Prof. Dr. Thomas Brinkhoff is Chair of the Institute Board and Chair of Geoinformatics at Oldenburg University of Applied Sciences. He leads the Institute for Applied Photogrammetry and Geoinformatics (IAPG) and contributes to institutions like the Association for the Promotion of Geoinformatics in Northern Germany (GiN e.V.) and the Oldenburg Research and Development Institute for Computer Science (OFFIS e.V.). Education: Diploma in Computer Science (Informatik), Universität Bremen (1990) Doctorate in Computer Science (Dr. rer. nat.), Ludwig Maximilian University of Munich (1994) Brinkhoff's research spans geodatabase systems, spatiotemporal data processing, geosensor analytics, and location-based services. His work addresses Volunteered Geographic Information (VGI), web-based geospatial visualization, and mobile data integration, with applications in traffic management and forensic science. Recent projects include ProSaDi (Digital Provenance and Collection Research) and contributions to the Laboratory for optical 3D metrology . He has served on program committees for ACM SIGSPATIAL (2002-2019), AGILE conferences (2010-2025), and editorial boards of journals like GeoInformatica and TGIS. Notable Lectures: 2024: Forensic applications of tachograph data 2023: Geoinformatics in homicide investigations 2022: Spatiotemporal analysis for sustainability projects 2015: Open geodata standards at FOSSGIS 2014: Mobile sensor data processing
Prof. Dr. Dennis Säring is a faculty member at the University of Applied Sciences Wedel , specifically affiliated with the School of Engineering. His academic and research activities focus on Deep Learning , Medical Image Analysis , and applications of Artificial Intelligence in healthcare and biomedical imaging. He has led seminars on Deep Learning topics and supervised student projects in Autonomous Driving at Audi's AADC 2018 competition. Research Highlights : Cardiovascular imaging, forensic age estimation via MRI, neural network-based bone segmentation, and cerebrovascular aneurysm analysis. Technical Expertise : Cardiac MRI, 3D/4D image processing, parametric mapping, and spatiotemporal data fusion. His recent publications (2018-2023) emphasize 3D MR segmentation for age assessment, CMR strain analysis in athletes, and T1/T2 mapping for myocarditis. Key collaborations include institutions like the University Medical Center Hamburg-Eppendorf and Wedler Hochschulbund, with funding for autonomous vehicle research. While no explicit scientific awards are listed, his work spans clinical cardiology, forensic radiology, and AI-driven medical diagnostics.
Madelon Hulsebos is a Researcher at CWI in Amsterdam, where she leads the Table Representation Learning (TRL) Lab and contributes to the Database Architectures group. She is also a faculty member of the European Laboratory for Learning and Intelligent Systems (ELLIS) Amsterdam unit. Her career bridges academia and industry, including a postdoctoral fellowship at UC Berkeley and prior industry experience in automating data analysis pipelines with ML. Education : PhD in Computer Science (University of Amsterdam, 2023), with research at Sigma Computing and MIT; Postdoctoral Fellow (UC Berkeley, 2024). Her research focuses on establishing tabular data as a key AI modality through Table Representation Learning , generative models for relational data, and robust systems for data analysis. Key interests include: Relational Table Embeddings LLMs for QA/text2SQL and data wrangling Retrieval over Data Lakes and Databases Agentic Systems for Data Science Democratizing insights from structured data Recent work highlights trends in benchmarking table retrieval (TARGET), semantic column detection (AdaTyper, Sherlock), and large-scale tabular data curation (GitTables, SchemaPile). These projects address challenges in metadata utilization, data lake search, and end-to-end systems for structured data. She has secured significant funding, including the NWO AiNed Fellowship Grant ($1M) for her 5-year DataLibra project. Madelon organizes workshops at NeurIPS , SIGMOD , and ACL , and reviews for top venues like VLDB and NeurIPS. Scientific Awards : NWO AiNed Fellowship Grant ($1M) She actively mentors students and collaborates on European AI initiatives, including monthly TRL seminars and workshops. Her lab's tools (GitTables, TARGET) are widely adopted for training foundation models on tabular data.
Katia Bianchini is a Research Fellow at the Max Planck Institute for Social Anthropology in Halle, Germany, with a focus on the intersection of law and anthropology in refugee and immigration contexts. She holds a PhD in Law (University of York), an LLM in Comparative Laws (University of San Diego), and a Law degree (Università di Pavia). Her work bridges empirical legal analysis with anthropological methodologies to address issues such as statelessness, asylum adjudication, and the rule of law in migration policies. Education PhD in Law, University of York (2011–2016) LLM in Comparative Laws, University of San Diego (1999–2000) Law degree, Università di Pavia (1992–1998) Bianchini’s research interests include refugee law , immigration law , statelessness , EU law , and human rights law . Her current project examines legislation and responses to missing and deceased sea migrants in Italy , analyzing legal frameworks for search, identification, and burial practices, particularly along the Central Mediterranean Route. She emphasizes the importance of legal anthropology to understand gaps between abstract law and its real-world application. The trends in her publications reflect a focus on statelessness determination procedures , asylum law (notably witchcraft-based claims), humanitarian visas , and rule of law challenges in migration contexts. Her work spans journal articles , book chapters , and monographs , often combining legal analysis with empirical data from interviews and fieldwork. Scientific Awards Erasmus scholarship, University of Leuven, Belgium (1997–1998) Grants and Professional Activities include visiting researcher roles at Fordham University and the University of Oxford, as well as editorial work for the Statelessness and Citizenship Review and the CUREDI Database . She has presented extensively on topics like statelessness in the UK , cultural diversity in asylum adjudication , and NGO criminalization in Mediterranean rescue operations .
Jishen Zhao is an Assistant Professor in the Department of Computer Science and Engineering at the University of California, San Diego (Jacobs School of Engineering). His research focuses on computer architecture, non-volatile memory systems, and deep learning acceleration. Dr. Zhao has published extensively in top venues including ISCA, MICRO, ASPLOS, and IEEE Transactions. He collaborates with researchers at UCSD and beyond to advance systems for emerging applications in AI and autonomous vehicles. Dr. Zhao's primary research areas include persistent memory systems, hardware/software co-design for deep learning, and safety-critical computing. He develops techniques for crash consistency, memory disaggregation, and efficient neural network deployment. His work on autonomous vehicles addresses scenario generation and perception-aware system design. Recent projects explore LLM applications for software engineering and hardware verification. Analysis of Dr. Zhao's 2024-2025 publications reveals a strong shift toward AI-integrated systems research. He applies large language models to tasks like RTL verification and software issue localization while continuing to innovate in memory systems for serverless computing. There is growing emphasis on safety-critical systems for autonomous vehicles and energy-efficient neural network training using novel hardware architectures. Information about Dr. Zhao's scientific awards, advising activities, grants, and laboratory facilities was not available in the provided documentation.
Joakim Nivre is a Professor at Uppsala University's Department of Linguistics and Philology. He is a leading researcher in computational linguistics, with a focus on dependency parsing, Universal Dependencies (UD) framework development, and multilingual NLP applications. His recent work explores LLMs in climate change discourse analysis, pharmacovigilance explainability, and historical text processing. Key research areas: Dependency parsing theory, Universal Dependencies standardization, LLM evaluation Collaborations: SweSAT-1.0 benchmark development, ClimateEval project, PARSEME integration His 2025-2023 publications demonstrate expertise in explainable AI for healthcare, synthetic data generation for idioms, and multilingual benchmark design. Notably, he co-developed SweSAT-1.0 to evaluate Swedish LLMs and contributed to typology-informed UD revisions. Despite extensive work in NLP, no scientific awards are mentioned in available texts.
Karl Ulrich Schreiber is an Adjunct Professor at the Department of Physics and Astronomy, University of Canterbury, New Zealand, and an apl. Professor at the Institute for Astronomical and Physical Geodesy at the Technical University of Munich (TUM). He is a scientist at the Geodetic Observatory Wettzell, jointly operated by TUM and the Bundesamt für Kartographie und Geodäsie (BKG). His work bridges fundamental physics and geodetic applications, with leadership roles in major international projects including ESA’s MAGIC/Science, QSG4EMT, and Baltic+ Theme 5, as well as DFG Research Units NEROGRAV and UPLIFT. His research focuses on Space Geodesy , Satellite and Lunar Laser Ranging , and Ring Laser Technology . He has pioneered the use of large ring laser gyroscopes for measuring Earth's rotation, polar motion, and seismic rotations. His work enables high-precision monitoring of geophysical phenomena such as Earth tides, Chandler wobble, and rotational ground motions from earthquakes. He is a key contributor to multi-technique co-location studies (VLBI, SLR, GNSS) and time transfer experiments, advancing the Global Geodetic Observing System (GGOS). His recent publications show a strong trend in developing and applying large-scale ring laser arrays (e.g., ROMY) for geophysical sensing, photon-counting laser ranging for space debris and satellite tracking, and optical timing systems for synchronization across geodetic networks. These efforts span disciplines including geodesy, seismology, quantum optics, and fundamental physics. Scientific contributions include: Development of the Wettzell Large Ring Laser (G-ring) for continuous Earth rotation monitoring. First direct measurements of Earth's diurnal polar motion and Chandler wobble using ring lasers. Pioneering work in rotational seismology, validating ring laser data against seismic arrays. Contributions to lunar laser ranging and its role in reference frame realization. Leadership in ESA and DFG projects advancing space geodesy and inertial sensing. He advises doctoral and master’s students within the DFG Research Training Group UPLIFT and collaborates with international institutions on instrumentation and data analysis. His lab at Wettzell hosts advanced laser ranging and ring laser systems, serving as a fundamental geodetic observatory. Future work includes enhancing clock ties for global geodesy, expanding multi-component rotation sensing, and advancing space-based geodetic technologies.
Victor Vianu is a Professor in the Department of Computer Science and Engineering at the University of California, San Diego, within the Jacobs School of Engineering. His work focuses on the intersection of database theory and verification techniques, particularly in the context of data-driven business processes and workflows. Research Interests Professor Vianu's primary research interests span database theory, verification of database-driven systems, and computational logic. His current work focuses on automatic verification of interactive data-driven web services and business processes, exploring how to provide customized workflow views for different stakeholders in organizational settings. His research addresses significant technical challenges at the intersection of data management and process modeling, requiring novel approaches that go beyond traditional relational algebra to handle both data and process aspects simultaneously. His work on data-driven business processes investigates how to specify, analyze, and synthesize views of workflows that expose only information relevant to specific user roles. This research has important applications in e-commerce, digital government, healthcare, and scientific infrastructure, where different stakeholders require varying levels of workflow abstraction and detail. Research Contributions and Trends Professor Vianu's recent publications demonstrate a consistent focus on the integration of data management and workflow processes. His work has evolved from foundational database theory to increasingly practical applications in business process management. A key trend in his research is the development of formal frameworks for workflow views that maintain consistency while providing appropriate abstractions for different user roles. His publications reveal a progression from theoretical foundations to more applied aspects of workflow verification and integration, often in collaboration with researchers from INRIA and other institutions. Advising and Research Support Professor Vianu leads the UCSD Database Laboratory, which conducts research on database systems and theory. He currently advises graduate student Marysia Tran and has likely mentored numerous other students throughout his career. His research is supported by the National Science Foundation under grant "Views of Data-Driven Business Processes: Foundations and Applications" (NSF Project III 1815247). This project brings together techniques from logic, automata theory, complexity theory, algorithms, and automatic verification to address challenges in workflow management. Research Environment Professor Vianu is an active member of the UCSD Database Laboratory, which maintains a regular research seminar series. He has collaborated extensively with researchers including Alin Deutsch (UC San Diego), Serge Abiteboul (INRIA and ENS-Paris), Pierre Bourhis (Univ. of Lille and CNRS), and Adrien Koutsos (ENS Cachan). His foundational work includes co-authoring the influential textbook "Foundations of Databases" with S. Abiteboul and R. Hull, which remains a standard reference in database theory.
Muhammad Ali Gulzar is an Assistant Professor in the Computer Science Department at Virginia Tech and an Amazon Scholar at Amazon Web Services. His research focuses on improving developer productivity through automated debugging and testing for applications in emerging domains, including data-intensive software such as dataflow programs, ML/AI applications, and computational notebooks. Education Ph.D. in Computer Science from University of California, Los Angeles (Google Ph.D. Fellow 2017-2020) Research Interests Gulzar's research spans three primary areas: (1) automated tracking-code localization techniques in web applications, (2) re-engineering testing and debugging for data-intensive applications, and (3) advancing current testing and debugging practices in Federated Learning Applications. His work addresses the challenges of debugging in complex systems where traditional approaches fail due to the scale and distributed nature of modern applications. His research has significant implications for improving software quality, developer productivity, and accessibility in web applications. Research Trends Recent publications demonstrate a strong focus on debugging and testing challenges in emerging application domains. His work bridges traditional software engineering with machine learning, data-intensive systems, and web technologies. Notably, he has made significant contributions to Federated Learning debugging (FedDebug), accessibility challenges in ad-driven web applications, and semantic caching for Large Language Models. His approach often combines novel algorithmic insights with practical implementations that address real-world challenges in software development and maintenance. Scientific Awards Google Ph.D. Fellow (2017-2020) $1.1 million NSF award for Federated Learning research ACM CCS 2024 Distinguished Artifact Award Advising and Grants Gulzar leads a productive research group with multiple students contributing to publications in top-tier venues. His NSF-funded research on Federated Learning demonstrates his ability to secure competitive funding for innovative projects. His advising style appears to emphasize practical impact alongside theoretical contributions, with students often taking lead roles in publications. Current research directions include debugging techniques for Large Language Models, accessibility challenges in modern web applications, and novel testing approaches for distributed data processing systems.
Lucio Baccaro is Director at the Max Planck Institute for the Study of Societies (MPIfG) and was Full Professor of Macrosociology at the University of Geneva, where he also served as Deputy Dean for Research (2016–2020). He has held academic positions at MIT, Case Western Reserve University, and visiting roles at the University of Turin and the University of Vienna. His primary affiliations are with MPIfG and the University of Geneva, both central to his research in political economy and sociology. Education: PhD in Management and Political Science, Massachusetts Institute of Technology (MIT), 1999 Doctorate in Labor Law and Industrial Relations, University of Pavia, 1997 Master of Business Administration, Stoa' (IRI-MIT joint venture), 1991 Laurea in Philosophy, summa cum laude, University "La Sapienza", Rome, 1989 Lucio Baccaro’s research focuses on comparative political economy, labor relations, global worker rights, and deliberative governance . His work integrates economic sociology and political sociology to analyze institutional change, social dialogue, and the impact of globalization on labor and welfare systems. He has led major comparative studies on employment models, pension reforms, and international labor standards. His scholarship emphasizes the interplay between institutions, ideas, and power in shaping economic governance. His recent publications reveal a consistent focus on institutional change, deliberative processes, labor market reforms, and global justice . Themes include path dependence in international organizations, the transformation of collective bargaining, and the role of expertise in democratic governance. His interdisciplinary approach bridges sociology, political science, and economics, with strong methodological rigor in comparative and qualitative analysis. Scientific Awards and Honors: Honorary Professor, University of Duisburg-Essen (2023) Professeur honoraire, University of Geneva (2020) International Geneva Award (2011) Outstanding Young Scholar Award, IRRA (2003) Founder's Prize, SASE (2001) Maurice F. Strong Career Development Chair, MIT (2006–2009) Multiple fellowships from SSRC, Harvard, MIT, and CUNY Alfiere del Lavoro, awarded by the President of Italy (1984) Advising and Grants: While specific student advisees are not listed, Baccaro has supervised research and mentored scholars through his roles at MPIfG and the University of Geneva. He has secured substantial research funding, including grants from the Swiss National Science Foundation (SNF) and the Swiss Network for International Studies (SNIS), supporting projects on post-Fordist growth models, employment policy, and deliberative governance. His leadership in co-principal investigator roles highlights his collaborative research approach and institutional influence. Labs and Research Teams: As Director at MPIfG, Baccaro leads a major research institute focused on the study of societal and economic institutions. He has been instrumental in shaping research agendas on political economy and governance, fostering interdisciplinary collaboration and international scholarly exchange.
Dr. Lothar Lemnitzer serves as a Researcher at the Berlin-Brandenburg Academy of Sciences and Humanities, affiliated with the Center for Digital Lexicography of the German Language in Berlin. His office is located at Jägerstrasse 22/23, Space 18, with contact details including phone +49 (0)30 20370 538 and email lemnitzer@bbaw.de. His research spans critical areas in linguistic technology: Lexicography Digital Humanities German Language Processing Computational Linguistics Natural Language Processing Language Technology Dr. Lemnitzer's work focuses on developing digital infrastructure for German language resources, contributing to modern lexicographic methodologies through computational approaches. His publications reflect ongoing advancements in creating structured lexical databases for academic and public use. No scientific awards are documented in the available profile information. While the text references publications and a curriculum vitae, specific details regarding student supervision, grant funding, or collaborative projects remain unlisted. The Center for Digital Lexicography operates as a dedicated unit within the academy, driving innovation in digital dictionary creation and language resource management for the German-speaking academic community.
Chang Xu is a Professor and Ph.D. supervisor at Nanjing University, affiliated with the State Key Laboratory for Novel Software Technology, School of Computer Science, and Institute of Computer Software (ICS). He has been a full-time faculty member since 2010, when he joined as an associate professor and was later promoted to full professor in 2015. Education: Ph.D. from The Hong Kong University of Science and Technology (HKUST) in 2008 (advisor: Prof. S.C. Cheung) M.Eng. from Institute of Software, Chinese Academy of Sciences (ISCAS) in 2003 B.Eng. from University of Science and Technology of China (USTC) in 2000 Research Interests: Professor Xu's research focuses on big data software engineering, intelligent software testing and analysis, and adaptive and autonomous software systems. His recent work centers on constructing and providing runtime support for intelligent software in open environments, with emphasis on inconsistency detection and resolution for environments, and quality assurance for adaptive, concurrent, learning-based, smartphone-based, and spreadsheet-based applications. His work bridges theoretical foundations with practical applications in software engineering, particularly in program analysis, software testing, and self-adaptive systems. Scientific Awards: ACM SIGSOFT Distinguished Paper Award from ICSE 2025 Best Student Paper Award from EUROSYS 2025 ACM Distinguished Member in 2024 Best Paper Award from SOSP 2023 Best Paper Candidate from ISSRE 2022 Yangtze River Scholar by the Ministry of Education in 2021 Multiple ACM SIGSOFT Distinguished Paper Awards from conferences including ASE, ICSE National Science and Technology Progress Award (Second Class) in 2011 Academic Service and Advising: Professor Xu has served on numerous program committees for top software engineering conferences including ICSE, ASE, ESEC/FSE, and ISSTA. He is an editorial board member for several journals including Journal of Computer Science and Technology and Frontiers of Computer Science. He has supervised numerous Ph.D. and MSc students, with research topics spanning program analysis, software testing, self-adaptive systems, and more. His students have gone on to successful careers in both academia and industry. Research Groups: Professor Xu is associated with the SPAR research group at Nanjing University and the CASTLE research group at HKUST, focusing on software analysis, reliability, and testing.
Amine Mhedhbi is an Assistant Professor at Polytechnique Montréal , where he leads the Data & AI Systems Lab . He earned his PhD in 2023 from the University of Waterloo. His work bridges data management , graph databases , and AI systems , with a focus on performance, debuggability, and user interface design for data applications. Education : PhD (University of Waterloo, 2023) Research Interests center on modern analytical data systems , including multimodal data management , language model integration , and graph query optimization . His projects like FLockMTL and GraphflowDB aim to combine semantic analysis, AI, and traditional database operations. Scientific Awards include the NSERC Discovery Grant , the Cheriton School Distinguished Dissertation Award , the VLDB Best Paper Award , and fellowships from Microsoft and Meta . Key Collaborations : Semih Salihoğlu, Jimmy Lin, Elena L. Glassman Labs & Teams : Affiliated with DAIS Lab , IVADO , and co-founded the applied research team at Distyl AI in 2023.
Martin Grohe is a Professor at the School of Logic and Theory of Discrete Systems , part of the Department of Computer Science at RWTH Aachen University . His research spans Algorithms and Complexity , Logic , Database Theory , Graph Theory , and Machine Learning , with a focus on integrating logical frameworks into computational models. His recent work explores graph neural networks , Weisfeiler-Leman algorithms , and parameterized complexity , as seen in publications on isomorphism testing , database repairing , and probabilistic query evaluation . While no specific scientific awards are mentioned, his contributions to graph theory and machine learning are widely recognized through numerous peer-reviewed publications.
Prof. Dr.-Ing. Jürgen Teich is a full Professor and Chair for Hardware-Software Co-Design at the Department of Computer Science, Friedrich Alexander University Erlangen-Nuremberg (FAU). He serves as Head of Department Computer Science and Vice Dean of the Technical Faculty since August 2024, and has been Speaker of the FAU Research Center Embedded System Initiative (FAU ESI) since 2023. His educational background includes: Diploma degree in Electrical Engineering, University of Kaiserslautern (1989) Dr.-Ing. degree in Electrical Engineering, University of Saarland (1993) Habilitation (PD Dr.-Ing.) entitled "Synthesis and Optimization of Digital Hardware/Software Systems" (1996) Prof. Teich's research focuses on Embedded Systems , Invasive Computing , Hardware-Software Co-Design , and Reconfigurable Computing . His work spans from theoretical foundations to practical implementations, with particular emphasis on resource-constrained systems, many-core architectures, and energy-efficient computing. He has pioneered research in invasive computing paradigms that enable more efficient use of many-core processors by allowing applications to dynamically claim resources. His recent publications reveal a strong trend toward energy-efficient AI deployment on embedded devices , security of embedded systems , and novel memory technologies . There's a clear focus on practical implementations of machine learning on microcontrollers (TinyML), hardware acceleration for data processing, and innovative approaches to power management in self-powered systems. Among his notable scientific awards are: IEEE Fellow (since 2018) Member of Academia Europaea, Section Informatics (since 2011) Member of the National Academy of Science and Engineering (acatech) (since 2018) Member of the German Society of Humboldtians (since 2021) Prof. Teich has been Principal Investigator for numerous DFG-funded projects including SFB/Transregio 89 "Invasive Computing" (2010-2022), SFB 694, and multiple priority programs. He has coordinated large collaborative research efforts across Germany and internationally, with significant funding from DFG and other sources. His research group has produced influential work in embedded systems design and co-design methodologies. He leads the Hardware-Software Co-Design research group at FAU, which focuses on innovative approaches to embedded system design, invasive computing architectures, and efficient implementation of machine learning on resource-constrained devices. The group maintains strong collaborations with industry partners including Intel, Xilinx, and automotive companies.
