Find Academic Supervisors

Nicole SchweikardtView profile

Professor

• Logic
• Database Theory
• Complexity Theory
• +3 more

Nicole Schweikardt is a full Professor at the Department of Computer Science, Humboldt-Universität zu Berlin, since 2014. She previously held positions at Goethe-Universität Frankfurt (W2/W3 Professor for Theory of Complex Systems, 2007-2014) and served as Junior-Professor for Logic and Database Theory at HU Berlin (2005-2007). Her research focuses on logic in computer science, particularly database theory and complexity theory. Key contributions include algorithmic meta-theorems for bounded degree structures, efficient query evaluation techniques, and analysis of first-order logic extensions with counting quantifiers. She explores query languages' expressivity, document spanners, and locality properties in logic. Recent work (2025) covers event stream query discovery, color refinement for relational structures, and learning aggregate queries via first-order logic. Earlier studies (2018-2022) address FO+MOD queries under updates, Hanf normal forms, and enumeration algorithms over sparse graphs. GI-Dissertationspreis (2002) Emmy-Noether Fellowship (2005) Heinz Maier-Leibnitz-Prize (2007) Teaching Award (2015) She has supervised 6 PhD theses and contributed to database conferences (PODS, ICDT, LICS) as PC member and workshop organizer. Her affiliations include DFG Fachkollegium Informatik (since 2024) and editorial boards of Acta Informatica and ACM SIGLOG Education Committee.

• Data Management
• Computational Logic
• Database Theory
• +10 more

Michael Benedikt is Professor of Computer Science at the Department of Computer Science, University of Oxford, and a Fellow of University College, Oxford. His research lies at the intersection of computational logic, database theory, and theoretical computer science, with a focus on query answering, logic-based data management, and formal methods for data integration. Institution: University of Oxford, Department of Computer Science Position: Professor of Computer Science Email: michael.benedikt@cs.ox.ac.uk Office: 355 Wolfson Building, Parks Road, Oxford OX1 3QD, UK His primary research interests include data management, computational logic, model theory, query reformulation, integrity constraints, existential rules, and fixpoint logics. He investigates theoretical foundations of querying Web and social network data, ontology-based data integration, and finite model reasoning. His recent publications span top venues such as VLDB, PODS, LICS, ICALP, and IJCAI, covering topics like scalable querying of nested data, interpolation in fixpoint logics, finite open-world query answering, and rewriting recursive queries. A unifying theme across his work is the application of logical methods to ensure correctness, decidability, and efficiency in data access and transformation. Best Paper Award, ICALP 2017 (Track B) EPSRC Established Career Fellowship (2015–2020) He has supervised numerous PhD students and postdoctoral researchers, including Jaclyn Smith, Djordje Zivanovic, Antonia Kormpa, and Benjamin Spencer. His research group has been supported by grants from EPSRC and Microsoft Research. He actively contributes to the academic community through service on program committees (e.g., LICS, PODS, IJCAI, VLDB) and editorial boards (e.g., Journal of Computer and System Sciences). He co-authored a book on interpolation-based query reformulation published by Morgan Claypool.

Marko JurčevićView profile

Professor

• Internet of Things (IoT)
• Machine Learning
• Electrical Measurements
• +3 more

Marko Jurčević is a Full Professor at the University of Zagreb’s Faculty of Electrical Engineering and Computing (FER), affiliated with the Department of Fundamentals of Electrical Engineering and Electrical Measurements. His research integrates IoT, machine learning, and electrical measurement systems, with applications in smart grids, traffic management, and web/mobile technologies. Research Interests: Jurčević’s work spans: IoT & Machine Learning : Recognition of sound/events in IoT environments, human activity detection via smartphones, and sensor data analytics. Electrical Metrology : Development of calibration frameworks for smart grids, PMU testing, and remote surveillance of energy meters. Web/Mobile Systems : TypeScript-based web frameworks, progressive web apps for event management, and microservice architectures. Publication Trends: His recent articles focus on IoT validation (especially in healthcare), smart grid metrology, real-time signal processing for power systems, and data cleaning algorithms for sensor networks. Machine learning applications in measurement systems and 5G-enabled safety solutions are recurring themes.

• Computer Science
• Semantic Web
• Ontology Matching
• +3 more

Alsayed Algergawy is a researcher at the Institute of Computer Science , Friedrich Schiller University Jena . His work focuses on ontology alignment , schema matching , and knowledge graph integration . Affiliation: Friedrich Schiller University Jena, Institute of Computer Science Research interests span semantic web technologies , machine learning for data integration , and ontology engineering , with applications in biodiversity and invasion biology . He has developed tools like OAPT for ontology partitioning and DREIFLUSS for table matching. His recent publications emphasize LLM-driven knowledge graph completion , semantic annotation of scientific datasets , and clustering-based ontology matching . Collaborative projects include BiodivNERE for NLP in biodiversity and INBIO (Invasion Biology Ontology).

• Explainable Machine Learning
• Biomedical Engineering
• Neurotechnology
• +7 more

Xinqi Bao is a Digital Futures Postdoctoral Fellow at KTH Royal Institute of Technology, affiliated with the School of Electrical Engineering and Computer Science and the Division of Information Science and Engineering. Their research focuses on applying explainable machine learning (XML) to analyze electronic health records and improve medication repurposing for dementia patients through the XMLD project, in collaboration with Karolinska Institute and Karolinska University Hospital. Education : PhD in Biomedical Engineering from King's College London (KCL). Prior Roles : Postdoctoral Research Associate at KCL and the Bath Institute for Augmented Human (IAH). Research Expertise : Biosensors, biomedical signal processing, wearable medical devices, prosthesis control, and cyberpunk-inspired technologies like biomechatronic prosthetics and brain-machine interfaces. Xinqi Bao’s work bridges cybernetics, machine learning, and healthcare, with a focus on translating Ghost in the Shell-inspired concepts into real-world applications. Their current project emphasizes enhancing clinical decision-making through XML-driven approaches. Contact: xba@kth.se

• Smart Healthcare
• Human-Computer Interaction
• Affective Computing
• +6 more

George Moore is a Senior Lecturer in the School of Computing at Ulster University, specializing in Smart Healthcare, Human-Computer Interaction, and Affective Computing. His research focuses on positive computing and its applications to mental wellbeing, cognitive fatigue assessment, and assistive technologies for chronic conditions. PhD in Computing (Ulster University, 2000, Best Thesis Award) BSc (Hons) in Computing (Ulster University, 1994) Research interests center on integrating mobile technology with healthcare, including: Smartphone-based cognitive fatigue assessment Assistive technologies for Parkinson’s disease and Alzheimer’s Emotion-aware systems (e.g., 'Emotional Drive' automotive interface) Usability evaluation of medical software Dataset generation for intelligent environments Recent publications analyze mobile cognitive fatigue assessment, windowing approaches in dense sensing environments, and emotional response modeling. He has received citations from Scopus and Mendeley readership, with an h-index of 13. Best Thesis Award (PhD, 2000) Senior Lecturer since 1999 Member of Pervasive Computing Research Group InvestNI innovation voucher recipient (2011) George actively engages with industry through consultancy projects and community initiatives such as Google Developer Group Belfast and Women TechMakers. He coordinates undergraduate final year projects and has over 20 years of teaching experience in computing disciplines.

• Natural Language Processing
• Computational Linguistics
• Syntax Analysis
• +4 more

Vojtěch Kovář is a researcher at Masaryk University with dual appointments at the Institute of the Czech Language (Faculty of Arts) and the Center for Natural Language Processing (Faculty of Informatics). He has been affiliated with the university since 2006, holding positions as researcher and lecturer while also working as a software analyst at Lexical Computing CZ since 2012. His research focuses on automatic syntactic analysis of natural languages , particularly Czech and related languages, evaluation of syntactic analysis quality , integration of syntactic tools into downstream applications , and corpus linguistics . His work bridges theoretical linguistics with practical language technology applications. Recent publications reveal a strong trend toward dictionary creation methodologies , lexicographic infrastructure development , and corpus-based language resource compilation . His research increasingly addresses rapid dictionary development for both European and Asian languages, as well as bilingual resource creation in response to emerging language needs. PACLIC 2010 best student paper award Member of eLex conference program committee (2017-present) Kovář supervises bachelor's and master's theses at both the Faculty of Arts and Faculty of Informatics, with recent topics including semi-automatic dictionary creation, web-based proofreading systems, and automatic punctuation correction. He teaches multiple courses including Fundamentals of Mathematics and Statistics for Humanities, Algorithmic Description of Syntax, and Programming Basics for Humanities. His research is supported by projects including LINDAT/CLARIAH-CZ (Digital Research Infrastructure for Language Technologies) and the Web-based spelling, grammar and typographical corrector for Czech language initiative.

Sebastian ManethView profile

Professor

• Databases
• Automata Theory and Applications
• Data Compression
• +3 more

Sebastian Maneth is a Heisenberg Professor at the Universität Bremen , affiliated with the Faculty of Mathematics and Computer Science and the Department of Computer Science . His research focuses on Databases , Automata Theory and Applications , and Data Compression , with significant contributions to tree transducers and XML processing. Editor of Theory of Computing Systems (TOCS) Associate Editor for Frontiers in Computer Science Editor of Algorithms His recent work explores the boundaries of tree transducers , regular expressions , and grammar-based compression , with decidable properties in formal language theory. He organizes major conferences like the Dagstuhl Seminar on Regular Expressions and serves on numerous program committees (CIAA, ICALP, FoIKS, etc.). Current projects include FO-Query Enumeration over compressed data, shape-preserving tree transducers , and user identification via eye-tracking data . His editorial and organizational roles highlight leadership in theoretical computer science communities.

Mathias MüllerView profile

Researcher

• Scientific Integrity
• Reproducibility
• Evaluation Protocols
• +8 more

Mathias Müller is a postdoctoral researcher at the University of Zurich, where he works on sign language translation and natural language processing (NLP) with a focus on scientific integrity and accessibility. He collaborates with Sarah Ebling , Annette Rios , and others as part of the EU-funded project EASIER . His research interests span Sign language processing Scientific reproducibility Robustness of NMT systems Teaching neural machine translation (NMT) Markup technologies (XML, XSLT, etc.) Phonetics and acoustics His recent publications highlight trends in sign language translation, including multimodal approaches, gloss-based translation, and Signwriting integration. These works emphasize evaluation protocols and addressing bias in NLP systems. Scientific awards include Outstanding Paper Award at ACL 2023 Best Paper Award at AfricaNLP 2023 Best Poster Award at Swisstext 2023 He advises students like Shester and collaborates with teams on NMT system development. His work is supported by a 4-year Bridge Postdoc grant funded by the University of Zurich's Digital Society Initiative (DSI).

Ana María Fermoso GarcíaView profile

Professor

• Computer Science
• Artificial Intelligence
• Semantic Technologies
• +5 more

Dr. Ana María Fermoso García is a Professor at the Facultad de Informática , Universidad Pontificia de Salamanca . Her academic profile includes a PhD from Universidad de Deusto (2004) with the thesis "XBD sistema de consulta basado en XML a bases de datos relacionales". Research groups: ICS. Innovación en Ciencias Sociales and MARATON. Mobile applications, internet of things, data processing, semantic technologies, open data Email: afermosoga@upsa.es Her research focuses on semantic technologies , internet of things , machine learning , and XML data integration . She has contributed to inclusive educational systems for people with intellectual disabilities, open access data systems , and smart tracking frameworks for IoT applications. Her recent work combines BLE technology with capacity control in indoor spaces during pandemics. The 15 most recent publications show expertise in semantic web applications for university transparency, conversational AI for education, event mesh architectures for IoT, and open data systems for academic information. These works span disciplines including computer science , artificial intelligence , and educational technology . Key projects include: Inclu-sí lab - Artificial intelligence system for labor inclusion ViAFACILITA - Educational mobile app using computer vision SCIFI Framework - Smart tracking for IoT systems Open UPSA 4.0 - CRIS system for university research

• Information Organization
• Metadata Systems
• Data Curation
• +4 more

Karen Wickett is an Assistant Professor at the School of Information Sciences (iSchool), University of Illinois Urbana-Champaign. Her research focuses on information organization systems, metadata frameworks, data curation, and the conceptual foundations of information systems. She holds a PhD in Library and Information Science from UIUC and has held prior faculty positions at the University of Texas at Austin and a postdoctoral role at the Center for Informatics Research in Science and Scholarship (CIRSS) at UIUC. Wickett teaches courses on information modeling and data curation, with current offerings including IS589KMW (Independent Study). Her educational background includes: PhD: Library and Information Science, UIUC Prior academic roles: Faculty at UT Austin School of Information; Postdoctoral Researcher at CIRSS/UIUC Professional affiliations: Active member of ASIS&T and DCMI (Dublin Core Metadata Initiative) Research interests span metadata design, critical data modeling, and the materiality of information systems. Notable projects include analyzing archival silences in digital collections, developing research process models for geobiology fieldwork, and investigating ethical dimensions of open government datasets. Her work emphasizes interdisciplinary collaboration, particularly in scientific and cultural heritage domains. Publications consistently address foundational questions in information science, such as metadata relationships, database materiality, and systemic biases in data systems. Recent work (2023–2025) explores critical data quality frameworks and feminist approaches to data ethics. Awards: ASIS&T Best Short Paper Award (2020) Advising and grants: No specific advising roles listed, though her research collaborations likely involve graduate students. Her grants include funding for geobiology data curation projects and interdisciplinary initiatives. Labs/Teams: Previously affiliated with CIRSS and collaborates with geobiology teams at Yellowstone National Park for data curation projects.

Michael ErdmannView profile

Professor

• Artificial Intelligence
• Robotics
• Topological Robotics
• +5 more

Michael Erdmann is a Professor in the Computer Science and Robotics departments at Carnegie Mellon University (CMU), where he has been since 2002. He also served as Associate Faculty at the University of Pittsburgh's Department of Computational Biology from 2002-2007. His research focuses on leveraging topology, geometry, and probability to address robotics challenges under uncertainty, with applications in in-hand manipulation, protein structure analysis, and privacy-preserving systems. Ph.D., Computer Science, MIT (1989) M.S., Electrical Engineering and Computer Science, MIT (1984) B.S., Mathematics, University of Washington (1982) His work on topological methods has produced groundbreaking results, such as a graph controllability theorem connecting homotopy to system uncertainty. Recent publications explore stateless distributed computation, extrinsic dexterity for robotic manipulation, and topological approaches to process modeling. Erdmann's research bridges theoretical mathematics with practical robotics, often yielding insights applicable to both fields. Key publication trends include: (1) Topology-driven Robotics (2010-2017) - developing strategy complexes and homotopy-based controllability; (2) Dynamic Contact Manipulation (2005) - analyzing frictional contact constraints; (3) Protein Structure Analysis (2004-2005) - applying knot theory to molecular biology. Herbert A. Simon Award for Teaching Excellence in Computer Science (2014) Erdmann has been actively involved in academic governance, serving on CMU's SCS Promotions Committee (2014-2016), Doctoral Dissertation Award Committee (2015), and multiple conference editorial boards including the International Journal of Robotics Research (2000-2017). He teaches foundational courses like 15150 (Principles of Functional Programming) and 16811 (Mathematical Fundamentals for Robotics), reflecting his commitment to education and curriculum development.

Frank-Dieter DorloffView profile

Professor

• Procurement Management
• Logistics Systems
• E-Business
• +7 more

Prof. Frank-Dieter Dorloff is a full professor at the University of Duisburg-Essen, holding the chair of Procurement, Logistics and Information Management since 1998. Previously, he was a professor at the University of Essen. His expertise spans e-procurement, logistics systems, and information management, with a focus on B2B e-commerce, XML-based data standards, and inter-organizational coordination. He leads research projects on topics like openTRANS (business transaction standardization) and BMEcat (product catalog XML standards). Education: Studied Communications Engineering and Economic Engineering at RWTH Aachen, earned a Ph.D. in Mechanical Engineering (1975) with a thesis on EDP-based production planning models. Research interests include e-business applications, electronic marketplaces, and data interoperability. He actively participates in industry collaborations with firms like Bayer, BMW, SAP, and Siemens, and serves on boards of organizations such as the Federal Association of Procurement (BME) in the Ruhr region and the Bundesvereinigung Logistik. Teaching focuses on two specializations: 'Procurement, Logistics and Information Management' (BLI) and 'Information Systems in Procurement and Logistics' (ISBL), emphasizing both operational logistics processes and supporting IT systems. Notable contributions include pioneering work on electronic cataloguing standards and e-procurement systems. His team addresses global business data standardization challenges through initiatives like CEN/ISSS projects and openTRANS.

Ashraf AboulnagaView profile

Professor

• Database Systems
• Cloud Computing
• Big Data
• +3 more

Ashraf Aboulnaga is a Professor in the Department of Computer Science and Engineering at the University of Texas at Arlington (UTA). He holds a Ph.D. in Computer Science from the University of Wisconsin-Madison and has held prior roles as Chief Scientist at the Qatar Computing Research Institute, Associate Professor at the University of Waterloo, and Research Staff Member at IBM Almaden Research Center. His research focuses on database systems, cloud computing, and graph analytics, with recent emphasis on cloud-native database architectures and scalable graph processing. Education: Ph.D. (2002), M.S. (1999) from University of Wisconsin-Madison; B.S./M.S. (1993/1996) from Alexandria University. Affiliations: ACM Distinguished Scientist (2015), IEEE Senior Member (2009). Research interests include cloud database systems, distributed transaction processing, and knowledge graph integration. He has authored over 100 publications in top venues like SIGMOD, VLDB, and ICDE, and received Best Paper Awards at SoCC 2015 and VLDB 2011. Grants: Current funding includes NSF travel support for ICDE 2024 and a $1.4M NSF MRI grant for DiscourseLab (2025). Past grants include DOE support for soil microbiome data integration. Service: Associate Editor for VLDB Journal, PVLDB, and Distributed and Parallel Databases. Served as Program Committee member for SIGMOD, ICDE, and EDBT. Industry collaborations include advising on cloud DBMS architectures and distributed systems.

• Cloud Computing
• Grid Computing
• Health Informatics
• +5 more

David Levine serves as an Associate Professor in the Computer Science and Engineering Department within the College of Engineering at The University of Texas at Arlington. His academic career spans decades with continuous teaching and research contributions, evidenced by his ongoing course instruction through Fall 2025 and active grant leadership. Levine's research spans cloud and grid computing, health informatics, bioinformatics, pervasive computing, and secure programming. His work integrates computational techniques with practical applications in healthcare (Smart Hospital for Elderly Care), high-energy physics (Fermilab collaborations), and accessibility infrastructure. He has pioneered curriculum development in emerging fields including Cloud Computing, Secure Programming, Mobile Computing, and Data Mining, with courses consistently reaching maximum enrollment capacity and establishing distance learning records within the engineering college. His publication portfolio demonstrates significant interdisciplinary impact across IEEE Supercomputing, health informatics, genetics, and pervasive computing. Recent work focuses on spatial data visualization for public health (2022), hardware simulation platforms (2017), and scalable notification frameworks for healthcare systems (2011). His research has secured over $5 million in funding from NSF, NIH, DoE, and industry partners including Luminant Power. Computer Science Department Teaching Award recipient Student teams won ATT University Challenge, Nokia Symbian Challenge, and Department of Energy Challenge ($200k+ total) Levine has mentored 4 PhD students as co-supervisor, chaired 6 Master's theses, and advised numerous undergraduate researchers. His laboratory work focuses on grid computing applications for high-energy physics and bioinformatics, with current projects including the GAANN Doctoral Fellowships in IoT and Smart Hospital infrastructure development. He serves as NTT Hiring Committee Chair and Faculty Senate Chair, demonstrating significant institutional leadership.