Find Academic Supervisors

• Computer Networks
• Distributed Systems
• Data Mining
• +3 more

Wesley W. Chu is a Professor in the Computer Science Department at the University of California, Los Angeles . He earned his B.S.E. and M.S.E. in Electrical Engineering from the University of Michigan (1960, 1961) and Ph.D. in Electrical Engineering from Stanford University (1966). His career spans roles at IBM, Bell Laboratories, and UCLA since 1969. B.S.E. (EE), University of Michigan (1960) M.S.E. (EE), University of Michigan (1961) Ph.D. (EE), Stanford University (1966) Dr. Chu's research has evolved from foundational work in computer communications , distributed databases , and real-time systems (notably statistical multiplexing and ATM network development) to modern focus areas in intelligent information systems , data mining , and medical digital libraries . His methodologies for approximate matching and query relaxation underpin systems like CoBase , KMeD , and CoXML , with applications in logistics, healthcare, and web technologies. His contributions to data security and privacy (ISP project), XML schema transformation , and medical image systems have earned recognition through multiple best paper awards and the IEEE Technical Achievement Award (2003). He has held editorial and organizational roles at major conferences including SIGCOMM, VLDB, and ER.

• Big Data Analytics
• Cloud Computing
• Data Stream Processing
• +4 more

Yanlei Diao is a Professor of Computer Science at École Polytechnique (France) with a joint appointment at the University of Massachusetts Amherst. She received her PhD from UC Berkeley in 2005. Her research focuses on scalable data systems, particularly in big data analytics, cloud computing optimization, and real-time stream processing. Research Interests: Her work spans cloud infrastructure optimization (UDAO project), explainable anomaly detection in data streams (EXAD), interactive data exploration (AIDEme), genomic data analysis (GESALL), and uncertain data management (CLARO). She leads the CEDAR team at Inria/LIX focusing on cloud-scale data exploration. Awards & Honors: ERC Consolidator Grant (2017-2023) CRA-W Borg Early Career Award (2013) NSF CAREER Award (2008) Keynote speaker at ACM DEBS 2021 and SWIFT 2023 AI Forum Best Paper Award at SIGMOD 2011 ACM SIGMOD Dissertation Honorable Mention (2005) Advising & Leadership: Mentored over 20 PhD students and postdocs, currently supervising 7 researchers. Served as PVLDB PC Co-Chair (2025-2026) and ACM SIGMOD Editor-in-Chief (2014-2019). Leads multiple projects with industry partners including Alibaba Cloud.

Jeremy Fei WangView profile

Professor

• Artificial Intelligence
• AI-Driven Recommendation Systems
• E-Commerce
• +4 more

Jeremy Fei Wang is a Professor of Computer Information Systems at Flagler College within the School of Liberal Arts and Sciences and Department of Math & Technology, also serving as Director of the China Program. He leverages extensive industry experience from senior consulting roles at Cap Gemini Ernst & Young and Meritage Technologies, where he collaborated with global clients including Procter & Gamble and General Electric on enterprise IT solutions. Dr. Wang's academic credentials include: Ph.D. in Business Information Technology from Virginia Tech (2022) M.B.A. with MIS concentration from Ohio University (1998) B.A. in Economics from Marietta College (1996) His research centers on artificial intelligence applications in business contexts, with particular expertise in AI-driven recommendation systems, e-commerce frameworks, and Web 2.0/mobile platform development. Dr. Wang investigates user trust in AI agents through affordance theory, examines AI's impact on customer relationship management, and explores localization strategies for digital platforms in international markets. His work bridges theoretical innovation with practical business implementations across consumer products, finance, and healthcare sectors. Analysis of Dr. Wang's publication history (2010-2023) reveals a consistent trajectory from foundational Web 2.0 and e-commerce studies toward cutting-edge AI research, particularly in recommendation agent design. His recent work demonstrates increasing focus on China's digital ecosystem and dual-process models for user behavior, while maintaining strong connections to enterprise systems and mobile application development. The integration of affordance theory across his publications provides a unifying framework for understanding human-AI interaction. Professional recognition includes: Honored Guest Professor appointments at three Chinese universities Cap Gemini Ernst & Young's 'Consultant of the Month' (awarded twice) Cap Gemini Ernst & Young's 'Ace Award' (top 3% globally) Phi Kappa Phi honor society membership Beta Gamma Sigma and Omicron Delta Epsilon distinctions As an educator, Dr. Wang developed and teaches courses spanning business analytics, ERP systems, mobile application development, and information security. His China Program leadership involves strategic partnership development, recruitment innovation, and family support systems for Chinese students. His industry background directly informs classroom practice through real-world case studies and hands-on technical training.

Frank van HarmelenView profile

Professor

• Artificial Intelligence
• Knowledge Representation
• Semantic Web
• +3 more

Frank van Harmelen is a full professor at the Vrije Universiteit Amsterdam and scientific director of The Network Institute. He specializes in Artificial Intelligence, Knowledge Representation, and the Semantic Web. His research includes foundational contributions to OWL, Sesame, and large-scale reasoning engines. He holds a PhD from the University of Edinburgh (1989) and has been recognized with awards like the 10-Year Impact Award (2012). Research interests span symbolic knowledge representation, large knowledge bases, and medical guideline formalization. Notable projects include the EU-funded Large Knowledge Collider and the formalization of Dutch breast-cancer guidelines using dynamic temporal logic. Awards: Distinguished Lecturer (2003), Keur der Wetenschap (2005), European AI Society Fellow (2007), and Most Cited Article Award (2011). Advising includes student Jacopo Urbani, co-author of prize-winning work. His work integrates theorem-proving with medical applications and semantic web infrastructure.

• Database Systems
• Integration of heterogeneous databases
• Data quality and data integrity
• +6 more

Thomas Kudraß serves as Professor for Database Systems at the Faculty of Computer Science, Mathematics and Natural Sciences (IMN) at Leipzig University of Applied Sciences (HTWK Leipzig). With over 25 years of academic and industry experience, he teaches courses including Database Basics, Database Application Programming, Data Warehousing, and Big Data Technologies. His leadership roles include Internship Coordinator for Computer Science since 2001, Member of the Academic Senate since 2011, and Contact person for the IMN faculty alumni association since 2005. Dr. Kudraß earned his Dipl.-Ing. in Computer Science from Technical University of Dresden (1985-1990) and completed his doctorate at Darmstadt University of Technology (1992-1997), where his dissertation received the prestigious Jos Schepens Memorial Award. Prior to academia, he worked as an Information Systems Architect at UBS AG Zurich and Database Specialist at Swiss Bank Corporation Basel. His research spans database technologies with focus on heterogeneous database integration, data quality, data privacy, and modern database concepts. Recent work explores cloud-native billing applications for 5G, NoSQL databases, and privacy-preserving record linkage techniques. His publication record shows continuous evolution from traditional database systems to contemporary challenges in big data and distributed systems. Jos Schepens Memorial Award for doctoral dissertation (1997) Active participation in German Informatics Society (GI) specialist groups Organizer of multiple database-related workshops and conferences Professor Kudraß has significantly contributed to academic governance as E-Learning Officer (2000-02), Faculty Council member (2009-12), and liaison lecturer for the German Society for Computer Science (2001-14). He has coordinated numerous student projects and served on program committees for major conferences including INFORMATIK 2017 and BTW series.

Beatrice MarkhoffView profile

Professor

• Semantic Web
• Knowledge Engineering
• Semantic Interoperability
• +5 more

Beatrice Markhoff is a Professor of Computer Science (CNU 27) at the University of Tours , affiliated with the Faculty of Science and Technology (Blois site) and the Computer Science Department . She is a member of the UMR CNRS 7324 - CITERES - Archaeology and Territories Laboratory (CITERES-LAT) and the Maison des Sciences de l'Homme Val de Loire (MSH VdL) . Her research focuses on semantic interoperability , Web of data , knowledge representation , and knowledge extraction , with significant collaborations in cultural heritage disciplines . Doctorate in Computer Science, University of Franche-Comté (1995) HDR (Habilitation to Direct Research), François Rabelais University of Tours (2013) Her research themes include semantic interoperability, knowledge engineering, and data mining, with applications in cultural heritage. She co-created the International Workshop on Semantic Web for Cultural Heritage and co-edited special issues for the Semantic Web Journal and JOCCH . She leads projects like ANR SESAMES (2018-2023), H2020 ARIADNEplus (2019-2022), and H2020 4CH (2021-2023). Her academic contributions span XML data management, semantic web technologies, and functional programming. Key projects include carto4CH for cultural heritage mapping and OpenArchaeo for knowledge graph profiling. She has co-supervised PhD theses on topics like LOD querying and knowledge extraction from Wikidata .

Tobias BlankeView profile

Professor

• Artificial Intelligence
• Digital Humanities
• Big Data Ethics
• +7 more

Professor Tobias Blanke is a leading scholar at the University of Amsterdam and the Institute for Logic, Language, and Computation , with additional affiliation as Visiting Professor of Social and Cultural Informatics at King’s College London. His work bridges artificial intelligence and humanities disciplines. PhD in Computer Science and Political Philosophy Director of DARIAH (2012–2016) Head of Digital Humanities Department at KCL (2016–2019) Blanke’s research focuses on artificial intelligence and big data applications within the human sciences, emphasizing ethical implications such as: Predictive policing systems Algorithmic othering Platform monopolization Computational genealogy XML retrieval frameworks His recent publications demonstrate increasing interdisciplinary collaboration in digital humanities , with key partnerships at the Open Data Institute , TacticalTech , and British Library . While no formal awards are listed in available materials, his leadership in infrastructural projects like the European Holocaust Research Infrastructure highlights significant contributions to the field. Blanke maintains active teaching and research roles, leading initiatives like the International Artificial Intelligence PhD Academy courses for social sciences. His technical expertise spans: XML retrieval systems NoSQL database applications Algorithmic governmentality Digital publishing frameworks

• Database Systems
• Data Management
• Data Mining
• +4 more

Michael Grossniklaus is a Professor at the University of Konstanz, Germany, specializing in database systems, data management, and information systems. His research focuses on query optimization, social media data streams, and object-oriented databases. He has contributed to the development of C-SPARQL for RDF stream processing and frameworks for adaptive data management. Grossniklaus has collaborated extensively with researchers in areas such as trajectory data modeling, cloud database optimization, and context-aware systems. His work emphasizes practical applications in education technology, mobile computing, and semantic web technologies. Affiliation: University of Konstanz, Germany Key Research Areas: Database Systems, Data Mining, Social Media Analysis, Query Optimization Notable Projects: C-SPARQL, Sahara (cloud database optimization), LPLM (neural cardinality estimation) Recent publications highlight advancements in neural models for cardinality estimation, trajectory data models, and memory optimization in cloud databases. His interdisciplinary approach bridges theoretical foundations with real-world applications in education, social media, and mobile systems.

Weimin HeView profile

Professor

• Big Data Management
• Information Retrieval
• XML Data Management

Weimin He is a Professor in the Department of Computing and New Media Technologies at the University of Wisconsin-Stevens Point, where he has taught since 2009. As Academic Director, he initiated and developed the online Applied Computing degree-completion program. His research is recognized internationally, with publications cited at conferences like the International Conference on Information System and Artificial Intelligence. Education: Ph.D. in Computer Science, University of Texas-Arlington M.S. in Computer Science, Yunnan University, China B.S. in Computer Science, Yunnan University, China Research Focus: Professor He specializes in XML data management systems, information retrieval optimization, and scalable big data solutions, emphasizing practical applications in search engine technology and database efficiency. Publications: His 3 most recent articles (2011-2019) focus on XML query processing, visual evaluation interfaces, and Lucene-based search engines, reflecting sustained innovation in data retrieval methodologies. Professional Leadership: Senior Member, International Association of Computer Science & Information Technology Program Committee Member, International Conference on Frontiers of Information Technology (2018-present) Editorial Board, International Journal of Communications and Information Sciences (2010-present) and International Journal of Computer Theory and Engineering (2014-present) Courses Taught: Database Systems, Object-Oriented Programming, Data Structures and Algorithms, Programming Languages, Introduction to XML, and foundational computing courses.

• Data Modeling
• Data Security and Privacy
• Healthcare Data Management
• +5 more

Faiz Currim serves as Professor of Practice in Management Information Systems and Assistant Director of the INSITE: Center for Business Intelligence and Analytics at the University of Arizona's Eller College of Management. He joined the institution in 2011 after six years at the University of Iowa, having earned his PhD from the University of Arizona in 2004. His educational background includes: PhD in Management Information Systems, University of Arizona (2004) Dr. Currim's research focuses on data modeling, security, privacy, and specialized management of healthcare, temporal, and spatial data systems. His work bridges database theory with practical applications in urban mobility, patient care, and workplace wellbeing through advanced techniques including deep learning, network science, and big data analytics. Current projects address real-world challenges in healthcare analytics and smart city infrastructure. Analysis of his recent publications reveals strong trends in applying artificial intelligence to healthcare cost prediction and urban transportation systems, with consistent use of heterogeneous data sources and machine learning frameworks across diverse domains from patient monitoring to bike-sharing optimization. His scientific recognition includes: Best Paper Award at IEEE 2nd International Smart Cities Conference (2016) Dr. Currim directs the INSITE center's initiatives in business intelligence while teaching core courses including Enterprise Data Management and Business Data Communications. His academic leadership spans curriculum development in data security, XML schema, and spatial database applications, with active collaboration across healthcare and urban planning domains. He maintains leadership roles in professional organizations including the Association for Information Systems (AIS), INFORMS, and Association for Computing Machinery (ACM), driving interdisciplinary research through the INSITE center's industry partnerships and analytics projects.

Peixiang LiuView profile

Professor

• Computer Networks and Distributed Systems
• Cloud Computing
• Machine Learning
• +5 more

Peixiang Liu is a Professor in the Department of Computing at Nova Southeastern University's College of Computing & Engineering. He holds a Ph.D. from Imperial College London (Electrical and Electronic Engineering) and an MS in Computer Science from Peking University. His research focuses on computer networks, distributed systems, cloud computing, machine learning, database systems, network security, and big data analytics. Education Background: Ph.D., Electrical and Electronic Engineering, Imperial College London MS, Computer Science, Peking University Research Interests: Dr. Liu explores advanced topics in self-aware networks (SAN), quality of service (QoS), spatial databases, and business intelligence. He has contributed to geographic information system (GIS) database engines using XML data exchange formats. His work bridges theoretical computer science with practical applications in distributed systems and cybersecurity. Professional Activities: Conference roles: Poster Chair, Publications Chair, Session Chair, Program Committee Member (CATA, ISCIS, IPCCC) Reviewer for journals: Proceedings of the Royal Society, Performance Evaluation, The Computer Journal IEEE and ACM member Teaching & Industry Experience: Previously taught at Informix-Peking University Training Center and worked as a software engineer at New Sanhui Software Company in China.

• Process-oriented Information Systems
• Healthcare Information Systems
• Semi-structured Data Management
• +5 more

Barbara Oliboni serves as an Associate Professor in the Department of Computer Science at the University of Verona's School of Science and Engineering. Her academic appointments include membership on the Computer Science Department Council, Computer Science Teaching Committee, and Faculty Board of PhD in Computer Science. She also holds administrative roles as Chair of the Commission for Quality Assurance for the Master's Degree in Computer Engineering and Science, and as Departmental Orientation Representative. Her research focuses on three primary areas: Process-oriented Information Systems (modeling business processes with emphasis on temporal aspects and conceptual data modeling); Healthcare Information Systems (managing multimedia and temporal clinical data, visualization of clinical information); and Semi-structured Data Management (XML document modeling with attention to temporal aspects, versioning and evolution of documents). Her work intersects with artificial intelligence, human-computer interaction, and web information systems as reflected in her ERC research sector classifications (PE6_7, PE6_9, PE6_10). Dr. Oliboni participates in multiple research projects including SHIELD (Securing Decentralized Finance and Remote Healthcare Systems), NOMEN (Novel Methodologies and Tools for Next Generation Cyber Ranges), and previously led work on temporal clinical process modeling and bioinformatics platforms for temporal knowledge discovery. Her laboratory affiliations include the STARS Laboratory (Semistructured Temporal clinicAl GeogRaphical Systems). She teaches across multiple degree programs including Master's in Computer Science and Engineering, Bachelor's in Bioinformatics, and Bachelor's in Human Centered Medical System Engineering. Her current courses for 2025/2026 include Business Intelligence, Databases and WEB, Database Systems for Bioinformatics, and Information Systems.

Anca MuschollView profile

Professor

• Foundations of Formal Verification
• Automata Theory
• Logics and Games
• +2 more

Anca Muscholl is a Professor at the University of Bordeaux and holds the Hans Fischer Senior Fellowship at the Technical University of Munich (TUM-IAS). She leads the Formal Methods group at the Bordeaux Laboratory for Computer Science Research (LABRI). Her research focuses on foundational aspects of formal verification, automata theory, logics, concurrent systems, and database foundations. She has held academic positions at the University of Paris 7 and has been recognized with prestigious awards, including the Silver Medal from CNRS (2010) and membership in the Institut Universitaire de France (2007–2012). Education: Master’s from Technical University of Munich (TUM), PhD from University of Stuttgart (1994), and habilitation at the same institution. She has contributed to editorial roles for journals like Information Processing Letters and Discrete Mathematics & Theoretical Computer Science , and serves on the council of the European Association for Theoretical Computer Science (EATCS). Her work emphasizes automated controller synthesis for distributed systems and formal methods in concurrency. Notable achievements include advancements in distributed synthesis, temporal logic, and verification of reactive systems. She actively participates in organizing major conferences like ICALP and steering committees for theoretical computer science initiatives. Awards: Silver Medal (CNRS 2010), Junior Member of IUF (2007–2012), Best Paper Awards (PODS 2006, ETAPS 2001). Professional Roles: Editor for TheoretiCS , member of EATCS council, and leader of the Formal Methods group at LABRI. Research Themes: Formal verification, automata theory, concurrency, distributed systems, database logics.

Ghislain FournyView profile

Lecturer

• Quantum Mechanics
• Game Theory
• Database Systems
• +6 more

Ghislain Fourny is a Lecturer and senior scientist in the Department of Computer Science at ETH Zurich. His research spans quantum foundations, game theory, and database systems. He develops deterministic models merging game theory into quantum physics, proposing non-Nashian solution concepts to address quantum paradoxes. He co-designed the JSONiq query language and leads the RumbleDB project for large-scale data querying. A recipient of multiple teaching awards including the Golden Owl and ETH Medal, he advises numerous students on topics ranging from quantum theory to database systems. His work bridges theoretical physics, computer science, and mathematics, aiming to reconcile determinism with quantum mechanics through game-theoretic models. Education : Holds a Master's in Quantum Information (2007) and a PhD in Computer Science (2011). His early career included pioneering work on XBRL standards and XQuery implementations. Research Themes : Non-Nashian game theory: Fixpoint equilibria avoiding Grandfather paradoxes, Pareto optimality. Quantum foundations: Deterministic models challenging free-choice assumption, spacetime games integrating special relativity. Database systems: JSONiq language design, RumbleDB for scalable querying of heterogeneous data. Teaching Contributions : Courses include Big Data for Engineers, Information Retrieval, and Information Systems for Engineers. His open-access Big Data textbook is widely used in universities. Recognition : Over 20 awards including the 2023 VIS Teaching Award, ETH Medal (2000), and multiple top ranks in international mathematics competitions since 1993.

Tova MiloView profile

Professor

• data integration
• XML
• semi-structured information
• +4 more

Tova Milo is a full Professor at Tel Aviv University's School of Computer Science, where she has been affiliated since 1995. She previously worked at INRIA in Paris and the University of Toronto. She leads the Database research group and holds the Chair of Information Management, having served as Head of the Computer Science Department from 2011–2014. Educations: Ph.D. in Computer Science, Hebrew University, Jerusalem (1992) Her research focuses on advanced database applications, spanning theoretical and practical aspects of data integration, XML/semi-structured data, data-centered business processes, and crowdsourcing. She pioneered the concept of "crowd mining" and developed the OASSIS system at Tel Aviv University to explore this paradigm. Scientific Awards: ACM Fellow Member of Academia Europaea 2010 ACM PODS Alberto O. Mendelzon Test-of-Time Award EU ERC Advanced Investigators Grant She has received grants from the Israel Science Foundation, US-Israel Binational Science Foundation, Israeli-French Ministry of Science, and European Union programs. Her service includes chairing international conferences (PODS, VLDB, ICDT, XSym, WebDB) and editorial roles in TODS and Logical Methods in Computer Science Journal. Tova leads the Database research group at Tel Aviv University and contributed to key crowdsourcing frameworks like OASSIS. Her work emphasizes hybrid systems combining database knowledge with crowd-sourced data.