جستجوی استاد راهنمای دانشگاهی

Christian Meilickeمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Knowledge Graphs
• Ontology Matching
• +۵ مورد دیگر

Christian Meilicke is a Researcher at the Data and Web Science Group (DWS) within the School of Business Informatics and Mathematics at the University of Mannheim. His work focuses on artificial intelligence, ontology matching, and knowledge graph completion, with recent contributions to rule-based methods and their applications in business process modeling. He is heavily involved in teaching, coordinating courses such as 'Modeling Business Processes' and 'Artificial Intelligence.' His research interests include the integration of open and structured knowledge, probabilistic reasoning frameworks, and improving the efficiency of knowledge base systems. He has explored topics like inductive logic programming, automated debugging of ontologies, and the use of Markov Logic Networks for root cause analysis in IT systems. In terms of trends, his recent publications emphasize combining symbolic rule-based approaches with machine learning for knowledge graph tasks, such as activity recommendation and link prediction. He also investigates explainability in embeddings and temporal forecasting in knowledge graphs. His work often bridges theoretical advancements with practical applications in business informatics and data integration. No scientific awards have been explicitly mentioned. Christian has advised no formal students listed here but has contributed to teaching and mentoring through his courses and tutorials. His research and teaching are closely tied to the DWS Group, which focuses on data-centric AI and semantic technologies.

• RFID Technology
• Internet of Things (IoT)
• Wireless Sensor Networks
• +۳ مورد دیگر

Luca Catarinucci is affiliated with the University of Salento in Lecce, Italy. His research focuses on RFID technology, IoT systems, wireless sensor networks, and antenna design. He has collaborated extensively with researchers like Riccardo Colella and Luciano Tarricone, producing impactful work in smart healthcare systems, energy-autonomous sensors, and 3D-printed electromagnetic devices. His contributions span theoretical advancements in circuit design and practical applications in fields like environmental monitoring and biomedical research. Recent work emphasizes energy-efficient solutions and integration of AI-driven microcontrollers. Key research interests include improving RFID tag performance, developing IoT-aware architectures for healthcare, and advancing additive manufacturing techniques for antenna prototyping. His publications reflect a deep engagement with both hardware innovation and system-level integration of smart technologies. Notable projects include energy-autonomous parking sensors and novel RFID-based medical monitoring systems. Collaborations involve cross-disciplinary efforts in electrical engineering, computer science, and biomedical engineering, with applications ranging from industrial automation to personalized healthcare solutions. While no formal awards are listed, his prolific publication record and repeated funding of experimental platforms indicate significant academic influence.

Martin Lacknerمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Computational Social Choice
• Algorithms
• +۳ مورد دیگر

Martin Lackner is a Researcher at the Vienna University of Economics and Business (WU Wien) within the Institute for Data, Process and Knowledge Management. He previously held postdoctoral positions at the University of Oxford and TU Wien, and earned his doctoral degree (Dr. techn.) in computer science from TU Wien in 2014. His research focuses on artificial intelligence, computational social choice, and algorithm design, with a particular emphasis on multi-winner voting systems, approval-based methods, and fairness in decision-making processes. Education: PhD in Computer Science (TU Wien, 2014), Mathematics in Computer Science studies at TU Wien, and a semester at the University of Illinois at Urbana-Champaign (USA). Research interests include computational social choice topics such as multi-winner voting, approval-based committee rules, liquid democracy, and axiomatic analysis of voting systems. He has contributed to the development of the abcvoting Python library for implementing approval-based voting rules and co-authored the book Multi-Winner Voting with Approval Preferences (Springer, 2023). His work bridges theoretical computer science with practical applications in democratic processes and algorithmic fairness. Key contributions include studies on proportional representation mechanisms, participatory budgeting fairness, and long-term decision-making frameworks. Lackner's research frequently addresses the algorithmic aspects of collective decision-making, with publications in venues like Artificial Intelligence , Journal of Economic Theory , and top conferences such as AAAI and IJCAI. Grants and Projects: Principal investigator of the FWF-funded project Algorithms for Sustainable Group Decision Making (TU Wien, 2025–present), and co-developer of the abcvoting open-source software project.

• Static Analysis
• Logic Programming
• Program Verification
• +۴ مورد دیگر

Manuel V. Hermenegildo is a Professor at the Universidad Politécnica de Madrid, Spain. He is a prominent researcher in the field of programming languages and static analysis, with significant contributions to logic programming, program verification, and formal methods. His work focuses on advancing static analysis techniques, compiler optimization, and energy-efficient computing. He has co-authored numerous papers and organized international conferences such as LOPSTR and SAS, demonstrating his leadership in academic and research communities. His research explores topics including abstract interpretation, runtime checking, and parallel logic programming systems. He is a key contributor to the Ciao Prolog system, emphasizing comprehensive tool integration and formal methods. His research interests span static analysis frameworks, program verification, resource usage analysis, and energy efficiency in computing. He has developed methodologies for optimizing program performance while ensuring correctness, with applications in both theoretical and applied domains. His work often bridges the gap between high-level program analysis and low-level hardware constraints, particularly in embedded systems. Recent trends in his publications include advancements in static cost analysis, dynamic inference of invariants, and tools for incremental assertion checking. His collaborations with institutions like the University of Copenhagen and the University of Kent reflect a global network in advancing computational logic and software engineering. He has been actively involved in academic service, including editorial roles for conference proceedings and journals. His contributions highlight a commitment to both foundational research and practical tools for the programming language community.

Sebastián Ferradaمشاهده پروفایل

استادیار

• Knowledge Graphs
• Graph Databases
• Multimedia Databases
• +۳ مورد دیگر

Sebastián Ferrada is an Assistant Professor at the Data & Artificial Intelligence Initiative of Universidad de Chile. He also serves as Young Researcher at the Institute for Foundational Research on Data (IMFD) and Collaborating Researcher at the National Center for Artificial Intelligence Research (CENIA). His research focuses on Knowledge Graphs, with special emphasis on extraction, management, and applications for querying, browsing, and AI systems. His academic background includes: PhD in Computer Science (2021), Universidad de Chile MSc in Computer Science (2017), Universidad de Chile BEng in Computer Science (2017), Universidad de Chile Sebastián's research explores several key areas: Multimedia Databases with applications to Wikimedia Commons images Graph Databases and Knowledge Graphs construction Federated Data Management across heterogeneous RDF sources SPARQL query extensions for similarity-based operations Graph data management and compression techniques His recent publications demonstrate strong trends in knowledge graph construction, similarity-based querying, and efficient graph data management. These works combine theoretical advancements with practical implementations in real-world systems like IMGpedia and MillenniumDB. Scientific achievements include: Best Paper Award at CoopIS 2023 Best Demonstration Award runner-up at SIGMOD/PODS 2024 Best Student Paper (Resources Track) and Best Poster at ISWC 2017 First prize in CLEI 2017 for his Master's thesis Sebastián currently leads the Fondecyt project on graph data management and contributes to the U-Inicia project on AI processes in graph databases. He serves on the editorial board of Transactions on Graph Data and Knowledge.

Jason J. Jungمشاهده پروفایل

استاد

• Computer Science
• Knowledge Engineering
• Social Media Analysis
• +۳ مورد دیگر

Jason J. Jung is a Professor in the Department of Computer Engineering at Chung-Ang University, Seoul, Korea. His academic work focuses on knowledge engineering , social media analytics , and data mining within the Knowledge Engineering Laboratory. Research Interests : Computer Science, Social Knowledge, Data Modeling, Sentiment Analysis Projects : IoT-based cultural systems, real-time social event detection, transmedia storytelling models The 15 most recent publications (2014-2018) demonstrate expertise in social network analysis , multimodal data processing , and context-aware systems applied to urban services, cultural tourism, and digital storytelling. Key trends include real-time analytics , trust modeling , and collaborative frameworks for O2O services. Professional activities include editorial contributions, invited talks, and patent developments. Students at all levels (PhD/MSc/BSc) conduct research under his supervision at the Knowledge Engineering Laboratory. Personal interests include travel, film, painting, literature, and music.

Johannes Mäkelburgمشاهده پروفایل

پژوهشگر

• Cyber-Physical Systems
• Uncertainty Representation
• Knowledge Graphs
• +۳ مورد دیگر

Johannes Mäkelburg is a Doctoral Researcher at Technische Universität München , affiliated with the Chair of Data Engineering . His research focuses on addressing challenges related to uncertainty in cyber-physical systems , conducted in collaboration with the Collaborative Research Center (CRC) 1608 . He holds an M.Sc. in Mathematics from Ruhr-Universität Bochum (2021-2023) and a B.Sc. in Business Mathematics from the University of Trier (2017-2021). Research Interests : Uncertainty Representation, Knowledge Graphs, Graph Neural Networks, Data Engineering, Machine Learning Teaching : Seminar on Knowledge Graphs (INHN0015, INHN4006), Practical Course in Data Engineering (INHN0021) Email : johannes.maekelburg@tum.de His recent publications explore the intersection of knowledge graphs and uncertainty modeling in cyber-physical systems. Key contributions include unified frameworks for uncertainty representation and automation techniques for invoice validation using semantic technologies.

Rainer Kolischمشاهده پروفایل

استاد

• Airport Operations Management
• Health Care Operations Management
• Project Management and Scheduling
• +۲ مورد دیگر

Rainer Kolisch is a Professor of Operations Management at the TUM School of Management, Technical University of Munich , where he has held a chair since 2002. He currently serves as Head of the Operations & Technology Department (since 2024) and previously as Dean of the QTEM Masters Network (2016–present) and Vice Dean of International Affairs (2007–2020). His career includes academic roles at Technical Universities of Dresden (Full Professor, 2002) and Darmstadt (Associate Professor, 1999–2002). Affiliations: TUM School of Management, Technical University of Munich Editorial Roles: Editor-in-Chief of OR Spectrum (2014–2020), Member of editorial boards for journals like International Journal of Production Research Research Interests focus on Airport Operations Management , Health Care Operations Management , Project Management and Scheduling , and Engineer-to-Order Manufacturing . His work addresses dynamic scheduling, resource allocation, and robust optimization in transportation and healthcare systems, with recent studies on electric vehicle charging networks and agile project management. Scientific Awards include: Best Teaching Award (2022) Excellence in Reviewing (2022) OMEGA Best Paper Award (2021) Handelsblatt Research Recognition (2005) DFG Habilitation Fellowship Advising spans numerous PhD and Master’s students , including Christopher Bersch, Robert Brachmann, and Giacomo Dall'Olio. His grants likely include DFG funding, though specifics are not detailed here.

Guido Friebelمشاهده پروفایل

استاد

• Organizational Economics
• Personnel Economics
• Human Resource Management
• +۷ مورد دیگر

Prof. Guido Friebel, Ph.D. holds the Chair for Human Resources at Goethe University Frankfurt. He previously held positions at the Toulouse School of Economics (EHESS) and Stockholm School of Economics.

An Chenمشاهده پروفایل

استاد

• Life and Pension Insurance
• Risk Management in Finance and Insurance
• Optimal Asset Allocation
• +۴ مورد دیگر

Prof. An Chen is a Full Professor and Head of the Institute of Insurance Science at the University of Ulm, Germany. With expertise in actuarial science and financial risk management, their research focuses on life and pension insurance, optimal asset allocation, and derivatives pricing. Education: Ph.D. in Economics (2007), University of Bonn M.Sc. in Economics (2003), University of Bonn Student Assistant, Department of Economics (2001-2003) Research Interests: Life and pension insurance systems Risk management in financial institutions Optimal asset-liability management Climate risk and sustainable finance Awards: Chris Daykin Award (2023) ICA Best Paper Award (2018) Multiple ASTIN Bulletin PBSS Prizes (2019, 2021) University Teaching Awards (2016, 2011) Advising & Grants: Advised 14+ PhD students at Ulm and Bonn Co-editor of ASTIN Bulletin and Insurance: Mathematics and Economics Member of DGVFM Board and advisory committees Research Groups: Leading research on longevity risk, tontines, and sustainability-linked finance Collaborations with international institutions including Fudan University

• Virtual Reality
• Augmented Reality
• Educational Technology
• +۷ مورد دیگر

Roghayeh Barmaki is a researcher with extensive publications in virtual reality, augmented reality, and educational technology. Her work spans rehabilitation systems, autism therapy, and neuroimaging analysis using fNIRS. She collaborates with institutions including Georgia Institute of Technology and University of Florida. Key Collaborators : Anjana Bhat, Jicheng Li, Shayla Sharmin, Vuthea Chheang Research Themes : Wearable sensors, LSL framework, movement synchrony, multimodal learning analytics Research Interests She focuses on immersive technologies for education and therapy, with expertise in: Functional Near-Infrared Spectroscopy (fNIRS) for cognitive engagement Wearable sensor integration in rehabilitation Gender perspectives in AR/VR education Multimodal affect analysis for autism Privacy-preserving behavioral analytics 3D visualization for anatomy training Publication Trends Recent work emphasizes fNIRS applications in gaming environments and hybrid deep learning models for cognitive analysis. Earlier studies focused on gesture recognition, movement synchrony estimation, and autism intervention datasets. Impactful Projects She developed the MMASD dataset for autism research and contributed to VR therapy systems. Her collaborations include: Georgia Tech's Autism Technology Research University of Florida's TeachLivE virtual classroom Germany's AIxVR conference contributions International collaborations on sensor systems

• Explainable Artificial Intelligence
• Type-2 Fuzzy Logic Systems
• Computational Intelligence
• +۱۲ مورد دیگر

Hani Hagras is a Professor in the School of Computer Science and Electronic Engineering at the University of Essex, UK , where he leads pioneering research in type-2 fuzzy logic systems and explainable artificial intelligence (XAI) . His work bridges theoretical advances with real-world applications in smart infrastructure, healthcare, telecommunications, and ambient intelligence. His research interests include explainable AI, type-2 fuzzy logic, computational intelligence, machine learning, human-computer interaction, and intelligent systems. He investigates how fuzzy systems can enhance the transparency, robustness, and adaptability of AI models, particularly in uncertain and dynamic environments. His recent work explores applications in genomics, predictive maintenance, and smart grid optimization. The publication trends show a strong focus on integrating fuzzy logic with deep learning and optimization techniques to create interpretable models. His work frequently appears in top-tier journals such as IEEE Transactions on Fuzzy Systems , IEEE Transactions on Artificial Intelligence , and Neurocomputing . He emphasizes real-world applicability, often collaborating with industry partners like BT. ORCID: 0000-0002-2818-5292 He has advised numerous PhD and Master’s students, including Mehrin Kiani, Ashish Bhatia, and Hugo Leon-Garza, many of whose research projects focus on workforce optimization, healthcare AI, and intelligent systems. His research has been supported by major grants, particularly in smart environments and telecommunications. Hani Hagras is actively involved in leading research labs and teams at the University of Essex, including work on augmented reality for field service support, georeferenced data visualization , and ambient-assisted living systems. His team develops fuzzy logic frameworks for real-time decision-making in complex environments.

Renaud Vilmartمشاهده پروفایل

پژوهشگر

• Quantum Computing
• Categorical Quantum Mechanics
• Formal Methods for Quantum Computing
• +۷ مورد دیگر

Renaud Vilmart is a researcher at LMF (Laboratoire Méthodes Formelles), part of Inria Saclay, affiliated with Université Paris-Saclay, CNRS, and ENS Paris-Saclay. He holds an Inria Starting Faculty Position (ISFP), placing him in a research-intensive faculty role. He is actively involved in the scientific committee of Inria Saclay and co-supervises the Groupe de Travail Informatique Quantique (GTIQ) under the GdR-IFM. His research focuses on quantum computing, particularly on the ZX-Calculus —a graphical language rooted in category theory that enables visual reasoning about quantum processes. This formalism unifies quantum circuits and measurement-based models, offering intuitive tools for verification and optimization. His work addresses foundational questions such as the completeness of the ZX-Calculus with respect to quantum mechanics. The 15 most recent articles reflect a strong trend in formal methods for quantum computing , with emphasis on diagrammatic reasoning, categorical semantics, and completeness proofs. Key topics include stabilizer theory, Clifford+T circuits, fermionic circuits, and scalable extensions of the ZX-Calculus. These publications demonstrate a deep integration of logic, algebra, and quantum theory. His scientific achievements have been recognized with: Kleene Award for best student paper at LiCS (Logics in Computer Science) Accessit (honorable mention) for the Gilles Kahn Award from the Société Informatique de France He is actively involved in mentoring and academic leadership through co-supervising GTIQ and serving on the Inria Saclay scientific committee. Though no specific grants are listed, his ISFP position is typically grant-funded, indicating sustained research support. He contributes significantly to education through teaching in the QDCS and QMI master’s programs and the ARTeQ year, focusing on advanced complexity and quantum computing topics. His research is conducted within the LMF (Laboratoire Méthodes Formelles), a collaborative lab between Inria, CNRS, and ENS Paris-Saclay, which fosters interdisciplinary work in formal methods and theoretical computer science.

• Corporate Taxation
• International Taxation
• Public Finance
• +۴ مورد دیگر

Prof. Dr. Christoph Spengel holds the Chair of General Business Administration and Business Taxation II at the University of Mannheim. His academic focus lies in corporate taxation, international tax policies, and legal form optimization. He actively contributes to research on cross-border taxation, tax harmonization, and tax reform. Recent engagements include advising on cum-cum transaction regulations and presenting at the North Rhine-Westphalia State Parliament in 2025. Spengel co-authored influential works like *Corporate Taxation and Legal Form* (2015), a standard reference for German company taxation. He leads the MaFAT e.V. initiative, fostering collaboration in accounting and taxation education. His research spans global minimum tax, EU tax base harmonization, and tax incentives for innovation.

• Database Systems
• Data Privacy
• Machine Learning
• +۴ مورد دیگر

Zhenjie Zhang is a Professor in the Department of Computer Science at East China Normal University's School of Computer Science and Software Engineering, with a distinguished research career spanning nearly two decades. His work bridges theoretical computer science with practical industrial applications, maintaining strong international collaborations with researchers from TU Wien, National University of Singapore, and industry partners including ByteDance. Dr. Zhang's research focuses on the intersection of database systems, machine learning, and industrial applications. His early work centered on database privacy and query processing, evolving toward causal inference, fault diagnosis systems, and industrial AI applications. His recent publications demonstrate a strategic shift toward solving real-world engineering problems using advanced machine learning techniques, particularly in manufacturing, transportation, and cloud systems. The consistent publication trajectory across top venues like IEEE TKDE, VLDB, and ACM Transactions shows sustained research excellence and adaptability to emerging technical challenges. His publication record reveals significant contributions to causal inference methods, evidenced by multiple papers on causal discovery and transfer learning. The research demonstrates practical impact through industrial collaborations, particularly in fault diagnosis systems for mechanical equipment and adaptive control for unmanned vehicles. The recent work shows increasing focus on deploying AI models efficiently in resource-constrained environments, reflecting awareness of practical implementation challenges. Dr. Zhang has mentored numerous junior researchers who have become active contributors in the field, including Ruichu Cai and Zining Zhang. His collaborative network spans multiple continents, indicating strong research leadership and international recognition. The consistent flow of publications in top venues suggests successful grant funding and research group management, though specific grant details aren't provided in the source material.