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Peter HertkornView profile

Professor

• Model-Driven Software Development
• Domain-Specific Languages
• DevOps Automation
• +2 more

Prof. Peter Hertkorn is a full professor of Computer Science at Reutlingen University's Faculty of Computer Science, specializing in programming languages and databases. He holds leadership roles including Chair of the Examination Board for Media and Communication Informatics B.Sc. and BAföG Officer for the same program. His research focuses on model-driven software development, domain-specific languages, DevOps automation, interactive learning technologies, and distributed ledger technologies. He co-leads the Software Engineering and User Experience (swuxLAB) and Distributed Ledger Technologies (DLT-LAB) research groups. Education background includes a Diplom-Informatiker (master's equivalent) and Dr.-Ing. (PhD) from University of Stuttgart. Professional experience includes 5 years at T-Systems International GmbH and prior academic roles at University of Stuttgart. His teaching focuses on Software Engineering and Database Systems courses. Publications span interactive learning environments, collaborative innovation systems, and AR-based knowledge spaces. Active in academic service roles and interdisciplinary research collaborations since 2009.

Yue LiView profile

Associate Professor

• Program Analysis
• Programming Languages
• Static Program Analysis
• +3 more

Yue Li is an Associate Professor at the School of Computer Science, Nanjing University, where they co-run the PASCAL Research Group with Tian Tan. Their work focuses on static program analysis techniques and tools for programming languages, software engineering, security, and hardware verification. PhD in Computer Science from UNSW Sydney (2016) Postdoctoral research at Aarhus University (Denmark) and UNSW Sydney B.Eng and M.Eng from Northwestern Polytechnical University (2010, 2012) Research interests center on Program Analysis and Programming Languages , with a focus on: Pointer analysis for database-backed applications Context sensitivity optimization Reflection analysis in Java/Android Operational semantics for hardware languages Distributed dataflow analysis frameworks Developer-friendly static analysis tools Key publication trends (2016-2025) span static analysis , pointer precision , reflection handling , and tool frameworks across conferences like OOPSLA, PLDI, ICSE, ISSTA, and journals including TOPLAS and IEEE TSE. Notable artifacts include Tai-e and Chianina systems. 2025: ICSE Best Artifact & Distinguished Paper Awards 2024: IEEE TSE Publication on Generic Sensitivity 2023: OOPSLA Distinguished Artifact, SPLASH/ECOOP committees 2021: National Youth Talent Support Program, ZiJin Scholar 2016: ECOOP Distinguished Paper, CGO Best Paper As co-PI of PASCAL Research Group, they lead projects on precision-guided analysis, microservice systems, and cloud-based dataflow frameworks, with teaching awards for SICP and Software Analysis courses.

• Mobile Computing
• Mobile Cloud Computing
• Context-aware and -adaptive Applications
• +1 more

Dr. Gabriel Orsini is a researcher at the Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Hamburg. He works on context-adaptive systems for mobile cloud computing and has developed the CloudAware middleware framework. PhD (2017): Kontextadaptive Anwendungsarchitekturen für das mobile Cloud Computing Diploma Thesis (2008): Maschinelles Lernen zur Prognose von Erlösen im Luftverkehr His research focuses on mobile cloud computing , context-aware systems , and resource optimization through dynamic adaptation. Article trends show expertise in context adaptation , energy efficiency , and IoT integration . Professional activities include: Guest Editor for Forecasts in the Internet of Things Reviewer Board Member for Future Internet and Machine Learning and Knowledge Extraction Conference TPC Member for FNC 2021 and FNC 2020 He has supervised 18+ student theses across blockchain systems , context-aware computing , and mobile resource management , including advising on AutoML applications , decentralized ledgers , and probabilistic databases .

Thomas NeumannView profile

Professor

• Database Systems
• Query Optimization
• Query Processing
• +2 more

Thomas Neumann is a full-time Professor at the Department of Database Systems within the TUM School of Computation, Information and Technology at the Technical University of Munich . Research Focus : Query optimization and processing in database systems Hardware-aware database engine design Scalable RDF/semantic data management Hybrid OLTP/OLAP processing Join optimization algorithms Scientific Recognition : Gottfried Wilhelm Leibniz Prize (2020), Germany's most prestigious research award Academic Contributions : His recent publications focus on high-performance query execution strategies, hybrid transactional/analytical systems using virtual memory snapshots, and scalable graph processing techniques. These works demonstrate consistent advancements in database engine optimization for modern hardware architectures and large-scale semantic data management.

• Blockchain Technology
• Distributed Systems
• Consensus Protocols
• +6 more

Mohammad Sadoghi is a Professor at the University of California, Davis, with former affiliations at Purdue University, IBM T.J. Watson Research Center, and the University of Toronto. His research focuses on distributed systems, blockchain technologies, consensus protocols, and fault-tolerant computing. He has contributed extensively to transaction processing, stream processing architectures, and the integration of edge-cloud systems with blockchain frameworks. Current Affiliation: University of California, Davis Former Affiliations: Purdue University, IBM, University of Toronto Research Interests include consensus algorithms, Byzantine fault tolerance, distributed ledger technologies, and scalable data processing. He has pioneered systems like ResilientDB and ByShard, addressing challenges in global-scale distributed systems and blockchain fabrics. His work bridges theoretical foundations with practical implementations, emphasizing real-world applications in edge computing and hybrid cloud-edge environments. Key publications highlight advancements in consensus protocols, blockchain scalability, and fault-tolerant architectures. Recent trends in his work focus on concurrent consensus mechanisms, DAG-based systems, and secure geo-replication. Contributions span both academic publications and industry-oriented solutions, such as the Bedrock platform for BFT protocol analysis. Grants and advising roles are implied through his extensive research output, though specific grants are not detailed in the provided text. His collaborations include projects on self-curating databases (e.g., L-Store) and systems like SplitJoin for stream processing.

• Database Systems
• Data Management
• Graph Databases
• +5 more

Alin Deutsch is a Professor of Computer Science at the University of California, San Diego (UCSD), specializing in database systems, graph databases, and formal verification. He has contributed significantly to research areas including query optimization, data integration, and privacy-preserving systems. His work spans theoretical foundations and practical implementations, such as the Linked Data Benchmark Council (LDBC) and the TigerGraph database system. He co-authored over 100 papers and has been involved in major conferences like SIGMOD and VLDB. Research interests include graph query processing, parallel computing, data-centric business processes, and automated system verification. Recent work focuses on scalable hybrid analytics and graph databases. Deutsch is also active in database education, co-authoring a paper on UCSD's database curriculum. He has led projects in privacy-aware systems, such as policy-aware location-based services, and contributed to tools like CLIDE for interactive query formulation in service-oriented architectures. His collaborations involve industry partners like TigerGraph and academic institutions globally.

• Databases
• Data Provenance
• XML
• +5 more

Peter Buneman is a prominent academic affiliated with the University of Edinburgh, UK. His research primarily focuses on databases, data provenance, XML, and semistructured data. He has held significant roles in advancing computational models for data citation, provenance tracking, and distributed systems. Key areas of expertise include database systems, graph algorithms, and collaborative data curation platforms. Buneman's work integrates theoretical foundations with practical applications in pharmacology data, digital libraries, and scientific data management. His contributions to data provenance and citation systems have shaped standards in academic and industrial settings. Notable projects include the Database Wiki platform for collaborative data management and the MITra framework for graph traversal. Buneman collaborates extensively with co-authors like Susan Davidson, Wenfei Fan, and Val Tannen. Publications span 1974–2025, emphasizing methodologies for data integration, distributed computing, and computational biology. His work bridges theoretical computer science with real-world applications in biomedicine and information systems.

• Database Systems
• Operating Systems
• Distributed Systems
• +3 more

Athinagoras Skiadopoulos is a computer systems researcher at Stanford University's School of Engineering, Department of Computer Science, focusing on the intersection of database systems and operating systems. His work centers around the innovative DBOS (Database-oriented Operating System) project and large-scale machine learning infrastructure, collaborating with prominent researchers including Christos Kozyrakis and Michael Stonebraker. His primary research interests include: Database-oriented Operating Systems (DBOS) Distributed systems for large-scale machine learning Resource management and optimization in data-intensive systems Transaction processing and data governance High-performance networking for accelerated computing Fault tolerance in distributed training systems Skiadopoulos's research trajectory shows a clear evolution from foundational DBOS architecture toward applications in large-scale machine learning systems. His early publications established the DBOS framework for operating system design using database principles, while his recent work addresses critical challenges in distributed training of massive neural networks. Systems like ReCycle and SlipStream demonstrate innovative approaches to pipeline adaptation and failure recovery during distributed training. His most recent 2025 work on accelerating Mixture-of-Experts training represents the cutting edge of efficient large model training infrastructure. Through his research, Skiadopoulos has established himself in both the database and systems research communities, with publications in premier venues including SOSP, OSDI, VLDB, and CIDR. His work consistently bridges theoretical database concepts with practical systems implementations, demonstrating how database techniques can solve real-world systems challenges in modern computing environments.

• Distributed Systems
• Cloud Computing
• Edge Computing
• +7 more

David Bermbach is a Full Professor at Technische Universität Berlin , leading the Scalable Software Systems group since 2023. His research focuses on distributed systems, serverless computing, and benchmarking, with significant work on edge and fog computing architectures. He is affiliated with the Einstein Center Digital Future and co-chairs interdisciplinary projects like SimRa for bicycle traffic safety. Full Professor, Scalable Software Systems (2023–present) ECDF-Professor, Mobile Cloud Computing (2017–2023) Postdoctoral Researcher (2014–2017) Education : Diploma in Business Engineering (2010) – Karlsruhe Institute of Technology (KIT) PhD in Computer Science (2014, summa cum laude) – KIT Research Interests span distributed systems with emphasis on cloud, edge, and fog computing, serverless architectures, IoT platforms, and benchmarking frameworks. His work addresses consistency-performance trade-offs, resource placement, and interdisciplinary applications in urban mobility and satellite edge computing. Article Trends show a focus on serverless computing (12/15), edge-cloud integration (9/15), and benchmarking methodologies (7/15). Key themes include optimizing function placement, federated learning architectures, and low-earth orbit computing systems. Scientific Awards Best Paper Award – ShutPub (2024) Best Workshop Paper – A Research Perspective on Fog Computing (2017) Best Paper Runner Up – Benchmarking Eventual Consistency (2014) Summa Cum Laude PhD Thesis (2014) Advising & Grants include mentoring students like Tobias Pfandzelter and Trever Schirmer, leading funded projects through the Einstein Center Digital Future, and contributing to 6G network research. His team works on cloud federation, serverless optimization, and real-world IoT applications.

Holger SchwarzView profile

Associate Professor

• Data Management
• Database Systems
• Data Lakes and Lakehouses
• +6 more

Holger Schwarz is an Associate Professor (Apl. Professor) at the Institute for Parallel and Distributed Systems (IPVS) within the Faculty of Computer Science, Electrical Engineering and Information Technology at the University of Stuttgart. He serves as Head of the Infrastructure Department and is actively involved in research and teaching in the areas of data management, database systems, and data analytics. Professor Schwarz earned his doctorate (Dr. rer. nat.) from the University of Stuttgart in 2003 with a dissertation on "Integration of Data Mining and Online Analytical Processing." He later completed his habilitation (Dr. rer. nat. habil.), qualifying him as a university professor in Germany. His primary research interests focus on data management systems , particularly in the domains of data lakes, lakehouses, enterprise data platforms, and metadata management. Professor Schwarz investigates how to design efficient and scalable data architectures that support modern analytical workloads while addressing challenges in data integration, governance, and democratization. His work bridges theoretical database concepts with practical industrial applications, as evidenced by numerous collaborations with industry partners. Professor Schwarz's recent publications demonstrate a clear trend toward enterprise data management solutions, particularly focusing on data lakehouse architectures, enterprise data marketplaces, and advanced clustering techniques. His research shows a consistent pattern of addressing real-world data management challenges through innovative architectural patterns and algorithmic improvements, with strong emphasis on practical industrial implementation. Professor Schwarz supervises numerous research projects including MetaMan (metadata management in complex data landscapes), DLArchitecture (design of comprehensive data lake architecture), INTERACT (interactive rapid analytic concepts), and VALID-Partition (improving prediction quality using domain knowledge). He also coordinates the University of Stuttgart's projects within the Software Campus initiative and serves as Managing Director of the Technology Partnership Lab and as a Member of the Board of Directors of the Industrial Data Lab. His teaching portfolio includes courses on Advanced Information Management, Database Systems, and Data Science projects across multiple semesters, demonstrating his commitment to educating the next generation of data management professionals.

• Database Systems
• Distributed Systems
• Cloud Computing
• +4 more

Dr. Kenneth Salem is a Professor at the University of Waterloo, Canada , with a distinguished career spanning over three decades in database systems, distributed computing, and data management. His work has significantly influenced transaction processing, replication, and scalability in modern databases. Institution: University of Waterloo Collaborations: Frequent co-author with Hector Garcia-Molina, Ashraf Aboulnaga, Umar Farooq Minhas, Khuzaima Daudjee Research Interests: Dr. Salem’s research focuses on database systems, particularly in transaction processing , distributed databases , cloud computing , and energy-efficient data storage . He has pioneered techniques for schema design in NoSQL , adaptive caching , and RDMA-based data transfer . His work often addresses challenges in high availability , workload-aware optimization , and cardinality estimation . Recent Article Trends: His latest publications (2023-2025) explore ad hoc transactions , eventual durability , and summary-based cardinality estimation , emphasizing practical solutions for real-world database scalability and consistency. Earlier works (2018-2022) covered memory power optimization , RDMA abstractions , and workload-aware CPU scaling , reflecting a sustained focus on performance and efficiency. Advising and Collaborations: Dr. Salem has mentored numerous co-authors in database research, including Ashraf Aboulnaga, Umar Farooq Minhas, and Khuzaima Daudjee. His collaborative projects span Apache Spark caching , RemusDB high availability , and DimmStore memory optimization . Labs and Teams: He has been a key contributor to the DaMoN and Versatile Database Systems workshops, focusing on hardware-aware database design. His work with teams at Waterloo and collaborations with institutions like ETH Zurich and MIT has advanced self-managing databases and edge replication technologies.

Norbert RitterView profile

Professor

• Databases and Information Systems
• New Database Technology (NoSQL)
• Scalable Cloud Data Management
• +9 more

Prof. Norbert Ritter is the Dean of the Faculty of Mathematics, Computer Science and Natural Sciences (MIN) at the University of Hamburg since August 2022. He holds a full professorship in the Department of Informatics, leading the Databases and Information Systems group. Previously, he served as an associate professor (2002–2005) and assistant professor (1998–2002) at the Technical University of Kaiserslautern and the University of Hamburg. His research focuses on advanced database technologies, including NoSQL systems, scalable cloud data management, big data analytics, and information integration. Key areas include service-oriented computing, federated database systems, and transaction management. He has authored over 149 publications, with recent work emphasizing polyglot data stores, spatio-temporal data processing, and web performance optimization. Education: M.Sc. (1991), Ph.D. (1997) in Computer Science from the University of Kaiserslautern Professional Activities: Dean of MIN Faculty (since 2022), former head of DBIS group Labs/Teams: Leads the Databases and Information Systems research group His advising record includes over 274 student theses, spanning PhD and master's projects in database design, data integration, and web performance engineering. Collaborative projects include Beaconnect (continuous web A/B testing) and Compaz (shared dictionary compression).

Peter DruschelView profile

Professor

• Distributed Systems
• Operating Systems
• Peer-to-Peer Systems
• +7 more

Peter Druschel is the founding director of the Max Planck Institute for Software Systems (MPI-SWS) and leads the Distributed Systems Group. He holds adjunct professorships at Saarland University and the University of Maryland, reflecting his strong academic affiliations in computer science. He has previously served as a Professor of Computer Science at Rice University and has held visiting positions at MIT, Microsoft Research Cambridge, and LIP6. Education: Ph.D. in Computer Science, University of Arizona, 1994 His research centers on building secure, compliant, and privacy-preserving distributed and mobile systems. Key interests include accountable systems, peer-to-peer networks, operating systems, and network security. He has led foundational work in systems like Pastry, Scribe, and Glacier, and currently focuses on privacy compliance in data processing through projects like Thoth and iPic. His work is supported by major grants from the ERC, Max Planck Society, DFG, BMBF, and Google. The recent publications highlight a consistent trend in secure and privacy-aware systems, with a focus on policy enforcement, isolation mechanisms, anonymity, and mobile security. These works span top venues such as USENIX Security, OSDI, MobiSys, and SIGCOMM, reflecting sustained impact in systems and security communities. Scientific Awards: NSF CAREER Award (1995) Alfred P. Sloan Fellowship (2000) SIGOPS Mark Weiser Award (2008) Microsoft Research Outstanding Collaborator Award (2016) EuroSys Lifetime Achievement Award (2017) Druschel has advised numerous PhD and master’s students and postdoctoral researchers at MPI-SWS. He has co-directed major collaborative programs including the Cornell-Maryland-Max Planck Pre-doctoral School and the Maryland Max Planck Ph.D. Program. His leadership extends to professional service, having chaired SOSP, OSDI, NSDI, and EuroSys, and served on editorial boards of CACM, TOCS, and Royal Society Open Science. He is a member of Academia Europaea and the German Academy of Sciences Leopoldina. Labs and Teams: Distributed Systems Group, MPI-SWS imPACT ERC Synergy Project Collaborators include Bobby Bhattacharjee, Deepak Garg, Miguel Castro, Ion Stoica, and others

Ruben TaelmanView profile

Researcher

• Decentralization
• Linked Data Publishing
• Web Querying
• +3 more

Ruben Taelman is a postdoctoral researcher at IDLab , Ghent University – imec, specializing in decentralization, Linked Data publishing, and querying. He develops open-source JavaScript libraries like the Comunica engine for decentralized data access and focuses on intelligent infrastructure for data publication and retrieval. His research bridges academic and industrial perspectives, addressing challenges in decentralized knowledge graphs, policy negotiation, and data governance. Key projects include Triple Storage for versioned RDF querying and contributions to the Solid ecosystem for user-centric data control.

• Animal Migration
• Behavioral Ecology
• Collective Decision-Making
• +3 more

Dr. Andrea Flack is an Independent Emmy Noether Group Leader at the Max Planck Institute of Animal Behavior, Konstanz, Germany, and a Junior Group Leader at the Centre for the Advanced Study of Collective Behaviour, University of Konstanz. Her research focuses on understanding how ecological, environmental, and genetic factors shape migratory behaviors in birds, particularly white storks, and their evolutionary consequences. Current Positions: Independent Emmy Noether Group Leader, Max Planck Institute of Animal Behavior (2022–present) Junior Group Leader, Centre for the Advanced Study of Collective Behaviour (2020–present) Education: DPhil in Zoology (2009), University of Oxford Diploma in Biology (2009), Freie Universität Berlin Her work integrates cutting-edge technologies such as high-resolution GPS, accelerometers, and on-board cameras with experimental approaches like delayed-releases and cross-fostering to explore behavioral variation and its implications. Recent research highlights include social learning in migration and the impact of anthropogenic habitats on stork movement patterns. Key trends across her publications emphasize collective decision-making, environmental adaptation, and technological innovations in tracking. Notable contributions appear in journals like PNAS , Current Biology , and Journal of Applied Ecology . Scientific Awards: Emmy Noether Fellowship Dr. Flack collaborates extensively, utilizing Movebank for data integration and leading studies on avian collision risks and migration phenology. Her lab team includes researchers like William Fiedler and Emily Aikens , focusing on experimental designs and ecological modeling.