جستجوی استاد راهنمای دانشگاهی

Marian Benner-Wicknerمشاهده پروفایل

استاد

• Software Engineering
• E-Learning
• Case Management
• +۷ مورد دیگر

Prof. Marian Benner-Wickner is a Professor of Computer Engineering at IU University of Applied Sciences, where he has been a faculty member since 2018. He leads the Industrial Engineering & Management and Industry 4.0 online study programs, focusing on software engineering and gender-neutral e-learning methodologies. His professional background includes roles as an IT specialist trainer at CampusLab GmbH and a software developer at the Fraunhofer Institute for Software and Systems Technology. He holds a PhD in Software Engineering (2016) from the University of Duisburg-Essen, where he managed the “Agenda-Driven Case Management” research cluster. His research interests span software engineering, case management techniques, process flexibility, smart home technologies, and digital youth protection. Notable contributions include work on adaptive case management systems, ontology-based recommendation systems, and e-learning metadata frameworks. Prof. Benner-Wickner actively contributes to organizations like the Wikimedia Foundation, CPS.HUB NRW, and the Society for Computer Science. His publications address topics such as IT integration architectures, automated grading systems, and security frameworks in mobile networks. His recent projects emphasize integrating IT applications, enhancing educational technologies, and optimizing knowledge-intensive business processes through semantic web technologies and process mining. In advising and grants, he oversees company-specific final theses in IT and technology, emphasizing practical industry collaboration. He has developed guidelines for design science research in academic works and advocates for empirical approaches to software process improvement. His leadership in Industry 4.0 programs reflects his commitment to bridging academic research with industrial applications. Leveraging his role as department head, he fosters innovation in curriculum design, particularly in leveraging digital tools for inclusive and adaptive learning environments. His interdisciplinary work intersects computer science, education, and policy, addressing societal challenges like digital youth protection and smart home security.

Niklas Mückمشاهده پروفایل

پژوهشگر

• Formal Methods
• Programming Languages
• Type Theory
• +۳ مورد دیگر

Niklas Mück is a PhD student at the Max Planck Institute for Software Systems in Saarbrücken, Germany, co-advised by Derek Dreyer and Deepak Garg. His research focuses on robust compilation techniques and formal verification within the semantic multi-language framework DimSum. He holds a Bachelor's degree from Saarland University. Education: Bachelor's degree in Computer Science, Saarland University Research Interests: His work integrates formal methods and programming language theory to ensure correctness in complex systems. Key areas include: - Compilation to capability machines - Theoretical foundations of type systems (Calculus of Inductive Constructions) - Semantic analysis for property preservation. Teaching Contributions: Teaching Assistant for courses like Pearls of Functional Programming (2025), Semantics (2023/24), and Mathematics Preparatory Courses (2020–2023) Main Organizer for Introduction to Computational Logic (2023) Research Trends in Publications: His publications emphasize bridging abstract theory (e.g., Kleene-Post theorems) with practical compiler design, leveraging semantic frameworks for rigorous guarantees. Recent work explores computability and reducibility in formal systems. Labs/Teams: Active contributor to the DimSum framework development team.

• Algorithms
• Theoretical Computer Science
• Programming Languages & Verification
• +۴ مورد دیگر

Scott DellaTorre is affiliated with the Max Planck Institute for Software Systems (MPI-SWS), where he contributes to research in Algorithms, Theory & Logic. His work spans Programming Languages & Verification, Cyber-Physical Systems, and Security & Privacy, reflecting a focus on foundational and applied computer science challenges. His research interests include Distributed Systems, Networked & Mobile Systems, and Social & Information Systems, indicating a blend of theoretical rigor and practical applications. While specific grants, awards, or advising roles are not detailed here, his affiliation suggests active participation in cutting-edge interdisciplinary research at MPI-SWS.

• Algorithms
• Theory & Logic
• Programming Languages & Verification
• +۴ مورد دیگر

Dip Nag is a researcher at the Max Planck Institute for Software Systems (MPI-SWS), focusing on interdisciplinary research areas including algorithms, programming languages, security, and distributed systems. His work spans theoretical foundations and practical applications in cyber-physical systems and social information systems. While specific academic rank details are not explicitly stated, his affiliation with the MPI-SWS Faculty section indicates a senior research role within the institute. No formal educational background, grants, or awards are documented in the provided text. Research interests prominently feature: Cyber-Physical Systems design and verification Security protocols for distributed networks Formal logic in programming language semantics Algorithmic foundations for social computing systems No recent publications or student advising records are listed in the provided materials.

Julius Reimerمشاهده پروفایل

پژوهشگر

• Journalism Studies
• Digital Journalism
• Media Research
• +۵ مورد دیگر

Julius Reimer is a Researcher at the Leibniz Institute for Media Research | Hans-Bredow-Institut (HBI) in Hamburg, Germany. His work focuses on the evolving dynamics of journalism in the digital age, particularly the shifting journalism-audience relationship, innovative reporting styles, automation in news production, and personal branding in journalism. He leads the German Research Foundation (DFG)-funded project "Journalism and Its Audience: the Re-Figuration of a Relationship and Its Influence on News Production," exploring how audience engagement impacts journalistic practices. Reimer holds an M.A. in Communication Science, Economic Policy, and Sociology from the University of Münster and the Università della Svizzera italiana in Lugano. He has extensive research experience, including roles as a research assistant at TU Dortmund University and involvement in projects like “(Re-)Discovering the Audience,” “SCAN,” and “When Data Become News.” His research interests span digitization’s impact on journalism, organizational innovation, transparency in media, and the role of startups in news production. Recent contributions include co-authorship in the second edition of the Routledge Companion to Digital Journalism Studies and participation in the Nomos Handbook on Journalism Research . Reimer has been active in academic networks, including chairing the German Young Scholars Network in Journalism Research (NaJoFo) from 2018–2020. His current projects also include studies on local news platforms like molo.news and ethical boundaries in algorithmic news production.

• Machine Learning
• Artificial Intelligence
• Stochastic Games
• +۵ مورد دیگر

Xian Chen is an active academic researcher with an extensive publication record spanning over 30 years from 1994 to 2025. Their research demonstrates significant contributions across multiple disciplines within computer science, engineering, and applied mathematics. The publication pattern indicates sustained scholarly activity at a high level, with numerous papers in top-tier journals and conferences. Chen's research interests span a remarkably diverse range of fields, with particular emphasis on machine learning, artificial intelligence, stochastic processes, and their applications across various domains. Their work bridges theoretical foundations with practical applications, as evidenced by publications in both theoretical journals like SIAM Journal on Control and Optimization and applied venues like IEEE Access . The research portfolio shows evolution from early work in parallel computing and wireless networks toward contemporary AI and machine learning applications. The publication record reveals significant trends in Chen's research trajectory. Early work focused on parallel computing, wireless networks, and database systems. Over time, there's a clear shift toward machine learning applications, optimization techniques, and interdisciplinary work connecting computer science with fields like biomedical engineering, renewable energy, and education technology. Recent publications (2024-2025) show strong focus on large language models, federated learning, hate speech detection, and educational AI applications, reflecting current trends in artificial intelligence research. The consistent output across multiple domains suggests a highly collaborative research approach with numerous co-authors across different institutions. Chen has established productive collaborations with researchers worldwide, as evidenced by the diverse author lists across publications. The research demonstrates both theoretical depth in areas like stochastic games and Markov decision processes, as well as practical applications in fields ranging from medical diagnostics to renewable energy systems. The interdisciplinary nature of the work indicates versatility in applying computational methods to solve domain-specific problems.

• Algorithms
• Theory & Logic
• Programming Languages & Verification
• +۴ مورد دیگر

David Swasey is a researcher at the Max Planck Institute for Software Systems (MPI-SWS), focusing on formal methods, programming languages, and system security. His work spans theoretical foundations of verification, secure compilation, and language design, with contributions to frameworks like Iris for concurrent reasoning and formal modeling of mobile systems. Research interests include algorithms, logic, cyber-physical systems, and distributed networks. His publications address challenges in robust verification, object-capability patterns, and enhancing security in systems like Android. He has explored modular compilation for Standard ML and cross-domain security protocols. Publications highlight a trajectory from foundational type system research to applied security solutions, with an emphasis on formal methods bridging theory and practice. No awards or grants are explicitly mentioned in the provided text.

• Algorithms
• Theory & Logic
• Programming Languages & Verification
• +۴ مورد دیگر

Ali Zarezade is a researcher at the Max Planck Institute for Software Systems (MPI-SWS), focusing on interdisciplinary research spanning algorithms, machine learning, and social computing. His work integrates theoretical foundations with practical applications in cyber-physical systems, distributed networks, and human-centric AI. Key research areas include human-in-the-loop machine learning, optimal control strategies for social networks, and spatio-temporal modeling of social media activity. His methods often combine stochastic control theory, sparse regression techniques, and online algorithm design to address challenges in education technology, security, and information diffusion. Prior contributions involve developing algorithms like RedQueen and Cheshire for optimizing social network activity, probabilistic models for hyperspectral unmixing, and visual tracking systems resilient to occlusions. His research bridges computational theory with real-world systems, emphasizing scalable solutions for distributed and networked environments.

Ali Behrouzمشاهده پروفایل

پژوهشگر

• Algorithms
• Theory & Logic
• Programming Languages & Verification
• +۹ مورد دیگر

Ali Behrouz is a researcher affiliated with the Max Planck Institute for Software Systems (MPI-SWS), part of the Max Planck Society. His research focuses on advanced topics such as algorithms, theory and logic, programming languages and verification, cyber-physical systems, distributed and networked systems, security and privacy, and social/information systems. His work bridges theoretical foundations with practical applications in computational systems and their societal implications.

Martin Schäferمشاهده پروفایل

پژوهشگر

• Applied Mathematics
• Harmonic Analysis
• Approximation Theory
• +۳ مورد دیگر

Dr. Martin Schäfer is a Researcher at the Chair of Applied Analysis within the Faculty of Mathematics at Chemnitz University of Technology. His research focuses on advanced mathematical frameworks such as α-molecules, coorbit space theory, and approximation methods in harmonic analysis. He earned his Diploma in Mathematics from the University of Bonn (2012) and completed his PhD at the Technical University of Berlin (2018) with a thesis on α-molecules. His work bridges pure and applied mathematics, addressing challenges in signal processing, image analysis, and high-dimensional approximation. Key research interests include approximation theory, Fourier analysis, function spaces, and the development of adaptive representation systems like shearlets and curvelets. Schäfer has contributed to conferences such as the International Conference on Multivariate Approximation (2016) and the GAMM Annual Meeting (2014), presenting on topics like phase retrieval and sparse recovery. His publications explore theoretical foundations of wavelet systems and their applications in optimal function recovery and sampling problems. Notable achievements include establishing new upper bounds for sampling numbers and developing subsampling techniques for finite frames. While no specific awards are listed, his prolific publication record in top journals like Applied and Computational Harmonic Analysis and Journal of Fourier Analysis and Applications highlights his academic impact. Schäfer collaborates internationally, evidenced by his participation in workshops in Germany, Canada, and the USA.

• Software Engineering
• Formal Verification
• Software Model Checking
• +۳ مورد دیگر

Dirk Beyer is a Full Professor of Software Engineering and Formal Verification at the Department of Computer Science, Ludwig-Maximilians-Universität München (LMU). He leads the Software and Computational Systems Lab (SOSY-LAB) and focuses on developing models, algorithms, and tools for constructing and analyzing reliable software systems. His research includes software model checking, static analysis, formal verification of real-time systems, and software structure analysis. Key contributions include the development of tools like CPAchecker (a configurable software verification system), CCVisu (for visual software decomposition), and BLAST (a foundational software model checker). He actively participates in international competitions such as SV-COMP (Software Verification Competition) and Test-Comp (Software Testing Competition), advancing the state of the art in automated verification and testing. His work emphasizes tool integration, off-the-shelf component composition, and cooperative verification approaches. Dirk also contributes to the formal methods community through service roles, including organizing conferences like TACAS and VMCAI, and co-chairing international events.

Jakob Zechمشاهده پروفایل

استاد

• Uncertainty Quantification
• High-Dimensional Approximation
• Sparse-Grid Techniques
• +۴ مورد دیگر

Jakob Zech is a Professor at the Interdisciplinary Center for Scientific Computing (IWR) at Heidelberg University since April 2020. Before this, he held postdoctoral positions at MIT (2019-2020) and ETH Zürich (2018-2019). He earned his PhD in Mathematics from ETH Zürich in 2018, focusing on Sparse-Grid Approximation of High-Dimensional Parametric PDEs, followed by a Master’s (2014) and Bachelor’s (2012) in Applied Mathematics from ETH Zürich and TU Wien, respectively. Research Interests : Zech’s work bridges Uncertainty Quantification (UQ), high-dimensional approximation, and computational mathematics. Key areas include sparse-grid techniques, neural networks, transport methods, Bayesian inverse problems, and the theoretical foundations of deep learning. His research emphasizes developing algorithms for stochastic modeling and analyzing their mathematical properties. Teaching : He has taught advanced courses such as High Dimensional Approximation, Theory of Deep Learning, and Numerical Methods for Bayesian Inverse Problems at Heidelberg University. He also served as a teaching assistant for numerous courses at ETH Zürich, covering numerical analysis, partial differential equations, and linear algebra. Publications : His recent work explores quantum computing applications in polynomial chaos expansions, statistical learning theory for neural operators, and multilevel optimization strategies. His articles reflect a strong focus on combining classical numerical methods with modern machine learning techniques. Labs/Teams : While no specific lab is mentioned, his research group is active in computational UQ and deep learning, collaborating internationally with institutions like MIT and ETH Zürich.

Thilo Kleinمشاهده پروفایل

استاد

• Market Design
• Matching Theory
• Empirical Methods
• +۵ مورد دیگر

Thilo Klein is a Professor of Quantitative Economics at Pforzheim University and a Senior Economist at the ZEW Research Institute in the Market Design Department. He holds a PhD in Business Economics and an MPhil in Operations Research from the University of Cambridge. His research focuses on market design applications in allocation systems, including matching markets for childcare, food donations, environmental subsidies, and microfinance. Key contributions include developing deferred acceptance algorithms for fair childcare assignment and analyzing the impact of market rules on policy outcomes. Education: PhD and MPhil in Economics from University of Cambridge. Prior to academia, he worked at OECD, ILO, and Spandana (India). Funded projects include grants from DAAD, ESRC, Leibniz Association, and German Federal Ministry of Agriculture. Awards include the ZEW Prize for Best Economic Consulting Project. Research emphasizes combining microeconomic theory with empirical methods to design efficient and equitable allocation mechanisms. Notable software contributions include the R package matchingMarkets for structural estimation and algorithm implementation. He also coordinates the KitaMatch platform for childcare allocation solutions. Teaching includes quantitative methods at Pforzheim University and advanced courses at institutions like University of Cambridge. Awards: ZEW Sponsors' Association Prize for Best Economic Consulting Project (202X). Grants: Led projects funded by DAAD, ESRC, Leibniz Association, Bertelsmann Foundation, and German Federal Ministry of Food and Agriculture. Consulting focuses on applying market design principles to public sector challenges. Active in policy briefs for efficient food donation systems and environmental subsidy mechanisms. Software tools include the KitaMatch Toolbox and matchingMarkets package for stable matching analysis.

Bozana Meinhardt-Injacمشاهده پروفایل

استاد

• Developmental Psychology
• Socio-emotional Development
• Human-Technology Interaction
• +۴ مورد دیگر

Prof. Bozana Meinhardt-Injac holds a professorship in Psychology with a focus on Developmental Psychology at the Katholische Hochschule für Sozialwesen Berlin. Her research explores socio-emotional development across the lifespan, human-technology interaction, and AI applications in Social Work, Health, and Education. She teaches foundational psychology, lifespan developmental psychology, and quantitative research methods. Her work integrates empirical studies on facial emotion processing, digital skill development, and the ethical implications of AI in social services. Notable projects include analyzing emoji adoption patterns in aging populations and evaluating VR platforms for mental health support. Publications span from 2007 to 2025, reflecting a focus on cognitive aging, technology acceptance, and neurodevelopmental challenges. ORCID: 0000-0001-7023-8100 . Research highlights include the role of texture in face perception, developmental trajectories of theory of mind, and the impact of irrelevant auditory stimuli on memory recall. Methodological contributions include designing validated face-processing tasks and evaluating immersive VR systems for stroke rehabilitation.

Armin Beverungenمشاهده پروفایل

استاد

• Sociology of Organization and Economy
• Digital Media Technologies
• Algorithmic Management
• +۹ مورد دیگر

Armin Beverungen is Professor for the Sociology of Organisation and Economy at Leuphana University Lüneburg and an associated member of the Centre for Digital Cultures. His academic work spans sociology, organization studies, media studies, and science and technology studies, with a particular focus on the intersections between digital technologies and organizational forms. Dr. Beverungen received his PhD in critical management studies from the University of Leicester. His academic journey includes research and teaching positions at the University of the West of England, Leuphana University, and the University of Siegen. From September 2022 to August 2023, he was on leave at Leuphana and served as a visiting professor at the Institute for Media Studies at Ruhr-University Bochum. He also regularly teaches in the technologies section of the contextual studies program at the University of St. Gallen. His research interests center on digital (media) technologies and organization; algorithmic management, automation and artificial intelligence; and smart, logistical cities. He has made significant contributions to understanding the financialization of universities, corporate governance, business ethics, and the politics of labor. His work critically examines how digital platforms, particularly Amazon, reshape urban spaces, labor relations, and organizational forms. Beverungen has been instrumental in establishing the Centre for Digital Cultures at Leuphana over the past decade, which has expanded his research to engage more deeply with media studies and science and technology studies. Dr. Beverungen's recent publications reveal a consistent focus on the organizational implications of digital technologies, particularly examining Amazon's logistical operations and urban interventions. His work demonstrates interdisciplinary reach, connecting sociology, media studies, urban studies, and organizational theory. A significant portion of his research analyzes how algorithmic systems reshape labor, urban space, and organizational forms, with particular attention to the political dimensions of these transformations. Member of editorial collective of 'ephemera: theory & politics in organization' (10 years) Founding editor of 'spheres: Journal for Digital Cultures' Founding editor of 'Digital Cultures' book series Associate editor of 'Organization: the critical journal of organization, theory and society' At Leuphana, Dr. Beverungen serves as deputy director of the MA program in Cultural Studies: Culture and Organization, and is a member of the study commission for MA programs in the Faculty of Humanities and Social Sciences. He regularly supervises BA and MA theses and is available for PhD supervision. His current research is supported by two major projects: 'Automating the Logistical City: Space, Algorithms, Speculation' (Volkswagen Foundation) and 'Smartness as Wealth' (Volkswagen Foundation). Dr. Beverungen has been involved with the Digital Cultures Research Lab (2017-2022) and continues to contribute to digital culture studies at Leuphana University. His interdisciplinary approach bridges sociology, media studies, and organization theory, creating innovative frameworks for understanding contemporary digital transformations.