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Andrea BlunckView profile

Professor

• Incidence Geometry
• Geometric Algebra
• Gender Studies in Mathematics Education
• +3 more

Prof. Andrea Blunck holds a professorship in Mathematics and Gender Studies at the University of Hamburg’s Department of Mathematics. Her research spans Incidence Geometry, focusing on algebraic-geometric connections, and Gender Studies in STEM education. She has held academic positions since 2004, including roles as Equality Officer for the Department and spokesperson for Gender & Diversity initiatives. Her work integrates gender aspects into mathematics teaching and explores mathematical research as a social process. Notable roles include leadership in the Arbeitskreis Frauen und Mathematik (Women and Mathematics Working Group). Education: Diplom in Mathematics (1988, University of Hamburg) PhD in Mathematics (1990, University of Hamburg) Habilitation in Mathematics (1997, TU Darmstadt) Research Interests: Inzidenzgeometrie and Geometrische Algebra, including applications of octonions and composition algebras. Gender integration in mathematics curricula and teacher training. Awards & Grants: Lise-Meitner Research Fellowship (2000, Austrian Science Fund) Multiple academic roles emphasizing gender equity in STEM. Labs/Teams: Active in Hamburg’s Mathematical Society and collaborative projects on Gender & Diversity in research.

Long ChengView profile

Researcher

• Cloud Computing
• Big Data Analytics
• Parallel and Distributed Systems
• +3 more

Dr. Long Cheng was a former Researcher at the International Center for Computational Logic (ICCL) within the Faculty of Computer Science at TU Dresden. His research focused on cloud computing, big data analytics, and distributed systems, particularly in optimizing large-scale data processing, outer join operations, and semantic web technologies. He contributed to projects involving parallel programming models like X10, MapReduce frameworks, and efficient data compression techniques for RDF datasets. Cheng collaborated with the Knowledge-Based Systems research group, addressing challenges in scalable systems, high-throughput indexing, and parallel reasoning under non-monotonic logics. His work emphasized performance optimization in distributed environments, including skew handling, data redistribution strategies, and algorithm scalability for large datasets. Publications span topics such as outer join evaluation in cloud environments, efficient compression of semantic web data, and high-performance query execution over distributed systems. His research bridges theoretical computational logic with practical applications in big data and cloud infrastructure.

Ivo F. SbalzariniView profile

Professor

• Computational Biology
• Systems Biology
• Scientific Computing
• +7 more

Prof. Dr. Ivo F. Sbalzarini is a Professor of Computer Science and holds the Chair of Scientific Computing for Systems Biology at TU Dresden. He is also a tenured Senior Research Group Leader at the Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG) and Director of the Center for Systems Biology Dresden (CSBD). His academic journey includes a Diploma in Mechanical Engineering from ETH Zurich (2002) and a Doctorate in Computer Science from ETH Zurich (2006), awarded the Chorafas Prize. He has held roles such as Dean of the Faculty of Computer Science at TU Dresden (2021–2025) and Co-Spokesperson of the International Max Planck Research School for Cell, Developmental, and Systems Biology (IMPRS-CellDevoSys). Research interests focus on particle methods for image-based computational biology, including multi-scale simulations, data-driven modeling, and parallel high-performance computing. Applications include systems biology of development and active matter. His work integrates computational approaches with biological systems to understand cellular processes and tissue morphogenesis. Notable contributions include the development of the MOSAIC Group, a transdisciplinary research team, and leadership roles in initiatives like the Center for Advanced Modeling and Simulation (CAMS) and the Cluster of Excellence Physics of Life (PoL). He also founded TU Dresden's Computational Modeling and Simulation Master’s program. Prof. Sbalzarini has advised numerous PhD students and postdocs, with research spanning bioimage analysis, stochastic simulation algorithms, and adaptive particle methods. His awards include the Willi Studer Prize and Chorafas Prize, recognizing his academic and research excellence.

Sebastian WilczekView profile

Researcher

• Plasma Technology
• Plasma Simulation
• Gas Conversion
• +3 more

Sebastian Wilczek is a researcher at Technische Hochschule Georg Agricola (THGA) in Bochum and works part-time at enaDyne GmbH in Leipzig. He completed his PhD in plasma technology at Ruhr University Bochum and serves as a visiting researcher there, teaching Numerical Methods in Electrodynamics . His academic work spans research and teaching in plasma modeling, CO₂ conversion, and simulation techniques. Research Focus: Wilczek’s research centers on plasma technology , particularly radio-frequency (RF) plasma systems , with emphasis on non-thermal plasma catalysis for greenhouse gas conversion . His work includes detailed studies of electron dynamics in low-pressure capacitively coupled plasmas (CCPs), sheath behavior , and ionization mechanisms using advanced simulation tools like PIC/MCC and nonPDPSIM . Publications & Conferences: Wilczek has contributed to multiple peer-reviewed conference papers and simulations on topics such as CO₂ dissociation , electron temperature dynamics , and waveform tailoring for plasma optimization. His recent work compares microwave plasma torches with other sources for carbon recycling and investigates non-neutral discharge regimes at atmospheric pressure. Simulation Tools: He co-developed eduPIC , an educational PIC/MCC code for plasma simulation , available in multiple programming languages including Rust and C/C++. This tool is designed to help students and researchers understand and extend particle-in-cell methods for their own applications.

Arne KoorsView profile

Researcher

• Discrete-Event Simulation
• Algorithm Optimization
• Financial Market Modeling
• +3 more

Arne Koors serves as a scientific Assistant at the Department of Computer Science , University of Hamburg , under the Faculty of Mathematics, Informatics and Natural Sciences (MIN) . His research focuses on discrete-event simulation optimization , financial market modeling , and ERP system integration . He has contributed to 9 Bachelor's and 5 Diplom theses as primary supervisor. Education & Teaching: He teaches courses including Mathematics for Computer Science , Introduction to Computer Science , and Simulation Projects . His teaching spans topics like cryptography, network systems, and simulation seminars. Research Contributions: His work emphasizes performance optimization of simulators, priority queue algorithms, and simulation-ERP system interaction. Notable achievements include a Best Paper Award at ESM 2014 for Analysis by State: An Alternative View on Discrete Event Time Series . Practical Experience: He led project management for 75 manufacturing companies in ERP implementation and developed a globally used sales planning software deployed in 250 firms. His invited talks include presentations on ERP systems in education and sales planning strategies. Key Projects: Development of the DESMO-J simulation framework, integration of financial risk metrics into discrete-event systems, and asynchronous RNG methods for performance enhancement.

Mark-Matthias ZymlaView profile

Research Fellow

• Computational Semantics
• Syntax/Semantics Interface
• Formal Pragmatics
• +5 more

Mark-Matthias Zymla is a post-doctoral researcher at the University of Konstanz's Department of Linguistics specializing in computational linguistics. His work bridges theoretical linguistic frameworks with practical computational implementations, focusing on semantic representation and processing. His primary research interests include computational semantics, the syntax/semantics interface, formal and computational pragmatics, with particular expertise in tense and aspect systems, argumentation theory, discourse particles, and rhetorical questions. He develops computational tools like LiGER (Linguistic Graph Expansion and Rewriting) that integrate syntactic analyses from LFG and Universal Dependencies with semantic annotations using Glue Semantics. Zymla has taught numerous courses at the University of Konstanz including Computational Semantics, Lexical Functional Grammar, Large Language Models, and Grammar Development across multiple semesters since 2015. His research is supported by projects like CUEPAQ (Visual Analytics for Argument Quality), VALIDA, and tense/aspect research funded by the Nuance Foundation. He actively participates in the ParGram community, co-organizing meetings in Rochester (2023) and Groningen (2022), and co-founded the 'SuP' reading group on semantics and pragmatics at Konstanz. His publications demonstrate strong interdisciplinary work connecting computational linguistics with visual analytics, argumentation studies, and cross-linguistic semantic annotation.

Thorsten OhlView profile

Professor

• Particle Physics
• High-Energy Physics
• Collider Physics
• +3 more

Prof. Thorsten Ohl is a Professor at the University of Würzburg's Faculty of Physics and Astronomy, leading the Department of Theoretical Physics II. He is a Principal Investigator in the Research Training Group (RTG) 2994, focusing on particle physics at colliders in the LHC precision era. His work centers on theoretical physics, computational methods, and high-energy collider experiments, particularly involving the WHIZARD event generator framework. His research spans precision measurements, BSM physics, scattering amplitudes, and software development for particle physics simulations. His research interests include quantum field theory, noncommutative standard models, and advanced computational techniques for collider analysis. He contributes to international projects like the FCC-ee and LHC precision experiments. His publications highlight advancements in event generation tools, model implementation, and precision studies of Higgs sectors and vector boson scattering. Prof. Ohl collaborates on RTG 2994's doctoral training and oversees the development of software tools for high-energy physics, emphasizing parallel computing and Monte Carlo methods. His lab integrates theoretical insights with computational innovation to address forefront questions in particle physics.

• Econometrics
• Empirical Finance
• Asset Pricing
• +9 more

Joachim Grammig is a Professor in the Department of Statistics and Econometrics at the School of Business and Economics, University of Tübingen, Germany. His research lies at the intersection of econometrics and empirical finance, with a focus on asset pricing, financial market microstructure, high-frequency data, and international financial markets. His research interests span Econometrics , Empirical Finance , Asset Pricing , Financial Market Microstructure , High Frequency Data , and International Financial Markets . He develops and applies advanced statistical models to understand price formation, risk, and information flow in financial markets. His recent publications show a strong trend toward integrating structural economic models with modern econometric techniques such as indirect inference, simulation-based estimation, and machine learning. His work frequently addresses long-standing puzzles in asset pricing, including the equity premium, rare disasters, and information asymmetry. He also contributes to methodological advances in duration modeling and specification testing. Diverging Roads: Theory-Based vs. Machine Learning-Implied Stock Risk Premia (2024) Estimating the SARS-CoV-2 Infection Fatality by Data Combination (2022) Empirical Asset Pricing with Multi-Period Disasters (2021) Creative Destruction and Asset Prices (2016) Tell-Tale Tails: A New Approach to Estimating Unique Market Information Shares (2013) He advises PhD students and junior researchers, including Jantje Sönksen and Franziska Julia Peter. His research is supported by access to high-frequency financial data and computational tools, and he emphasizes reproducibility by sharing programs and data. He has collaborated extensively with scholars across Europe and the U.S. He leads a research team in econometrics and empirical finance at Tübingen, fostering a collaborative environment for graduate students and visiting scholars.

Thomas ZeiserView profile

Researcher

• High-Performance Computing
• Lattice Boltzmann Methods
• Computational Fluid Dynamics
• +3 more

Dr. Thomas Zeiser serves as Head of Systems & Services and Chief Operating Officer HPC at NHR@FAU (Center for National High Performance Computing Erlangen) at Friedrich Alexander University Erlangen-Nuremberg. He leads the Systems & Services group of NHR@FAU and HPC4FAU since the end of 2020 and serves as deputy for NHR@FAU in the NHR Betreiberausschuss. His work focuses on transitioning from serving FAU only to national center operations, managing HPC systems, procuring new infrastructure, financial controlling of NHR@FAU's budgets, and supporting planning for a new data center building. Dr. Zeiser's research interests center around High-Performance Computing with specific expertise in Lattice Boltzmann Methods , large-scale simulations, evaluation of HPC hardware and software, and efficient operation of HPC systems. His work bridges the gap between theoretical computational methods and practical implementation in high-performance environments. He has implemented the first job-based job and performance monitoring for RRZE's HPC systems and has extensive experience in procurement of HPC infrastructure. Analysis of Dr. Zeiser's publication record reveals a consistent focus on practical applications of computational methods in HPC environments. His research demonstrates a progression from fundamental lattice Boltzmann method development toward increasingly complex system-level concerns including fault tolerance, performance monitoring, energy efficiency, and scalable implementations. The publications show strong collaboration patterns with researchers at FAU and other German institutions, particularly in the areas of computational fluid dynamics and parallel computing. Dr. Zeiser regularly serves as a reviewer for various journals and compute time commissions of different HPC centers. He is also one of the local organizers for the Ferienakademie of TUM, FAU, and Universität Stuttgart held in Sarntal. His work with NHR@FAU positions him at the forefront of national high-performance computing infrastructure in Germany. At NHR@FAU and RRZE (Regional Computing Center Erlangen), Dr. Zeiser leads teams responsible for operating some of Germany's most powerful academic supercomputing resources. His group plays a critical role in supporting computational research across multiple disciplines at FAU and increasingly at the national level through the NHR initiative.

Christoph GrögerView profile

Lecturer

• Industrial Analytics
• Data Management
• Data Analytics
• +8 more

Christoph Gröger holds the academic title Dr.-Ing. and serves as Chief Expert for Data & AI at Bosch, leading enterprise architecture in Bosch's global data strategy team. He is also active as a guest lecturer and researcher at the University of Stuttgart, focusing on industrial analytics, data management, and data platforms. Institution: University of Stuttgart (IPVS - Applications of Parallel and Distributed Systems) Role: Lecturer, Guest Researcher Current Focus: Data platforms, data strategies, enterprise data marketplaces His research centers on industrial analytics, addressing data management and analytics in manufacturing and enterprise systems. He explores data lake architectures, metadata modeling, and the integration of data warehouses with data lakes. His work spans Industry 4.0, mobile manufacturing dashboards, and prescriptive analytics for business process optimization. Recent publications analyze data lakehouses, metadata frameworks, and enterprise data marketplaces. These works emphasize practical implementations, metadata challenges, and democratizing corporate data. His research trends highlight hybrid data architectures, agile manufacturing analytics, and data productization. Scientific Awards: Best Paper Award at ICEIS 2016 Best Student Paper Award at ICEIS 2014 Best Student Paper Award at ICEIS 2014 At the University of Stuttgart, Gröger teaches courses on Industrial Analytics, Data Warehousing & Analytics (with a focus on Data Mining), and Data Platforms for Industry 4.0. He has led doctoral seminars on industrial analytics since 2019 and contributes to the Industrial Data Lab collaboration between Bosch and the university.

• Robotics
• Automation Technology
• Mechatronic System Design
• +3 more

Prof. Dr.-Ing. Tobias Bruckmann holds the Chair of Mechatronics at the University of Duisburg-Essen . His research focuses on robotics , particularly cable-driven parallel robots with applications in logistics , construction , and space systems . He is also involved in automation technology and human-machine interfaces . Key Scientific Activities : Organized multiple international conferences (e.g., CableCon 2019, IFToMM DA-CH 2020) and served as Associate Editor for IEEE robotics conferences. Research Projects : Led EU-funded CableBOT (logistics), DFG projects SEGESTA and ARTIST , and contributed to FAROMIR (home robotics). Recent Publications (2025-2023): Explored cable force calculations, automation in construction, human-robot collaboration, and space robot suspension systems. Collaborations : Worked with institutions in Germany (Fraunhofer IPA, TU Delft), France (INRIA), China (The Chinese University of Hong Kong), and Poland. Email: tobias.bruckmann@uni-due.de

• Database Systems
• Data Mining
• Query Optimization
• +3 more

Jeffrey F. Naughton is a Professor at the University of Wisconsin and works at Google Inc in Madison, WI, USA. His academic career spans decades with significant contributions to database systems, data mining, and privacy-preserving analytics. Research Interests : Distributed query processing and optimization Machine learning integration with relational databases Differential privacy in data analysis Scalable data warehousing systems Energy-efficient database architectures Temporal data management Article Trends : Over the past decade, Naughton's publications demonstrate a trajectory from foundational database optimization to modern challenges in scalable analytics and privacy-preserving techniques. Key themes include query execution prediction, workload summarization, and system design for big data environments. Scientific Awards : ACM Software System Award (2008) - Recognizing his contributions to database software systems Collaborative Network : He has collaborated with leading researchers including AnHai Doan (entity matching), Somesh Jha (privacy), and Stratis Viglas (query optimization), producing impactful work in SIGMOD, VLDB, and ICDE venues.

• Applied Mathematics
• Optimization
• Computational Mathematics
• +3 more

Yair Censor is a distinguished Professor in the Department of Mathematics at the University of Haifa. His work focuses on applied mathematics, particularly in optimization, projection methods, and computational algorithms with applications in medical physics and engineering. He has developed foundational techniques like the superiorization method, which balances feasibility-seeking and objective function reduction in iterative algorithms. Research Interests: Optimization theory, convex feasibility problems, superiorization, medical imaging algorithms, and parallel computing. Collaborations: Extensive work with Gabor T. Herman, Aviv Gibali, Reinhard Schulte, and others in computational methods for radiation therapy and tomography. His recent publications (2023–2025) emphasize feasibility-seeking algorithms, superiorization in floorplanning, and perturbation resilience. While no explicit awards or students are listed in the provided text, his contributions to iterative methods and medical physics remain influential.

Patrick GebhardView profile

Researcher

• Affective Computing
• Natural Language Processing
• Human-Computer Interaction
• +3 more

Dr. Patrick Gebhard is a researcher at the Cognitive Assistance Systems department of the German Research Center for Artificial Intelligence (DFKI), focusing on affective computing, human-computer interaction, and psychological modeling. His work bridges computational linguistics, mental health, and wearable technologies. Key projects: UBIDENZ (digital empathetic therapy assistance), MITHOS (mixed-reality teacher training), SocialWear (interactive smart fashion), MindBot (mental health in Industry 4.0), EmmA (emotional coaching avatars). Recent research explores emotion regulation strategies, psychodynamic conflict recognition via LLMs, and multimodal sign language corpora development. Collaborates with institutions like Saarland University, contributing to conferences such as CLPsych, LREC-COLING, and ACII. Contact: Patrick.Gebhard@dfki.de

• Hardware Design
• FPGA Programming
• Parallel Computing
• +5 more

Satnam Singh is a Professor at Newcastle University's School of Electrical and Electronic Engineering, UK. With a research career spanning over three decades from 1989 to present, Singh has established himself as a leading expert in hardware design, FPGA programming, and parallel computing systems. His research interests focus on hardware-software co-design , reconfigurable computing , and functional programming applications for hardware design. Singh has pioneered work in using functional languages like Haskell for hardware description and verification, particularly through his contributions to the Lava hardware description language. His work bridges theoretical computer science with practical hardware implementation challenges. Analysis of his publication history reveals a clear evolution from early work on formal verification and FPGA design in the 1990s, through substantial contributions to parallel programming models in the 2000s, to more recent applications of machine learning techniques in diverse domains including cheminformatics and sensory systems. His 2022-2025 publications demonstrate continued innovation in specialized processor programming, AI applications for olfactory systems, and health hazard classification using deep learning. Singh has maintained extensive collaborations throughout his career, notably with Krishna R. Pattipati (15 joint publications), Anuradha Kodali (8 publications), and David J. Greaves (5 publications), reflecting his ability to bridge theoretical computer science with practical engineering applications. His work spans multiple prestigious venues including FPGA, FCCM, ICFP, and IEEE Transactions on Systems, Man, and Cybernetics, demonstrating both theoretical depth and practical impact across computer architecture, programming languages, and applied machine learning domains.