جست‌وجوی استاد و پژوهشگر

• Biostatistics
• Statistical Methods for Clinical Trials
• Sample Size Planning
• +۳ مورد دیگر

Jun.-Prof. Dr. Carolin Herrmann is an Assistant Professor of Biostatistics at the Department of Mathematical Optimization, Mathematical Institute of Heinrich Heine University Düsseldorf. She holds a PhD in Health Data Sciences from Charité University Medicine Berlin and has extensive experience in academic and industry settings. Previously, she led the 'Clinical Trials' research group at Charité's Institute of Biometry and Clinical Epidemiology and held an interim professorship in biostatistics. Her work bridges methodological development and practical application, focusing on clinical trial design, sample size planning, and statistical modeling. Education: B.Sc./M.Sc. in Mathematics from Bielefeld University and University of Bergen, followed by a PhD in Health Data Sciences at Charité (2022). She also worked in Denmark's pharmaceutical industry on large clinical trials. Her research integrates statistical theory with real-world challenges, addressing topics like adaptive trial designs, time-to-event analysis, and statistical literacy in education. She emphasizes interdisciplinary collaboration between statistics, mathematics, and life sciences. Teaching and Didactics: Her work extends to improving statistical education through innovative methods, including catalogs of learning objectives and active learning strategies. She advocates for clearer communication of statistical concepts to enhance understanding in medical and health sciences curricula. Awards: No awards explicitly mentioned in the source text. Research Group: Her team develops cutting-edge statistical methods for clinical trials, focusing on sample size optimization, adaptive designs, and model selection. They also engage in applied research for pharmaceutical industries and academic collaborations.

Anh Tu Hoangمشاهده پروفایل

پژوهشگر

• Privacy-Preserving Systems
• Data Security
• Blockchain Technology
• +۳ مورد دیگر

Dr. Anh Tu Hoang is a Postdoctoral Researcher at TU Hamburg's Institute for Data Engineering, specializing in privacy-preserving systems, blockchain technologies, and knowledge graph anonymization. He holds a PhD from the University of Insubria, Italy, and degrees from Vietnam National University. His research addresses data security challenges in machine learning, federated learning, and decentralized systems. Education: Bachelor of Information Technology, University of Science, Vietnam National University (Ho Chi Minh City) Master of Information Systems, University of Science, Vietnam National University PhD in Computer Science, University of Insubria, Italy (2020) Research Focus: His work centers on developing mechanisms to protect privacy and security during data sharing, machine learning training, and blockchain operations. Key contributions include time-aware anonymization for knowledge graphs and blockchain-based federated learning frameworks. Projects include CDL-BOT and Orchid, focusing on decentralized learning and privacy-aware systems. Publications: Over 12 peer-reviewed articles in top venues like IEEE ICDE, ACM TOPS, and IEEE TDSC, with a focus on anonymization techniques, federated learning, and cryptographic protocols. Recent work explores zero-knowledge proofs for self-sovereign identity and proximity marketing privacy. Expertise: Combines cryptographic methods with data privacy principles to address modern challenges in distributed systems, social networks, and collaborative AI environments.

• Semiconductor Reliability
• Machine Learning for CAD
• Hardware Security
• +۶ مورد دیگر

Hussam Amrouch is a Professor (W3) at the Technical University of Munich (TUM) , leading the Chair of AI Processor Design (AI-Pro) and affiliated with the Munich Institute of Robotics and Machine Intelligence (MIRMI) . He also serves as the head of Semiconductor Test and Reliability (STAR) at the University of Stuttgart. His academic journey includes a Ph.D. (Dr.-Ing.) summa cum laude from Karlsruhe Institute of Technology (KIT) and leadership of the Dependable Hardware Research Group at KIT. His research spans design for reliability and testing , machine learning for CAD , hardware security , approximate computing , and emerging technologies with a focus on ferroelectric devices . Recent publications highlight applications in hyperdimensional computing , cryogenic circuits , and neuromorphic systems . Amrouch has received 8 HiPEAC Paper Awards and best paper nominations at top EDA conferences. His work is funded by organizations including the German Research Foundation (DFG) , Advantest Corporation , and the U.S. Office of Naval Research (ONR) . He has over 200 publications across multidisciplinary domains from semiconductor physics to computer architecture. As an editor at Nature Scientific Reports , he contributes to journal oversight. His technical leadership extends to program committees of major EDA conferences like DAC, ASP-DAC, and ICCAD.

Tobias Rolfesمشاهده پروفایل

استاد

• Mathematics Education
• Algebraic Skills
• Functional Thinking
• +۳ مورد دیگر

Prof. Dr. Tobias Rolfes holds the position of Professor for Mathematics Education with focus on secondary level at Goethe University Frankfurt. He is affiliated with the Institute for Didactics of Mathematics and Computer Science within the Faculty of Humanities. His research program includes several ongoing projects: ITS (teaching with intelligent tutorial systems), a² (diagnosis of algebraic skills), and MiO (competence development in upper secondary mathematics). Rolfes completed his PhD in Mathematics Education at University of Koblenz-Landau (2017), Master's in Business Administration at University of Hagen (2010), and teaching qualifications at University of Münster (2001). His professional trajectory includes positions at IPN - Leibniz Institute, LMU Munich, and secondary teaching roles before assuming his current professorship in 2022. His research spans foundational mathematical competencies, digital learning environments, and transition phases in mathematics education. Key investigations explore the development of functional thinking, statistical literacy, and technology-enhanced pedagogy. Research outputs demonstrate consistent focus on improving mathematical understanding through innovative instructional approaches and diagnostic assessments. Publications reveal sustained examination of mathematical competence development across educational stages, with particular attention to conceptual understanding of functions, derivatives, and statistical representations. Recent work increasingly incorporates digital learning technologies and longitudinal performance analysis. Professor Rolfes supervises doctoral candidates leading major research initiatives and maintains active knowledge transfer through practitioner-oriented publications in mathematics teaching journals. Consultations are available by appointment at his Robert-Mayer-Strasse office.

Prashant Srivastavaمشاهده پروفایل

پژوهشگر

• Machine Learning
• Deep Learning
• Image Analysis
• +۵ مورد دیگر

Prashant Srivastava is a Researcher at the Department of Systems Biology and Bioinformatics under the Faculty of Computer Science and Electrical Engineering at the University of Rostock, Germany. His work bridges machine learning with bioinformatics and financial risk modeling. Education: MSc Data Science and Analytics (2018-2020) from Royal Holloway, University of London Integrated B.S.-M.S. in Physics (2013-2018) from Indian Institute of Science Education and Research, Kolkata Master's Thesis in Computer Science (2020) on statistical risk methods in financial markets Master's Thesis in Physics (2017-2020) on extraordinary transmission in silicon-based micro-meter wire grid polarizers Research Focus: Prashant specializes in machine learning and deep learning applications. His work spans bioinformatics (bitter peptide prediction), data science (ConvGeN algorithm for imbalanced datasets), and financial risk modeling using VaR and Expected Shortfall frameworks. Recent Publications: His research trends include graph neural networks for peptide analysis, convex space learning for generative oversampling, and self-attention mechanisms for molecular interaction extraction from biological texts. Technical Expertise: Proficient in Python (numpy, scipy, tensorflow), R, C++, MATLAB, cloud computing (Azure), and database systems (SQL, NoSQL). He develops libraries like mgarch for GARCH modeling and applies advanced ML techniques (CNN, RNN, GAN, NLP) across domains. Labs & Teams: Active member of the Systems Biology and Bioinformatics group at the University of Rostock, contributing to interdisciplinary research at the intersection of computer science and life sciences.

Mohamed Abdelmagiedمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Educational Technology
• Knowledge Graphs
• +۳ مورد دیگر

Mohamed Abdelmagied is a Researcher at the University of Duisburg-Essen . He is affiliated with the Social Computing Group and contributes to the CourseMapper project. His research focuses on Graph Retrieval-Augmented Generation to enhance students' understanding of knowledge concepts. He is supervised by M.Sc. Qurat Ul Ain and M.Sc. Shoeb Joarder . Abdelmagied also assists in teaching the course Data Structures and Algorithms SS25 . His work intersects Artificial Intelligence , Educational Technology , and Knowledge Graphs .

• Database Systems
• Graph Databases
• Route Planning
• +۴ مورد دیگر

Dr. Theodoros Chondrogiannis is a Post-doctoral Researcher at the University of Konstanz's Database and Information Systems group. He holds a PhD from the Free University of Bozen-Bolzano (2017) and previously worked as a postdoc there until joining Konstanz. His research focuses on route planning, graph database query processing, and spatial network analysis. He leads a DFG-funded project on multi-criteria path queries and teaches 'Graph Data Management and Analysis' annually. Education: BSc (Computer Science, University of Peloponnese, 2009), MSc (Advanced Information Systems, National Kapodistrian University of Athens, 2013), PhD (Free University of Bozen-Bolzano, 2017). Research interests include algorithm design for transportation networks, graph database systems, and geosocial network analysis. His work bridges theoretical foundations with practical applications in urban mobility and query optimization. He will assume an Associate Professor role at NTNU's Department of Computer Science (IDI) starting January 2025. Notable service roles include publicity chair for SSTD 2023 and co-chair for ACM SIGSPATIAL Student Research Competitions (2019-2020).

Jan Nagelمشاهده پروفایل

استاد

• Probability Theory
• Random Walks
• Random Matrices
• +۱ مورد دیگر

Jan Nagel is Professor of Stochastics at TU Dortmund University's Department of Mathematics. His research explores probability theory with focus areas including random walks in random environments, random matrix theory, and stochastic processes. Recent publications investigate the dynamic behavior of viscoelastic structures with random material properties, sum rules in mathematical physics, and functional central limit theorems for random matrices. Dr. Nagel completed his doctorate in Mathematics at Ruhr University Bochum (2010) following a Diplom degree (2008). His academic trajectory includes positions as Assistant Professor at TU Dortmund (2019-2023), research fellowship at TU Eindhoven, and visiting professorships at LMU Munich. His work bridges theoretical mathematics with applications in statistical mechanics and disordered systems.

Lorenz Gruberمشاهده پروفایل

پژوهشگر

• Software Engineering
• Workflow Engineering
• Earth Observation
• +۳ مورد دیگر

Lorenz Gruber is a Researcher at the Chair of Software Engineering (Computer Science II) at the University of Würzburg under Prof. Samuel Kounev. He holds M.Sc. and B.Sc. degrees in Computer Science from the same institution. His research focuses on workflow engineering, earth observation, scientific computing, and software architecture, with notable contributions to graph-based urban area analysis. Education: Master of Computer Science (2021-2024) Bachelor of Computer Science (2018-2022) Abitur (2017) His work integrates interdisciplinary approaches, such as combining geospatial data with computational methods for urban settlement analysis. He coordinates software architecture lectures and supervises student theses. In 2024, he received the Würzburg Software Engineering Award for his master’s thesis on graph-based urban analysis frameworks. Prior Roles: Student Assistant at Chair of Software Engineering (2020-2024) Student Assistant at Chair of Communication Networks (2020-2023) Student Assistant at Chair of Artificial Intelligence (2020) His current activities include research in serverless computing and software engineering methodologies.

Sven Hertlingمشاهده پروفایل

استاد

• Knowledge Graph Generation
• Ontology Matching
• Knowledge Graph Integration
• +۳ مورد دیگر

Dr. Sven Hertling is a Substitute Professor for Data Science at the University of Mannheim, affiliated with the Data and Web Science Group. His research focuses on Knowledge Graph Generation, Ontology Matching, and Knowledge Graph Fusion. He teaches courses such as Knowledge Graphs, Data Mining, and Database Technologies. Notable awards include the Best Demo at ESWC 2021 and Best Paper at the Knowledge Graphs and Semantic Web Conference (KGSWC) 2022. Education: PhD in Computer Science (implied by role). His research interests span ontology alignment, large language model integration, and scalable knowledge graph systems. Recent work includes frameworks like KGrEaT for knowledge graph evaluation and tools like MELT for ontology matching analysis. He has contributed to over 50 publications, with a focus on ontology alignment evaluation (OAEI) and semantic web technologies. Key projects include the Software Campus initiative's GUI search engine and DBkWik, integrating knowledge from thousands of Wikis. Grants: €100,000 from Software Campus for the SuGraBo project. Advising: Coordinates OAEI challenges and chairs ESWC 2023. He actively serves on program committees for ISWC, ESWC, and other conferences, emphasizing community engagement in semantic web research.

Pascal Schweitzerمشاهده پروفایل

استاد

• Algorithms
• Graph Theory
• Computational Complexity
• +۳ مورد دیگر

Prof. Pascal Schweitzer is a faculty member in the Department of Computer Science at TU Darmstadt, leading the working group focused on Algorithms and Symmetry. Previously affiliated with TU Kaiserslautern, he holds a PhD thesis titled 'Problems of Unknown Complexity: Graph Isomorphism and Ramsey Theoretic Numbers.' His research interests include symmetry detection, algorithmic and structural graph/group theory, computational complexity, graph isomorphism problem, and computer algebra. He has collaborated on projects related to Weisfeiler-Leman algorithms and isomorphism tests for graphs with bounded parameters. Pascal's work is supported by contributions to conferences like LICS, STOC, and FOCS. He has co-advised master's students such as Jean-Paul Weber and Anton Catalin on topics like attack-defense trees and antivius engine scanners. He leads teams including EngageS and contributes to teaching areas like algorithmics, deduction, and distributed systems. He maintains an office at TU Darmstadt and can be reached via email at schweitzer@cs.uni-kl.de . His research explores theoretical computer science and practical applications in graph canonization and security models.

Thomas Krauseمشاهده پروفایل

پژوهشگر

• Corpus Linguistics
• Linguistic Annotation Tools
• Software Sustainability
• +۳ مورد دیگر

Overview Thomas Krause is a Researcher at the Institut für deutsche Sprache und Linguistik, part of the Sprach- und literaturwissenschaftliche Fakultät at Humboldt-Universität zu Berlin. His work focuses on corpus linguistics, software infrastructure for linguistic annotation, and sustainable research software development. Research & Projects Developed ANNIS , a widely used corpus search and visualization system. Co-creator of Hexatomic , an extensible annotation tool for linguistic corpora. Lead contributor to the LAUDATIO project for long-term data preservation in historical linguistics. Key Contributions His research emphasizes software sustainability, multilingual corpus infrastructure, and the integration of computational methods with linguistic analysis. Recent work addresses challenges in annotation processes, software architecture design, and cross-disciplinary collaboration.

• Combinatorial Optimization
• Approximation Algorithms
• Online Algorithms
• +۷ مورد دیگر

Sven O. Krumke is a Professor in the Department of Mathematics at the Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau (RPTU), where he has been a faculty member since 2004. He currently serves as the Dean of the Faculty of Mathematics, overseeing academic and administrative affairs. His research is centered in combinatorial optimization and algorithmic game theory, with strong applications in logistics, emergency response, and network design. PhD, University of Würzburg (1997) Habilitation, Technical University of Berlin (2002) Professor, RPTU Kaiserslautern-Landau (since 2004) His research interests include combinatorial optimization, approximation and online algorithms, robust scheduling, algorithmic game theory, and graph-theoretic applications. He has led major interdisciplinary projects such as GRK 2982: MIMO (Mathematics of Interdisciplinary Multiobjective Optimization) and ONE PLAN , focusing on optimizing emergency medical services in Rhineland-Palatinate. His work often bridges theoretical computer science and real-world decision-making systems. His recent publications (2016–2022) emphasize robust optimization , pandemic response logistics , decision-support systems in healthcare , and online routing . These works span domains such as vaccine location strategies, ambulance dispatch, car-sharing relocation, and scheduling under uncertainty. The recurring themes are efficiency, resilience, and algorithmic fairness in dynamic environments. Notable scientific contributions include work on network design, flow problems with budget constraints, and game-theoretic models of routing. While no specific awards are listed, his leadership in DFG-funded research groups underscores his academic standing. He actively supervises bachelor's and master's theses and teaches courses such as Grundlagen der Mathematik I: Analysis . He has collaborated with researchers across Germany and internationally, particularly in algorithmic game theory and optimization under uncertainty. Dr. Krumke leads and contributes to research teams in: AG Optimierung (Optimization Research Group) at RPTU GRK 2982: MIMO – interdisciplinary multiobjective optimization ONE PLAN – optimization in emergency medical response

Anders Blomdellمشاهده پروفایل

استاد

• Control Systems
• Real-Time Systems
• Embedded Systems
• +۷ مورد دیگر

Anders Blomdell is a Professor in the Department of Control Engineering at the Faculty of Engineering, Lund University. His work bridges theoretical control systems with practical applications in real-time, embedded, and cloud-based environments. He is actively involved in research projects focusing on autonomous systems, industrial automation, and networked control. His research interests include Control Systems , Real-Time and Embedded Systems , Networked Control , Industrial Automation , Robotics , and Cloud-Controlled Systems . These areas reflect his focus on scalable, adaptive, and secure control solutions for complex, interconnected systems. The recent publications highlight a strong trend toward event-based control , large-scale optimization , autonomous adaptation , and secure cloud integration . His work often combines control theory with computer science, particularly in distributed and real-time settings, showing a consistent effort to address challenges in latency, scalability, and robustness. Scientific Awards: Advising and Grants: While specific students are not listed, Anders Blomdell leads and participates in major research initiatives such as WASP, ELLIIT, and the Nordic University Hub on Industrial Internet of Things (HI2OT). These projects involve significant funding and collaboration with industry and academia, indicating active mentorship and leadership in training next-generation researchers. Labs and Teams: He is associated with RobotLab LTH and contributes to the development of tools like TrueTime and LabComm , which are widely used in real-time and networked control research. His work supports both academic and industrial innovation in automation and intelligent systems.

Florian Reitzمشاهده پروفایل

پژوهشگر

• Computer Science
• Database Systems
• Information Retrieval
• +۵ مورد دیگر

Florian Reitz is a Scientific Staff member at Schloss Dagstuhl - Leibniz Center for Informatics, specializing in the dblp computer science bibliography. His current role involves enhancing bibliographic data infrastructure and managing projects like SmartER. He holds a PhD from the University of Trier (2018), focusing on historical metadata analysis. Previously, he was a research assistant in the Databases and Information Systems group under Prof. Bernd Walter. His work centers on metadata quality, author disambiguation, and leveraging historical corrections for test collections. Research interests include information retrieval, database systems, and digital libraries. He contributes to projects like Scalable Author Disambiguation and has co-authored numerous publications on topics such as LLM applications, knowledge graphs, and FAIR data principles. Contact: florian.reitz@dagstuhl.de.