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Philippe RigauxView profile

Professor

• Music Information Retrieval
• Database Systems
• Spatial Databases
• +6 more

Philippe Rigaux is a Professor at the Conservatoire national des arts et métiers (CNAM) in Paris, France, where he conducts research at the CÉDRIC laboratory (Centre d'études et de recherche en informatique et communications). His academic career spans over 25 years with continuous publication output from 1995 through 2024, demonstrating sustained research activity in computer science with a specialized focus on music information retrieval and database systems. Rigaux's research interests center on the intersection of music and computer science, particularly in music score processing, representation, and querying. His work explores graph-based approaches to music representation, topological querying of music scores, and quality assessment in digital music libraries. He has made significant contributions to the development of tools and frameworks for music information retrieval, including the GioQoso quality assessment tool and the FACETS exploration system for large symbolic music collections. His research often bridges theoretical database concepts with practical music applications, focusing on scalable solutions for music content search and pattern matching. Analysis of his recent publications (2018-2024) reveals a consistent research trajectory focused on improving music information systems through innovative database techniques, graph theory applications, and quality assessment methodologies. His work shows increasing emphasis on multimodal music sources, collaborative music digitization, and advanced representation techniques for rhythm and structure. Rigaux frequently collaborates with researchers across Europe, particularly on projects related to digital music libraries and music information systems. Rigaux has contributed to major projects including NEUMA (a collaborative digital score library), CollabScore (integrating optical recognition with multimodal music sources), and GioQoso (a quality assessment tool for music notation). His research has been published in prestigious venues including Data and Knowledge Engineering, International Journal on Digital Libraries, and proceedings of the International Society for Music Information Retrieval (ISMIR).

Ansgar ScherpView profile

Professor

• Data Science
• Big Data Analytics
• Text Analytics
• +7 more

Professor Ansgar Scherp is a leading academic in Data Science and Big Data Analytics at Ulm University , Germany. His career spans multiple institutions including University of Essex, University of Stirling, and Kiel University, where he led the EU Horizon 2020 MOVING project. He holds a habilitation thesis on Semantic Media Management and has pioneered research in combining symbolic and statistical methods for data analysis. Current: Professor for Data Science & Big Data Analytics (Ulm University) Previous: Professor for Knowledge Discovery (Kiel University), Juniorprofessor roles (Mannheim, Koblenz-Landau) Skills: Semantic Web, Graph Mining, Text Analytics, Multimedia Systems His research interests focus on integrating Information Retrieval, Data Mining, Machine Learning, and Semantic Web technologies. He has developed innovative methods like HCF-IDF for semantic profiling and SchemEX for schema-level indexing of Linked Data. His work addresses challenges in media companies' digital transformation and large-scale Knowledge Graph analysis. Scientific awards include: Best Paper Award, Symposium on Document Engineering (2021) Best Student Paper Award, Symposium on Document Engineering (2019) ACM SIGMM Rising Stars Symposium Speaker (2016) Double Winner of Billion Triple Challenge (2008, 2011) klickTel Award (2013) He has supervised 12 PhD theses and over 15 Master's theses , with students now working at Google, Capgemini, and academic institutions. His email addresses are ansgar.scherp@uni-ulm.de and mail@ansgarscherp.net .

Matthias SpringsteinView profile

Researcher

• Computer Vision
• Deep Learning
• Multimedia Information Retrieval
• +5 more

Matthias Springstein is a researcher at the Technical Information Library (TIB), which is affiliated with Leibniz University Hannover. He is part of the Visual Analytics research group within TIB's Research & Development department, focusing on advanced computer vision and multimedia information retrieval techniques. His research interests span multiple areas of artificial intelligence with emphasis on computer vision applications. Springstein specializes in web-supervised learning for visual concepts, incremental learning approaches, and methods to minimize manual labeling efforts for training data. His work bridges theoretical machine learning with practical applications in digital humanities, particularly in art-historical image analysis and film/video studies. His publication record shows a consistent focus on multimodal analysis, with recent work exploring knowledge graphs for image classification, large-scale hierarchical classification of art-historical images, and computational tools for film analysis. The research demonstrates progression from foundational work in image-text relations and depth estimation toward increasingly sophisticated applications in cultural heritage and scholarly media analysis. Notable achievements include receiving the Best Paper Award at the International Conference on Multimedia Retrieval (ICMR) in 2019 for his work on semantic image-text relations. Springstein has developed TIB AV-Analytics, a computational platform for scholarly video analysis that has been presented at multiple major conferences (SIGIR 2023, SCSMI 2024), indicating significant impact in both the information retrieval and film studies communities.

Christiane RichterView profile

Researcher

• Remote Sensing
• Photogrammetry
• Geoinformatics
• +4 more

Christiane Richter is a Laboratory Engineer at the Faculty of Spatial Information, HTW Dresden, specializing in remote sensing, photogrammetry, and cultural heritage conservation. She leads the NascaGIS project, digitizing the UNESCO World Heritage Nasca Lines. Her work integrates GIS, astronomical analysis, and archaeological research to preserve ancient Peruvian geoglyphs. She co-authored over 50 publications and presented at international conferences like CIPA and ISPRS. Richter also serves as President of the 'Dr. Maria Reiche' association, promoting Nasca's cultural heritage. Her recent projects include documenting ancient aqueducts in Peru using UAVs and GPS. She holds an M.Sc. in Geoinformatics and has collaborated with institutions like TU Prague and UNESCO. Affiliations: HTW Dresden, TU Prague, UNESCO projects Education: M.Sc. Geoinformatics (University of Salzburg), Diploma in Surveying (HTW Dresden) Key Projects: NascaGIS, Nasca Aqueducts Survey, DAI Erbil Project Research Interests: Combining geospatial technologies with archaeology to solve mysteries of ancient landscapes. Recent focus on 3D modeling of geoglyphs and analyzing Nasca's irrigation systems.

Annika WilmersView profile

Professor

• Societal Transformation Processes
• Social and Protest Movements
• Research Synthesis Methodologies
• +3 more

Prof. Dr. Annika Wilmers is a Professor for Societal Responsibility at Frankfurt University of Applied Sciences, jointly affiliated with the Department of Social Work and Health and the School of Personal Development and Education (ScoPE). She concurrently serves as a Researcher at the DIPF | Leibniz Institute for Research and Information in Education. Her academic trajectory includes a doctorate in Modern and Contemporary History from the University of Tübingen, recognized with the Prix Emile et Aline Mayrisch, and roles such as Coordinator of the BMBF meta-project "Digitalisation in Education." Her research explores societal transformation processes, social movements, and evidence-based education policy. Key domains include: Methodologies for research syntheses in educational technology International comparative studies on teacher preparedness and digital equity Youth activism in climate education and democratic participation Her publications (2021–2025) emphasize digital pedagogy, teacher support for marginalized groups, and knowledge transfer frameworks. Trends include rigorous meta-analyses of digital inclusion, cross-sectoral competency development, and policy-practice alignment in European education. Awards: Prix Emile et Aline Mayrisch – Mention Spéciale (Doctoral Thesis Award) She coordinates multidisciplinary projects like Digi-EBF, focusing on Open Science and stakeholder engagement. No student advisories are listed, but she mentors through EU/OECD networks and editorial roles for journals including the Nordic Journal for Systematic Reviews in Education .

• Formal Languages
• Compiler Design
• Automata Theory
• +3 more

Michael A. Harrison is a Professor affiliated with the Graduate School of Business at Stanford University. His research focuses on formal languages, compiler design, automata theory, and operating systems security. He has contributed extensively to foundational areas of computer science, including parsing algorithms, context-free grammars, and software engineering methodologies. His work often intersects with theoretical computer science and practical applications in document processing and user interface systems. Notable publications include works on hypermedia systems, static program analysis, and historical tributes to key figures in computer science. Education and career highlights include a prolific publication record spanning over five decades, collaborations with prominent researchers like Seymour Ginsburg and Jim Gray, and editorial roles in major conferences such as POPL and STOC. His work on protection mechanisms in operating systems and compiler optimization has had lasting impacts on both theoretical and applied computing domains. Research interests emphasize bridging theory and practice, particularly in areas like document systems, security protocols, and algorithmic efficiency. His contributions to the SIGMOD and IEEE Transactions series highlight expertise in database systems and multimedia frameworks.

• Social Media Analysis
• Online Political Polarization
• Misinformation Detection
• +7 more

Ashwin Rao is a Research Professor at the University of Southern California's Information Sciences Institute (ISI) within the Viterbi School of Engineering. With a research career spanning over two decades, his work bridges computer science, social sciences, and political science, focusing on understanding human behavior through digital footprints. His academic journey began with signal processing research in the 1990s before evolving into network protocols and mobile computing, and most recently into computational social science and AI ethics. Rao's research interests encompass Social Media Analysis, Online Political Polarization, Misinformation Detection, Network Protocols, Mobile Computing, Privacy in Mobile Applications, Natural Language Processing, and AI Ethics. His work demonstrates a consistent trajectory from technical networking research to the societal implications of technology. His most recent publications reveal a strong focus on understanding political discourse online, particularly examining polarization, emotional responses to events, and the impact of social media algorithms on information ecosystems. His interdisciplinary approach combines computational methods with social science theories to address pressing issues in digital society. Rao has published extensively across top venues including ICWSM, WWW, ACL, IEEE Transactions, and numerous conferences in networking and systems. His work often appears with Kristina Lerman, with whom he collaborates closely at USC ISI. His recent research portfolio shows a sophisticated integration of machine learning techniques with social science questions, particularly examining how language models reflect and potentially amplify societal biases. Rao has made significant contributions to understanding privacy issues in mobile applications, network protocols, and social media dynamics. His research has been influential in both technical communities studying network performance and social science communities examining online behavior. His work on BitTorrent performance, mobile privacy, and social media analysis has been widely cited across disciplines. His laboratory work appears to focus on computational social science methodologies, developing tools and frameworks for analyzing large-scale social media data while addressing ethical considerations in AI and data analysis. Recent projects suggest strong connections with public health research through social media analysis during the pandemic.

• Computer Science
• Databases
• Distributed Systems
• +4 more

Shahram Ghandeharizadeh is a Professor at the University of Southern California , specializing in Computer Science with a focus on databases, distributed systems, and multimedia. His research spans caching middleware, flying light specks for 3D displays, and swarm robotics. Recent work includes CAMP (cache eviction policies), Disaggregated Database Management Systems , and Flight Patterns for Swarms of Drones , reflecting his expertise in data management and swarm-based technologies. He has collaborated extensively with researchers like Hamed Alimohammadzadeh and Hieu Nguyen . His scientific awards include the ACM Software System Award (2008) , recognizing long-term contributions to software systems. Publications since 2021 highlight advancements in cache management, graph databases, and swarm robotics, with a strong emphasis on non-volatile memory and decentralized frameworks.

Guido MenschingView profile

Professor

• Generative Grammar
• Minimalist Syntax
• Romance Linguistics
• +5 more

Prof. Dr. Guido Mensching holds a Professorship for Romance Linguistics at the University of Göttingen's Department of Romance Philology, specializing in generative grammar and medieval textual studies. His research spans minimalist syntax of Romance languages, medieval medical-botanical texts in Romance languages (particularly in Hebrew script), and comprehensive Sardinian linguistics including historical documentation and multimedia representation. Research interests focus on generative grammar frameworks applied to Romance syntactic structures, with significant contributions to medieval glossary studies examining Hebrew-script manuscripts containing Ibero-Romance, Arabic, and Latin elements. His Sardinian research encompasses historical linguistics, morphosyntactic analysis, and digital documentation initiatives. Current methodological approaches integrate minimalist program theory with digital humanities tools for textual analysis. Research output demonstrates consistent focus on three interconnected domains: (1) syntactic analysis of Romance languages through minimalist frameworks; (2) philological examination of medieval multilingual medical-botanical texts; (3) comprehensive documentation of Sardinian language structures. Publication trends show increasing integration of computational methods for lexical database development, particularly in the DiTMAO (Dictionnaire des Termes Médico-botaniques de l'Ancien Occitan) project. Research funding has been consistently secured through the German Research Foundation (DFG), supporting multiple long-term collaborative projects examining Hebrew-script medical manuscripts across European collections. These projects demonstrate sustained interdisciplinary collaboration between Romance linguistics, Judaic studies, and computational philology. Professional activities include editorial responsibilities for linguistic journals and organization of international research colloquia. Current work continues the critical edition of medieval medical texts while expanding digital infrastructure for Romance linguistic research.

• Internet Security
• Public Key Infrastructure
• DNSSEC
• +5 more

Taejoong (Tijay) Chung is an Associate Professor at the Computer Science Department, Virginia Tech, and Adjunct Professor at POSTECH. He previously served as Assistant Professor at RIT (2018-2020) and Postdoctoral Researcher at Northeastern University (2015-2018). Ph.D. in Computer Science and Engineering, Seoul National University (2015) His research focuses on Internet security protocols for DNS, TLS, Routing, and Email, with emphasis on Public Key Infrastructure (PKI), DNSSEC, RPKI, and Email Security. He develops scalable measurement frameworks (e.g., RoVista) and security enhancements (e.g., RevDNS, AccuRevoke) for global internet infrastructure. Recent publications (2023-2026) address RPKI validation risks , DNSSEC operational challenges , email authentication protocols , and scalable TLS monitoring . He explores post-quantum DNSSEC transitions and decentralized revocation mechanisms. Scientific awards include: NSF CAREER Award (2024) Outstanding New Assistant Professor, Virginia Tech (2024) IRTF Applied Networking Research Prize (2019) ACM CCS Best Paper Honorable Mention (2022) He mentors Ph.D. and Master’s students in cybersecurity, with former advisees securing positions at Meta, Cloudflare, and UVA. His research receives grants like the IRTF travel grant for IETF meetings (2025).

Stephan ThesmannView profile

Professor

• Business Informatics
• E-Business
• E-Learning
• +9 more

Stephan Thesmann is a Professor of Business Informatics at Pforzheim University, specializing in multimedia application systems. He holds a doctorate in business administration and has been active in academia since the 1990s. His career includes roles as a visiting professor at ESC Clermont Graduate School of Business and leadership in e-learning initiatives. Focus areas: E-Business, AI applications, human-computer interaction, and SEO/SEM Key projects: University-wide e-learning implementation (2003-2007), international Digital Enterprise Management program (2016-2019) Leadership roles: Dean of Studies for Business Informatics (2013-2020) His research explores digital business process optimization, accessible web design, and search engine strategies. He has authored textbooks including 'Interface Design' and 'Wirtschaftsinformatik für Dummies'. Scientific awards include the 2018 Teaching Award from the Faculty of Business and Law. He actively contributes to program accreditation and serves on Pforzheim University’s IT Advisory Board.

Michael MarmannView profile

Professor

• E-Learning
• Multimedia
• Database Systems
• +11 more

Prof. Dr. rer. nat. Michael Marmann is a full professor at the Faculty of Media of the University of Applied Sciences Düsseldorf . Since 2000, he has led teaching and research in E-Learning, Multimedia, and Database Systems , with research interests spanning E-Learning strategies, knowledge management, digital transformation, and interactive media development. He has been a web administrator for the Faculty of Media since 2001 and held an additional teaching role at the University of Duisburg-Essen’s Learning Lab in 2014/15. His work includes developing integrated e-learning platforms like alex and eStudy and leading student projects in digital applications and corporate learning. Education : Diploma in Computer Science from Dortmund University PhD in Information Systems and Databases from Fernuniversität Hagen (supervised by Prof. Gunter Schlageter) Research Interests : Optimization of E-Learning development processes Interactive learning media and knowledge cooperation Agile project management (Scrum, Kanban) Generative AI and synthetic media in education Knowledge work in the 21st century Teaching Portfolio : Lectures on Digital Literacy (since 2010), covering topics like AI literacy, lifelong learning, and digital ethics Corporate Learning modules (2018–2024) exploring gamification, metaverse applications, and AI-driven workforce training Digital Applications and Lernagentur project-based courses focusing on real-world digital product development Labs & Projects : Co-leads the E-Learning and Knowledge Cooperation and Interactive Learning Media labs Developed the alex portal (2001–2011) combining SumTotal LMS with Microsoft SharePoint Contributed to eStudy (2012–2020) and central HSD-Moodle systems Key projects: MYproject (blended learning platform, 2011), Job5 (career portal matching student profiles with industry needs, 2010) Current Roles : Teaching Digital Applications (BMT 17.P04) and Lernagentur (BMT 20.P04) since 2018 Active in curriculum development for upcoming programs like BA Creative, Synthetic & Interactive Media (2027) Freelance consultant for digital media solutions

• Computer Science
• Artificial Intelligence
• Machine Learning
• +6 more

Xue Yang is a Professor in the Department of Computer Science and Engineering at Shanghai Jiao Tong University's School of Electronic Information and Electrical Engineering. With an extensive publication record spanning from 2023 to 2026, Dr. Yang has established herself as a prominent researcher in multiple interdisciplinary fields at the intersection of computer science and practical applications. Dr. Yang's research interests span a wide spectrum of cutting-edge computational fields including Artificial Intelligence , Machine Learning , Quantum Computing , Image Processing , and Healthcare Applications of AI . Her work demonstrates a remarkable ability to bridge theoretical computer science with practical applications across diverse domains such as biomedical informatics, oceanography, and e-commerce. The interdisciplinary nature of her research is evident in publications that combine computer vision with medical applications, quantum computing with image processing, and machine learning with environmental monitoring. An analysis of Dr. Yang's recent publications reveals a strong focus on developing novel algorithms and computational frameworks that address complex real-world problems. Her work shows particular strength in generative models , feature learning architectures , and data-driven optimization approaches. The consistent publication output across multiple high-impact venues demonstrates sustained research productivity and influence in her fields of expertise. Exponential stability analysis for nonlinear systems Advanced machine learning architectures for biomedical applications Quantum-classical hybrid computing models Blockchain applications for network security Computer vision techniques for specialized imaging scenarios

Holger MeyerView profile

Professor

• Databases
• Digital Libraries
• Information Retrieval
• +5 more

Dr. Holger Meyer is a faculty member at the University of Rostock's Faculty of Computer Science and Electrical Engineering, specifically in the Institute of Computer Science. He is based at the Konrad Zuse House on Albert-Einstein-Straße 22, Room 332, and can be reached at phone number 0381-498 7597 or via email at hme@informatik.uni-rostock.de. Dr. Meyer teaches a variety of database-related courses including Database Application Programming (Bachelor), Databases for Users (Bachelor), Databases III (Master), and Digital Libraries and Multimedia Information Retrieval (Master). He also supervises projects under KSWS/Project/NEidI. His research focuses on database systems, digital libraries, information retrieval, data science, and XML database technologies. Dr. Meyer has made significant contributions to the development of digital archive systems, particularly through the Hydra.PowerGraph System, which enables building digital archives with directed and typed hypergraphs. His work also extends to applying crowdsourcing techniques in cultural heritage projects like the Mecklenburg Field Name Archive and developing SQL-based approaches for machine learning and signal processing tasks. Dr. Meyer's recent publications (2017-2019) demonstrate a strong emphasis on practical applications of database technologies across diverse domains including environmental monitoring (particulate matter analysis), automotive engineering, digital humanities, and historical geography. His work bridges theoretical database concepts with real-world applications, particularly through SQL-based implementations of machine learning operations and signal processing techniques. Throughout his career, Dr. Meyer has collaborated extensively with colleagues at the University of Rostock, particularly with Professor Andreas Heuer, Meike Klettke, and other researchers in the database and information systems group. These collaborations have resulted in numerous publications in prestigious venues including Datenbank-Spektrum, LNI proceedings, and international conferences.

Anyi RaoView profile

Assistant Professor

• Artificial Intelligence
• Computer Vision
• Generative Models
• +4 more

Anyi Rao is an Assistant Professor at the Hong Kong University of Science and Technology (HKUST) where he leads the Multimedia Creativity Lab (MMLab@HKUST) and serves as Associate Director of the HKUST Media Intelligence Research Center. He received his Ph.D. from the Chinese University of Hong Kong and completed postdoctoral research at Stanford University. His research explores human-AI collaboration for creativity, focusing on understanding, editing, and creating art, media, and film. Research Interests: Rao's work centers on developing AI tools that enhance human creativity in visual media production. Key areas include: Controllable generative models for image and video synthesis AI-assisted cinematography and virtual production tools Multimodal understanding of films and creative content Human-AI collaborative workflows for artistic creation His research has produced influential tools like ControlNet and AnimateDiff used by industry leaders including Netflix and Amazon. Publication Trends: Rao's recent publications demonstrate a strong focus on diffusion models, controllable generation, and video understanding systems. His work consistently bridges technical innovation with practical applications in media production, showing increasing emphasis on real-time creative tools and filmmaker-AI collaboration paradigms. Awards and Honors: Forbes 30 Under 30 Asia (2025) Rising Star Award, World AI Conference (2024) Marr Prize (Best Paper), ICCV (2023) Magic Grant, Brown Institute for Media Innovation (2023) Hong Kong PhD Fellowship (2021) Academic Activities: Rao actively recruits students for his research group and has secured multiple grants including Amazon Video Research Fund and Tencent Rhino-Bird Grant. He organized the SIGGRAPH/CVPR Creative Visual Content Workshops and curated the Hong Kong AI Film Festival. He serves on program committees for major conferences including CVPR, ICLR, and SIGGRAPH Asia.