1999–2000) Dipl.-Ing. in Electrical Engineering, Ruhr-Universität Bochum (1992–1999) His research interests span robust high-resolution sensor array processing, 4G/5G mobile networks, and network information theory. Notable projects include developing tensor models for ultrasonic sensor calibration and applying machine learning to anomaly detection in network flows. His work bridges theoretical optimization and practical applications in automotive radar, 6G networks, and medical imaging. Labs/Teams: Leads the Communication Systems Group at TU Darmstadt, focusing on interdisciplinary projects in signal processing and communication systems.

Bianca Maria ColosimoView profile

Professor

• Metal Additive Manufacturing
• Statistical Process Control
• Image Data Analysis
• +3 more

Prof. Bianca Maria Colosimo is a faculty member at Politecnico di Milano in the Department of Mechanical Engineering. Her research focuses on in-situ sensing and monitoring of metal additive manufacturing (AM) processes, particularly Laser Powder Bed Fusion. She develops statistical data mining techniques for defect detection and process control, integrating big data streams into quality assurance systems. Her work aims to advance smart AM technologies through real-time monitoring and digital twin methodologies. Key research interests include: Metal Additive Manufacturing Statistical Process Control Image Data Analysis Laser Powder Bed Fusion In-situ Monitoring Smart Manufacturing Systems Publications highlight her contributions to layerwise imaging , plume signature analysis , and spatial statistical modeling for AM processes. Contact: Department of Mechanical Engineering, Politecnico di Milano.

• Data Mining
• Machine Learning
• Text Summarization
• +6 more

Mark Last is a Professor at Ben-Gurion University in Beersheba, Israel, with a distinguished career spanning over three decades in computer science research. His work primarily focuses on data mining, machine learning, and natural language processing applications. His research interests encompass stream data mining, text summarization, fuzzy logic systems, and classification algorithms. Last has made significant contributions to developing techniques for analyzing dynamic data streams, multilingual text processing, and applying machine learning to real-world problems in healthcare, social media analysis, and security informatics. His work often bridges theoretical advancements with practical applications, particularly in handling non-stationary data and developing interpretable models. Recent research trends show a continued focus on stream data analysis, with applications expanding into social media monitoring, healthcare prediction systems, and multilingual content analysis. His work demonstrates consistent innovation in adapting machine learning techniques to evolving data environments and practical challenges. Mark Last has maintained a prolific publication record with over 175 publications documented in DBLP, collaborating extensively with researchers including Abraham Kandel, Marina Litvak, and Oded Maimon. His work has been published in top venues including IEEE Access, Machine Learning journal, and Expert Systems with Applications.

• Internet of Things (IoT)
• Fog Computing
• Digital Twins
• +3 more

Dimitrios Georgakopoulos is a researcher at Swinburne University of Technology and National Measurement Institute, focusing on Internet of Things (IoT), digital twins, fog computing, and smart manufacturing. His work bridges theoretical advancements with real-world applications in urban infrastructure, precision agriculture, and industrial IoT. Research Areas: IoT, Digital Twins, Fog Computing, Smart Cities, Precision Agriculture Key Contributions: Sensor sharing marketplaces, 5G-enabled smart city frameworks, metadata-assisted IoT data classification Recent Articles (2023-2025): Explore topics like digital manufacturing consistency, AI-powered roadside asset management, and deep learning for heterogeneous IoT data. Trends emphasize autonomic systems, sensor integration, and contextual data analysis. Collaborations: Frequently works with Prem Prakash Jayaraman, Ali Yavari, Abhik Banerjee, and Anas Dawod on IoT security, sensor networks, and time-sensitive applications.

Filip SadloView profile

Professor

• Computer Science
• Scientific Visualization
• Flow Visualization
• +5 more

Prof. Filip Sadlo is a Full Professor of Computer Science at Heidelberg University's Interdisciplinary Center for Scientific Computing (IWR), leading the Visual Computing Group. He serves as Dean of Studies for the Department of Informatics since 2022 and holds roles in multiple academic organizations including VGTC Executive Committee (2022–2025) and Associate Director of IWR (2022–present). His research focuses on visualization of complex scientific data, flow analysis, vector field topology, and high-performance computing. Education: PhD in Computational Visualization from ETH Zurich (2010), with prior roles at European Forest Institute and University of Freiburg. Research Interests: Specializes in visualization techniques for fluid dynamics, vector fields, and uncertainty quantification. Key areas include Lagrangian coherent structures, advection-diffusion processes, and interactive visualization systems. His work bridges computational methods with real-world applications in engineering and environmental science. Publications: Over 80 peer-reviewed papers since 2004, emphasizing visualization algorithms for dynamic systems, topological data analysis, and scientific computing. Recent work explores metacognition in data visualization and discontinuous vector field analysis. Grants & Projects: Principal investigator in DFG-funded projects on visualization in meteorology and MRI-based diagnostics, as well as initiatives in data integration and simulation science (e.g., SFB-TRR 191, HIDSS4Health). Labs & Teams: Heads the Visual Computing Group, fostering interdisciplinary research in computational visualization and scientific computing.

Floriment KlinakuView profile

Researcher

• Software Engineering
• Cloud Computing
• Elasticity in Cloud Applications
• +5 more

Floriment Klinaku is a Researcher and Doctoral Researcher at the University of Stuttgart , affiliated with the Software Quality and Architecture Group . His work focuses on elasticity modeling , cloud-native systems , and performance optimization for modern software architectures. He contributes to projects like the Slingshot Simulator , which addresses autoscaling and resource management challenges in containerized environments. Research Interests include: Autoscaling mechanisms for cloud applications Elasticity and resilience in microservices Data stream processing in cloud environments Performance prototyping for containerized systems DevOps practices for automotive software His publications emphasize architectural solutions for scalability, resilience, and explainability in cloud-native ecosystems. Current trends in his work involve model-driven engineering approaches to coordinate autoscaling policies and quantify impact of design decisions on system behavior. No scientific awards are explicitly listed, and no advising/grant information is provided. He is part of the Software Quality and Architecture Group , contributing to research on cloud performance and elastic systems.

• Database Systems
• Data Management
• Data Mining
• +4 more

Michael Grossniklaus is a Professor at the University of Konstanz, Germany, specializing in database systems, data management, and information systems. His research focuses on query optimization, social media data streams, and object-oriented databases. He has contributed to the development of C-SPARQL for RDF stream processing and frameworks for adaptive data management. Grossniklaus has collaborated extensively with researchers in areas such as trajectory data modeling, cloud database optimization, and context-aware systems. His work emphasizes practical applications in education technology, mobile computing, and semantic web technologies. Affiliation: University of Konstanz, Germany Key Research Areas: Database Systems, Data Mining, Social Media Analysis, Query Optimization Notable Projects: C-SPARQL, Sahara (cloud database optimization), LPLM (neural cardinality estimation) Recent publications highlight advancements in neural models for cardinality estimation, trajectory data models, and memory optimization in cloud databases. His interdisciplinary approach bridges theoretical foundations with real-world applications in education, social media, and mobile systems.

Tobias DistlerView profile

Associate Professor

• Distributed Systems
• Byzantine Fault Tolerance
• Energy-efficient Computing
• +7 more

Tobias Distler is an Associate Professor (Privatdozent) at the Department of Computer Science 4 (Distributed Systems and Operating Systems) at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). He leads research in resource-efficient fault tolerance, energy-aware systems, and distributed coordination. His work focuses on Byzantine fault tolerance, cloud computing, real-time systems, and embedded systems resilience. Research Projects: REFIT (Resource-efficient Fault and Intrusion Tolerance) EDC (Efficient Distributed Coordination) E³ (Energy-aware Execution Environments) TClouds (Trustworthy Clouds) Research Interests: His expertise spans distributed systems, fault-tolerant replication, energy-efficient computing, real-time systems analysis, and secure cloud infrastructure. He emphasizes practical system design with rigorous theoretical foundations. Publications: Over 100 peer-reviewed papers in top venues like Middleware, EuroSys, DSN, and ECRTS. Notable contributions include Egalitarian BFT, Strome (energy-aware stream processing), and TinyBFT for embedded systems. Awards: SIGACT Research Highlights Nomination (2024) FAU Teaching Award for Junior Researchers (2021) IBM Ph.D. Fellowship (2012-2013) Professional Activities: Served on program committees for Middleware, EuroSys, DSN, and IEEE Transactions. Chair of Artifact Evaluation for Middleware '20. Founded the BCRB workshop on Byzantine consensus and blockchains. Education: Habilitation (2021) and Ph.D. (2014) from FAU, focusing on resource-aware system software for replicated services. Advisor to numerous graduate students in distributed systems research.

Jason J. JungView profile

Professor

• Computer Science
• Knowledge Engineering
• Social Media Analysis
• +3 more

Jason J. Jung is a Professor in the Department of Computer Engineering at Chung-Ang University, Seoul, Korea. His academic work focuses on knowledge engineering , social media analytics , and data mining within the Knowledge Engineering Laboratory. Research Interests : Computer Science, Social Knowledge, Data Modeling, Sentiment Analysis Projects : IoT-based cultural systems, real-time social event detection, transmedia storytelling models The 15 most recent publications (2014-2018) demonstrate expertise in social network analysis , multimodal data processing , and context-aware systems applied to urban services, cultural tourism, and digital storytelling. Key trends include real-time analytics , trust modeling , and collaborative frameworks for O2O services. Professional activities include editorial contributions, invited talks, and patent developments. Students at all levels (PhD/MSc/BSc) conduct research under his supervision at the Knowledge Engineering Laboratory. Personal interests include travel, film, painting, literature, and music.