جستجوی استاد راهنمای دانشگاهی

Stephen Meisenbacherمشاهده پروفایل

پژوهشگر

• Privacy-preserving Natural Language Processing (NLP)
• Differential Privacy
• Hybrid, Expert-Driven Classification Systems
• +۵ مورد دیگر

Stephen Meisenbacher is a Research Associate at the Technical University of Munich (TUM) , affiliated with the School of Computation, Information and Technology and the Department of Computer Science, I19 . He has been part of the Software Engineering for Business Information Systems (SEBIS) chair since March 2022. His research focuses on Privacy-Preserving Natural Language Processing (NLP) , Differential Privacy , and Privacy-Enhancing Technologies (PETs) , with a particular interest in their integration into software development and business applications. His work also explores Hybrid, Expert-Driven Classification Systems and Usable Privacy solutions. Stephen’s recent publications address trends in AI Privacy Risks , Text Rewriting with DP , Legal AI Use Cases , and Data Protection Compliance . He has contributed to GDPR-related research and PETs adoption in small enterprises. His teaching includes Natural Language Processing seminars and Software Engineering lecture courses for Master’s and Bachelor’s students at TUM. He also organizes Entrepreneurship for Small Software-Oriented Enterprises seminars. Stephen holds a Master’s in Informatics from TUM (DAAD Graduate Scholarship) and a Bachelor’s in Computer Science from the University of Notre Dame, with additional studies in German Language and Literature. Contact: stephen.meisenbacher@tum.de | LinkedIn

• Responsible Computing
• Data Protection & Governance
• Digital Well-Being
• +۳ مورد دیگر

Asia J. Biega is a tenure-track faculty member (W2) at the Max Planck Institute for Security and Privacy (MPI-SP), where she leads the interdisciplinary Responsible Computing group. She is also a principal investigator of the Cluster of Excellence CASA and the FINDHR consortium. Her work sits at the intersection of computing and society, focusing on responsible computing, data protection & governance, and digital well-being within data-driven and AI-based systems. Dr. Biega's research spans multiple disciplines including computer science, law, philosophy, and social sciences. Her work examines how principles of responsible computing can be computationally operationalized, with particular attention to data protection frameworks, privacy technology governance, and digital well-being. She actively collaborates across disciplinary boundaries to make technical contributions while supporting research in other fields. Her approach combines theoretical rigor with practical applications, often drawing from her industry experience at Microsoft and Google. Her publication record reveals a strong focus on the intersection of fairness, privacy, and transparency in information retrieval systems. She has pioneered work on data minimization compliance, fair ranking algorithms, and user perceptions of data collection practices. Her research consistently bridges technical and legal perspectives, particularly examining how GDPR principles can be computationally implemented. Recent work shows increasing attention to generative AI governance, algorithmic hiring systems, and the relational aspects of data in recommender systems. Dr. Biega has received several prestigious awards including the Council of Europe's Rodotà Award for innovative research in data protection, the SaTML Notable Reviewer Award, the GI-DBIS Dissertation Award of the German Informatics Society, and recognition as one of the '100 Brilliant Women in AI Ethics' in 2025. She has advised numerous PhD students and postdocs who have gone on to faculty positions at institutions including the University of Trieste, Penn State, and the University of Washington. Her research is funded by the Max Planck Society, Alexander von Humboldt Foundation, and the European Union (Horizon Europe FINDHR). She serves as General Co-Chair for ACM FAccT 2025 and has held leadership roles in multiple academic conferences.

• Learning Analytics
• Educational Technology
• Virtual Reality Education
• +۵ مورد دیگر

Ulrik Schroeder is a Universitätsprofessor (Full Professor) at RWTH Aachen University, leading the Chair of Learning Technologies within the Faculty of Computer Science. His research focuses on the intersection of educational technology, learning analytics, and immersive technologies with particular emphasis on practical implementations in higher education settings. Professor Schroeder's research spans multiple interconnected domains in educational technology. His primary interests include Learning Analytics implementation (particularly using xAPI standards), Virtual Reality applications for education, Open Educational Resources development and conversion, and gamification approaches for programming education. He has developed several notable tools including convOERter for OER conversion, WebWriter for creating explorable explanations, and various xAPI-based learning analytics infrastructures. His work consistently bridges theoretical frameworks with practical educational applications, often focusing on computer science education contexts. Analysis of his recent publications reveals a strong trend toward integrating Learning Analytics with immersive technologies, particularly Virtual Reality environments. His research demonstrates a systematic approach to educational technology development, with emphasis on scalability, interoperability through standards like xAPI, and practical implementation in real educational settings. The work increasingly focuses on personalized learning paths, quality assurance for educational resources, and privacy-conscious data collection. Co-editor of 21. Fachtagung Bildungstechnologien (DELFI) (2023) Co-editor of Hochschuldidaktik der Informatik HDI 2018 Co-editor of DeLFI 2018 conference proceedings Professor Schroeder has supervised numerous doctoral and postdoctoral researchers who frequently appear as co-authors on his publications, indicating an active research group. His projects often involve interdisciplinary collaborations across computer science, education, and psychology. Current major initiatives include the AIStudyBuddy project for study path analysis and the development of VR classroom simulations for teacher training. His research group, the Learning Technologies Innovation Lab, develops open research tools that support various aspects of educational technology research and implementation.

• Marketing Analytics
• Electronic Commerce
• Online Advertising
• +۱۱ مورد دیگر

Prof. Dr. Bernd Skiera holds the first chair for electronic commerce in Germany at Goethe University Frankfurt am Main since 1999. He serves on the board of efl - The Data Science Institute and the Schmalenbach Society, while representing Germany at the European Marketing Community (EMAC). Chair of Marketing, Goethe University Frankfurt am Main Board member, efl - The Data Science Institute National representative, European Marketing Community (EMAC) His research focuses on MarTech/SalesTech integration, customer value management, online advertising analytics, data-driven pricing models, and the economic implications of internet privacy regulations. He leads the ERC Advanced Grant project on cookie usage restrictions' economic consequences. Recent publications examine dynamic pricing in digital markets, competition visualization using big data, and AI applications in marketing analytics. The ERC Advanced Grant research has produced empirical analyses of GDPR impacts on advertising ecosystems. 2015 Journal of Marketing Best Paper Award 2013 International Journal of Research in Marketing Best Paper Award Multiple MSI/H. Paul Root Award recognitions He has mentored 17 doctoral students who became professors globally, including at London Business School and LMU Munich. His work bridges marketing analytics with financial valuation through customer equity modeling.

• Database Systems
• Graph Databases
• Data Management
• +۷ مورد دیگر

Amol Deshpande is a Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley, College of Engineering. With over 160 publications spanning from 2000 to 2025, his research has significantly impacted the database systems community. His work bridges theoretical foundations with practical systems, evidenced by numerous publications in top-tier venues including SIGMOD, VLDB, and ICDE. Professor Deshpande's research focuses on database systems, with particular expertise in graph databases, data management, probabilistic databases, query optimization, and data provenance. His work addresses fundamental challenges in managing complex data, including efficient graph analytics, dataset versioning, streaming data processing, and privacy-preserving data management. Recent research directions include entity-relationship abstractions beyond traditional relations, standalone catalog engines for large data systems, and graph theoretical approaches to dataset versioning. His publication trends show a consistent focus on evolving database technologies, with early work on probabilistic databases and query optimization, transitioning to graph analytics and data provenance, and more recently addressing modern challenges in data cataloging, privacy-first data management, and serverless stream processing. His research spans both theoretical contributions (e.g., approximation algorithms for stochastic optimization) and practical systems building (e.g., RStore, TreeCat). Professor Deshpande has mentored numerous PhD students who have become active researchers in the database community, including Hui Miao, Souvik Bhattacherjee, and Konstantinos Xirogiannopoulos. His collaborative work spans across institutions, with frequent collaborations with researchers from MIT, University of Maryland, and other leading institutions. His research has been supported by major funding agencies and has influenced both academic research and industry practices in data management. The evolution of his work reflects the changing landscape of data management, from traditional relational systems to modern graph and streaming data challenges.

• Web Security
• Software Security
• Secure Programming
• +۳ مورد دیگر

Prof. Dr. Martin Johns serves as Chair of Application Security at the Institute for Application Security within the Carl Friedrich Gauss Faculty at Technical University Braunschweig. He joined TU Braunschweig after working as Research Expert at SAP Security Research, where he shaped security strategy and led software security teams. Prior to SAP, he worked as software engineer in Germany at companies like TC Trustcenter and Infoseek Germany. Academic qualifications include a PhD in Computer Science (University of Passau, 2009) and a Diploma in Computer Science (University of Hamburg, 2003). His research focuses on web security and software security , particularly secure programming , vulnerability detection , and attack mitigation strategies. Recent publications cover topics like GDPR compliance frameworks , WebAssembly security , federated learning privacy , and server-side request forgery (SSRF) defenses. His work appears in top conferences including IEEE S&P, CCS, WWW, and ACM CODASPY.

• Marketing Analytics
• Electronic Commerce
• Online Advertising
• +۸ مورد دیگر

Prof. Dr. Bernd Skiera is a leading Marketing Professor at Goethe University Frankfurt since 1999 and a member of the managing board of the efl - The Data Science Institute. His work bridges information systems and marketing, with a focus on data-driven decision making and digital transformation.

Martin Stürzlingerمشاهده پروفایل

استاد

• Digital Archiving
• Electronic Records Management
• OAIS Model
• +۵ مورد دیگر

Dr. Martin Stürzlinger is a Part-Time Professor for Digital Archiving at the Department of Information Sciences, University of Applied Sciences Potsdam. He also operates his consulting firm Archiversum, advising organizations on long-term information storage (www.archiversum.com). His work bridges academic research with practical applications in digital preservation. Research Interests: Dr. Stürzlinger specializes in digital archiving, focusing on the OAIS model, life-cycle management, and archival description standards like Records in Contexts (RiC). His research addresses organizational challenges in digital preservation, legal compliance (e.g., GDPR), and metadata design for accessibility. Recent Publications: His selected works explore OAIS implementation, the impact of GDPR on private archives, and the evolution of archival description standards. These contributions highlight trends in digital preservation, emphasizing interoperability, sustainability, and cross-institutional collaboration. Collaboration & Standards: He actively contributes to international working groups, including ICA-EGAD (Archival Description) and nestor's certification standards for digital archives. His efforts in standardization include the Austrian implementation of ISAD(G) and ISDIAH, as well as Swiss guidelines for electronic records management. Teaching & Outreach: Dr. Stürzlinger has lectured extensively, including courses on archive management at BFI Vienna and IT applications in archives at the University of Vienna. He has delivered over 40 lectures globally, addressing topics like cost estimation for digital archiving and the role of corporate archives in business efficiency.

Oliver Gasserمشاهده پروفایل

پژوهشگر

• Internet Measurement
• IPv6
• BGP
• +۹ مورد دیگر

Oliver Gasser is a researcher at the Max Planck Institute for Informatics (MPI-INF) and the Technical University of Munich (TUM), where he has co-lectured courses such as Advanced Computer Networking and Master Course Computer Networks. His research focuses on Internet measurement, security, and privacy, with a strong emphasis on IPv6, DNS, BGP, and web tracking technologies. His research interests include Internet measurement, IPv6 deployment, BGP security, DNS infrastructure, web tracking, privacy technologies, and network resilience. He has made significant contributions to understanding IPv6 hitlists, router fingerprinting, hypergiant content delivery networks, and consent banner manipulation on the web. His work combines large-scale active measurements with data analysis to uncover systemic issues in Internet infrastructure and privacy practices. The recent publications highlight a consistent focus on measurement-driven research across networking, security, and privacy. Trends include analyzing IPv6 adoption patterns, detecting covert tracking mechanisms in web cookies, evaluating security of Internet protocols like DNS and BGP, and improving measurement methodologies for large-scale network studies. His work often involves developing open tools and datasets that advance reproducibility in networking research. PAM 2023 Best Paper Award TMA 2023 Best Paper Award TMA 2023 Fast Track Award PAM 2018 Best Paper Award IRTF Applied Networking Research Prize 2018 IMC 2017 Community Contribution Award TMA 2017 Best Dataset Award CoNEXT 2023 Community Contribution Award Oliver Gasser has advised or co-advised over 40 master’s and bachelor’s theses at MPI-INF and TUM, demonstrating strong mentorship in academic research. He has led several measurement projects that have received external funding, including development of the IPv6 Hitlist Service and tools for analyzing web tracking. His community service includes extensive participation in program committees for major networking conferences such as IMC, CoNEXT, PAM, and TMA. He leads and contributes to several open research initiatives including the IPv6 Hitlist Service, SNMPv3 Measurement Service, MPTCP Measurement Service, DNS Observatory, and the BannerClick tool for automated cookie banner interaction. These platforms provide valuable resources for the global networking research community and support reproducible science.

• Computer Security
• Network Security
• Systems Security
• +۴ مورد دیگر

Nuno Santos is an Associate Professor in the Department of Computer Science and Engineering at Instituto Superior Técnico (IST), University of Lisbon, and a senior researcher at INESC-ID Lisbon. He leads the SysSec team, focusing on systems security and privacy. His research spans secure enclaves, network security, and censorship-resistant systems. Education: Ph.D. in Computer Science (2013) from Max Planck Institute for Software Systems (MPI-SWS) in affiliation with Saarland University. Visiting research stints at Vrije Universiteit Amsterdam (2018) and Technical University of Munich (2024). Research Interests: Systems security, privacy, trusted execution environments (TEEs), network security, censorship resistance, AI security, and secure cloud computing. He has pioneered work on mitigating vulnerabilities in TrustZone-based TEEs and enhancing confidential computing. Publications: Over 30+ peer-reviewed articles in top-tier venues like S&P, USENIX Security, CCS, and NDSS. Recent trends focus on AI-driven security (e.g., automated exploit generation, prompt-to-SQL injections) and confidential computing (e.g., AMD SEV-SNP analysis). Awards: IST Outstanding Teaching Award (2019/2020), 2024 Prémio Científico Universidade de Lisboa/Caixa Geral de Depósitos. Advising & Grants: Supervised MSc theses in areas like AI-powered vishing attacks and confidential VMs. Active in conference organization (e.g., USENIX Security’25 Vice Chair, IEEE EuroSP’26 Co-Chair). Labs/Teams: Leads the SysSec team at INESC-ID Lisbon, collaborating on projects like AnyTEE (TEE framework) and FlowLens (network security tool).

Michael Beurskensمشاهده پروفایل

استاد

• Private Law
• Business Law
• Digital Law
• +۵ مورد دیگر

Prof. Dr. Michael Beurskens is a faculty member at the Faculty of Law of the University of Passau , holding the Chair of Private Law, especially Business Law and Digitalisation . His work integrates Private Law , Competition Law , and Intellectual Property Law with Digitalization challenges, focusing on AI regulation, data access, and GDPR compliance. Academic Background: LL.M. in Intellectual Property Rights (University of Chicago) LL.M. in Gewerblicher Rechtsschutz Attorney-at-Law (New York) Habilitation: University of Düsseldorf, 2007 His research interests span the legal frameworks governing online platforms (Digital Markets Act, Digital Services Act), data trading (Data Act, Data Governance Act), AI regulation (AI Act), and copyright (InfoSoc Directive, DSM Directive). He emphasizes practice-oriented research and team-based academic collaboration , including social activities like weekly lunches and access to central ice cream supplies. Key teaching activities include courses on Corporate Law , Commercial Law , Law of Obligations , and Intellectual Property , with a focus on e-learning projects such as Schuldrecht AT Online and Gesellschaftsrecht Online. He advocates for student-led research and early publication opportunities . The chair actively promotes women in science through preferential employment and intensive supervision. It also develops legal tech tools like Visilex (jurisprudence flashcards) and CASIM (case simulation software).

• Competition Law
• Digital Regulation
• Energy Law
• +۳ مورد دیگر

Dr. Jasper van den Boom is currently a Postdoctoral Research Fellow at the Chair for Civil Law, German and European Competition Law at Heinrich Heine University Düsseldorf. He holds a Master’s degree from Tilburg University in European Economic & Competition Law and completed his PhD there with a thesis on digital market regulation. His research focuses on competition law, digital regulation, energy law, and cybersecurity. He has taught at Utrecht University and supervised theses on competition law and digital governance. Key achievements include nominations for the Tilburg University Dissertation Award and KNHW Award for interdisciplinary work. His research spans topics like Digital Markets Act (DMA) enforcement mechanisms, ecosystem competition analysis, and cybersecurity policy. He contributed to policy reports for the Dutch National Cybersecurity Centre and co-authored studies on EU competition law’s interactions with digital markets. Dr. van den Boom’s work bridges legal frameworks with technological and economic realities, emphasizing practical regulatory solutions for modern challenges in digital ecosystems and energy sectors.

Lionel C. Briandمشاهده پروفایل

استاد

• Software Engineering
• Software Verification and Validation
• Trustworthy AI
• +۶ مورد دیگر

Lionel C. Briand is a Professor of Software Engineering with shared appointments at the University of Luxembourg's SnT Centre for Security, Reliability, and Trust and the School of Electrical Engineering and Computer Science at the University of Ottawa. He holds a Canada Research Chair (Tier 1) in Intelligent Software Dependability and Compliance and serves as Director of Lero, Ireland's national software research center. His academic leadership spans over 25 years of collaborative research with industry partners across automotive, aerospace, energy, financial, and legal domains. Professor Briand's research focuses on software verification and validation, trustworthy AI systems, model-driven engineering, and empirical software engineering methodologies. His work bridges theoretical foundations with industrial applications, particularly in cyber-physical systems where machine learning components interact with safety-critical control systems. He has pioneered techniques for testing AI-enabled systems, GDPR compliance automation, and mutation analysis for space systems. His publication portfolio demonstrates consistent innovation in software testing, with recent emphasis on large language models for test generation, automated compliance checking, and safety analysis of deep neural networks. Key trends include black-box testing methodologies, metamorphic testing for security, and search-based approaches for DNN validation. IEEE Fellow and ACM Fellow IEEE Computer Society Harlan Mills Award (2012) ACM SIGSOFT Outstanding Research Award (2022) IEEE Reliability Society Engineer-of-the-Year Award (2013) ERC Advanced Grant recipient (2016) Fellow of the Academy of Science, Royal Society of Canada (2023) ICSE 2011 Most Influential Paper Award As Director of Lero and holder of a Canada Research Chair, Professor Briand leads major research initiatives including an ERC Advanced Grant on cyber-physical system modeling and testing. His industrial collaborations generate substantial grant funding, particularly in automotive safety validation and regulatory compliance automation. He mentors numerous researchers through his dual appointments and serves on program committees for top software engineering conferences. Professor Briand directs research activities at the SnT Centre's SVV department, focusing on software verification and validation. His team develops practical tools like MASS for space system mutation analysis and COREQQA for compliance requirements understanding, with strong industry adoption in automotive and aerospace sectors.

• Cyber Security
• Cryptography
• Steganography
• +۶ مورد دیگر

Rainer Böhme is a Professor at the University of Münster, Germany. His research focuses on cyber security, cryptography, steganography, digital forensics, and blockchain technology. He has made significant contributions to understanding cyber risk quantification, central bank digital currencies (CBDCs), and the socio-technical challenges in cryptocurrency systems. Key areas of research include steganalysis (analysis of hidden data in digital media), forensic techniques for neural network inference pipelines, and the economic implications of cyber insurance. He actively contributes to conferences like the Financial Cryptography Workshops (FC) and the Workshop on Information Hiding and Multimedia Security (IH). Böhme's work bridges theory and practice, addressing real-world issues such as privacy in CBDCs, adversarial attacks on AI systems, and the role of law enforcement in cryptocurrency markets. His recent studies explore the security implications of image orientation in JPEG files and the detection of privileged parties in blockchain transactions. He has collaborated with institutions like the University of Vienna and ETH Zurich, and his research has been published in top-tier venues such as IEEE Transactions on Information Forensics and Security and the ACM Conference on Computer and Communications Security (CCS).

Laura Stateمشاهده پروفایل

پژوهشگر ارشد

• Artificial Intelligence
• AI Ethics
• Explainable AI
• +۳ مورد دیگر

Laura State serves as a Research Fellow at the Humboldt Institute for Internet and Society (HIIG) in Berlin, Germany, where she contributes to the AI & Society Lab's Impact AI project. This initiative develops transdisciplinary auditing methodologies to evaluate artificial intelligence systems' contributions to societal transformation and ecological sustainability through rigorous impact assessment frameworks. Her academic credentials include: PhD in Data Science from Scuola Normale Superiore, Pisa, Italy (Advised by Salvatore Ruggieri and Franco Turini) MSc in Neural Information Processing from the University of Tübingen BSc in Physics from the University of Rostock State's research synthesizes hard sciences with social perspectives to investigate AI's societal and planetary implications. She specializes in transparency and accountability mechanisms for non-interpretable machine learning models, developing assessment methodologies to determine how AI can foster sustainable futures. Her interdisciplinary approach integrates technical AI development with regulatory frameworks and ecological impact analysis, emphasizing real-world applicability through industry-academia collaboration. Her 2023-2025 publications reveal a cohesive research trajectory centered on explainable AI and regulatory compliance, particularly regarding GDPR requirements. Key themes include legal-technical alignment for explanation systems, bias/fairness policy frameworks, and innovative evaluation tools like REASONX. The work consistently bridges machine learning theory with societal accountability, demonstrating methodological rigor in translating technical capabilities into public-interest applications. As a core member of HIIG's AI & Society Lab, State collaborates on transdisciplinary teams examining AI's role in sustainability transitions. The Impact AI project coordinates researchers from computer science, law, and social sciences to develop evaluation frameworks that measure AI's contribution to UN Sustainable Development Goals, with active engagement in policy dialogues and public science initiatives like Lange Nacht der Wissenschaften.