جست‌وجوی استاد و پژوهشگر

Laura Dietzمشاهده پروفایل

دانشیار

• Information Retrieval
• Natural Language Processing
• Knowledge Graphs
• +۳ مورد دیگر

Laura Dietz is a tenured Associate Professor in the Department of Computer Science at the University of New Hampshire. She leads the TREMA lab and focuses on text-based machine learning, information retrieval, and environmental data science. Her academic journey includes postdoctoral roles at Mannheim University and the University of Massachusetts, alongside a PhD from the Max Planck Institute for Informatics. Education: PhD in Computer Science (Max Planck Institute, 2011), followed by postdoctoral research at UMass (2012–2015) and Mannheim (2015–2016). Tenure-track appointment at UNH since 2016. Research Interests : IR+NLP: Integrates knowledge graphs, entity retrieval, and machine learning to automatically generate comprehensive articles. This work is supported by an NSF CAREER Award (2019–2023). Watershed Data Science: Analyzes storm event impacts using time-series forecasting, with grants from the Northeast Big Data Hub. Machine Learning: Develops methods for sequential data analysis across domains like social media and environmental science. Grants & Awards : NSF CAREER Award (Utilizing Fine-Grained Knowledge Annotations) Elite Postdoc Program of BW-Stiftung (2016–2019) Best Paper at JCDL 2018 for Entity-Aspect Linking Service & Leadership : Organized HIPstIR Workshop on non-mainstream IR research Coordinated TREC Complex Answer Retrieval Track (2017–2019) Keynote speaker at ECIR, NAACL, and SPIRE Labs & Teams : Head of TREMA Lab at UNH, focusing on query-driven knowledge synthesis and environmental data science. Collaborates with faculty in Natural Resources and the Environment Department.

• Software Testing
• Model-Based Testing
• Search-Based Software Engineering
• +۶ مورد دیگر

Raluca Lefticaru is an Associate Professor in Computer Science at the University of Bradford's School of Computing, Software and Artificial Intelligence & Engineering (CSAI&E), within the Faculty of Engineering & Digital Technologies. She leads the BEng Software Engineering programme and holds a visiting researcher position at the University of Sheffield's Testing group. A Fellow of the Higher Education Academy (FHEA), she specializes in software testing methodologies, particularly model-based testing using evolutionary approaches, formal specification, and P systems verification. Her research interests span software testing, model-based testing, search-based software engineering, membrane computing, and formal verification. Recent professional activities include organizing conferences such as YISEC 2023, AIERC 2022, and A-MOST 2021, serving as a program committee member for SEFM 2025, ICTSS 2023, and ICSE 2022, and reviewing for WCCI 2022. She has held roles including Co-chair of YISEC 2023 and Communication Chair of CMC18 (2017). Raluca's work emphasizes interdisciplinary applications, from IoT security to medical imaging analysis. Her publications reflect contributions to testing frameworks for P systems, fault tree analysis, and AI-driven solutions for cyberbullying detection and industrial fire prevention. She actively contributes to academic journals in membrane computing, optimization, and software engineering. Awards: Fellow of the Higher Education Academy (FHEA) Key Projects: IoT safety-security integration, robotic system testing, and COPD self-management systems Conference Leadership: Organized over 10 international conferences since 2017

Isidoro Gil Leivaمشاهده پروفایل

استاد

• Library Science
• Information Science
• Automatic Indexing
• +۴ مورد دیگر

Isidoro Gil Leiva is a Professor at the Department of Library and Documentation Science within the Faculty of Communication and Documentation at the University of Murcia. He holds a Doctorate from the same institution with a thesis on automated indexing in library science (1998). His research focuses on automated indexing systems, information retrieval, metadata modeling, and the impact of digital technologies on library practices. Key contributions include the development of the SISA automated indexing software and comparative studies of indexing methodologies. Education: PhD in Library Science from Universidad de Murcia (1998), with thesis titled 'La automatización de la indización propuesta teórico-metodológica'. Research Interests: Automated Indexing Systems (SISA, KEA, MAUI) Evaluation of Information Retrieval Systems Metadata Standards and Linked Data E-books Management in Academic Libraries Bibliometric Analysis of Scientific Output Recent Work Trends: His 2020-2024 publications emphasize: Impact of e-books on traditional cataloging practices Comparative analysis of author-assigned keywords vs automated systems Application of semantic web principles to audiovisual archives Optimization of satellite imagery metadata Advising & Grants: Supervised doctoral research under Dr. José Vicente Rodríguez Muñoz. Active in collaborative projects involving Latin American libraries and institutions. No specific grant details mentioned in provided texts. Labs/Teams: Involved in research groups like 'Libraries, Archives and Information Culture' and previously 'Information Technology' at Universidad de Murcia.

Masana Castrillo, Marcمشاهده پروفایل

پژوهشگر

• Deep Learning
• Continual Learning
• Computer Vision
• +۳ مورد دیگر

Herr Marc Masana Castrillo is a Researcher at the Institute of Computer Graphics and Vision within Graz University of Technology (College of Engineering). Holding a PhD in Computer Vision (cum laude) from Universitat Autònoma de Barcelona (2020), he specializes in Deep Learning , Continual Learning , and Neural Network Compression . His work addresses catastrophic forgetting in sequential tasks, out-of-distribution detection, and domain adaptation. PhD Thesis: "Lifelong Learning of Neural Networks: Detecting Novelty and Adapting to New Domains without Forgetting" MSc in Computer Vision (with Honours, 2015) BSc in Mathematics and Computer Science (2014) His research spans continual learning frameworks , feature disentanglement , and multimodal translation . Publications in top-tier venues like TPAMI , BMVC , and ICCV highlight his contributions. He co-developed Avalanche , an open-source PyTorch-based library for reproducible continual learning research. Scientific recognition includes the Best Master Thesis Project at UAB (2015) and the Business Track Award at Accenture Datathon (2016). His email addresses are mmasana@tugraz.at and marc.masana@icg.tugraz.at . He has reviewed for journals like TPAMI and conferences including CVPR and ICCV .

• Artificial Intelligence
• Cybersecurity
• Computer Science
• +۳ مورد دیگر

Michael Morak is a Professor at the Department of Artificial Intelligence and Cybersecurity, Alpen-Adria-Universität Klagenfurt, affiliated with the Faculty of Technical Sciences. He holds the titles Privatdozent, Diplom-Ingenieur, and Doctor. His research focuses on artificial intelligence, cybersecurity, and computer science, with notable contributions in logic programming, answer set programming, and algorithmic methods. He has led and contributed to multiple research projects funded by entities like the Austrian Research Promotion Agency (FFG) and the Austrian Agency for International Cooperation in Education (OeAD), addressing topics such as multi-agent systems, radar simulation, and educational technology. His work spans theoretical advancements, including reversibility in planning and dynamic programming, as well as practical applications like interactive SQL learning tools (aDBenture). He collaborates with industry partners, including Infineon Technologies, and has published extensively in top-tier conferences and journals. Morak’s teaching emphasizes innovative methods in computer science education, leveraging game-based learning and interactive platforms to enhance student engagement. Key areas of research include formal methods in AI, algorithmic complexity, and the integration of logic programming with real-world systems. His projects often bridge academia and industry, aiming to solve complex challenges in cybersecurity, robotics, and educational innovation.

Lin Linمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Machine Learning
• Blockchain
• +۶ مورد دیگر

Lin Lin is a Senior Lecturer in the Department of Informatics at New Jersey Institute of Technology (NJIT). Her work bridges artificial intelligence, blockchain, and intelligent transportation systems, focusing on novel AI applications across domains. Education: Ph.D. Lin's research spans Artificial Intelligence , Machine Learning , and Blockchain , with notable contributions to traffic signal control, watermarking robustness, and financial modeling. She explores human-AI perception alignment, synthetic data generation for rare events, and deep learning in transportation. Recent publications highlight trends in Generative AI (e.g., RAGIC for stock prediction), Reinforcement Learning in traffic systems (PairUpLight), and GANs for image inpainting. Her work integrates domain knowledge into neural architectures, emphasizing practical real-world applications.

• Database Systems
• Query Optimization
• Cardinality Estimation
• +۳ مورد دیگر

Dan Suciu is a Professor at the University of Washington, specializing in database systems and theoretical computer science. His research focuses on query optimization, cardinality estimation, information theory, and the intersection of databases with programming languages and fairness concerns. He has collaborated extensively with researchers like Magdalena Balazinska, Mahmoud Abo Khamis, and Christopher Ré. His work spans foundational database theory, algorithm design, and practical systems. Key areas include worst-case optimal joins, equality saturation for query optimization, and applying information theory to cardinality estimation. Recent projects explore causal reasoning in databases and algorithmic fairness through database repair techniques. Publications highlight advancements in join algorithms, estimation frameworks (e.g., SafeBound, LpBound), and theoretical results in semiring-based query evaluation. His work bridges theory and practice, influencing both academic research and industrial systems. Notable contributions include the Seattle and Cambridge reports on database research, outlining field priorities. His systems like Mosaic and Themis address open-world data and approximate query processing.

• Semantic Web
• Linked Data
• RDF/S Provenance
• +۴ مورد دیگر

Irini Fundulaki is a prominent researcher in the Semantic Web and Linked Data domains. Her work focuses on data provenance, access control, and benchmarking for RDF systems. She has collaborated extensively with institutions across Europe and contributed to annual Ontology Alignment Evaluation Initiatives. Research Interests: Dr. Fundulaki's research spans Provenance management in RDF/S datasets Usage control policies via reification Ontology alignment and semantic interoperability Benchmarking tools for linked data systems XML access control frameworks Publication Trends show sustained contributions to semantic data management, with recent works on SPARQL provenance (2024), Geo-Spatial link discovery (2023), and precision medicine ecosystems (2020).

• Databases and Algorithms
• Data Integration
• Natural Language Processing
• +۳ مورد دیگر

Professor Elzbieta Pustulka is a faculty member at FHNW University's School of Business, affiliated with the Institute for Business Informatics. Her research centers on databases, NLP, and AI-driven business process optimization. Research explores database pedagogy through gamification (SQL Scrolls), NoSQL implementations for ERPs, and automated information extraction techniques. Recent work emphasizes CI/CD practices in database development and educational game design for programming concepts. She supervises graduate students in projects spanning database indexing, logistics simulations, and AI-driven reporting systems. No scientific awards are noted.

• Temporal Databases
• Query Languages
• Embedded Control Systems
• +۴ مورد دیگر

David Toman is an Assistant (later Associate) Professor in the Department of Computer Science at the University of Waterloo, part of the Faculty of Mathematics. His research focuses on temporal databases, query languages, embedded control systems, semi-structured data (XML), finite model theory, and programming language implementation. He holds a PhD from Kansas State University (1996) and an MS (MGr.) from Masaryk University (1992). Toman has held roles including Visiting Professor at BRICS, Aarhus University, and postdoctoral fellowships at the University of Toronto. His work includes over 40 refereed publications and contributions to projects funded by CITO, CFI, and NSERC. Awards include the NSERC/NATO Postdoctoral Fellowship and multiple summer school fellowships. Education: PhD in Computer Science, Kansas State University (1996) MS (MGr.) in Computer Science, Masaryk University (1992) Research Interests: Temporal databases and query languages Query processing in embedded control systems XML and semi-structured data management Finite model theory and formal methods Programming language implementation Grants & Awards: CITO Project: Text Indexing for Data Warehouses (CDN$143,000) CFI/OIT: Software Technology for Embedded Control Programs (CDN$705,000) NSERC Individual Research Grant (CDN$84,000) Key Contributions: Developed temporal extensions of SQL and query optimization techniques Contributed to description logics and duplicate elimination in databases Published widely in venues like ACM TODS, IEEE TKDE, and EDBT

Axel Polleresمشاهده پروفایل

استاد

• Semantic Web
• Ontology Languages
• Web Databases
• +۷ مورد دیگر

Axel Polleres is a full professor at the Vienna University of Economics and Business (WU Wien), leading the Department of Information Systems and Operations Management and heading the Data Management group within the Institute for Data, Process and Knowledge Management. He specializes in Semantic Web technologies, knowledge representation, and open data. His work includes contributions to SPARQL, RDF, and W3C standards. Education: PhD and Habilitation in Computer Science (TU Wien) MSc in Computer Science (TU Wien) Research Interests: Semantic Web, Ontology Languages, Linked Data Nonmonotonic Reasoning, Answer Set Programming Query Languages (SPARQL), Data Integration Open Data ecosystems and Quality Assessment Recent Articles Trends: Focusing on knowledge graph evolution, constraint validation (SHACL), and open data pipelines, with applications in city data and semantic web services. His work bridges theoretical foundations with practical implementations. Awards: IEEE 2015 Best Paper Award RR2010 Best Paper Award ISWC2009 In-use Track Best Paper Advising & Labs: Advisor to over 30 PhD/MSc students. Leads the Data Management group at WU, focusing on open data systems and semantic technologies. Involved in projects like FRESH, OMEGA, and W3C standardization efforts.

• Knowledge Representation
• Description Logics
• Computational Logic
• +۳ مورد دیگر

Magdalena Ortiz is a Full Professor and Head of the Knowledge-Based Systems Research Unit at TU Wien, specializing in Knowledge Representation and Reasoning with a focus on Description Logics (DLs). Her work emphasizes integrating DLs with database systems, particularly in query languages and reasoning algorithms. She leads research in semantic technologies, ontology-mediated query answering, and formal methods for data validation (e.g., SHACL). Research interests include expressive query languages, computational complexity of DL reasoning, and applications in graph databases and cloud security. She has extensive experience in EU-funded projects (e.g., FRESH, KtoAPP) and serves editorial roles in AI conferences/journals. Her teaching includes advanced courses on Description Logics, Logic, and Ontology Engineering. Notable contributions include advancements in SHACL validation, Datalog rewritings for ontology-mediated queries, and reasoning with closed predicates. She advises multiple PhD students and collaborates internationally on topics like temporal equilibrium logic and OBDA systems.

• Information Retrieval
• Electronic Publishing
• Design for Children
• +۷ مورد دیگر

Dr. Monica Landoni is an Adjunct Professor at the Faculty of Informatics of the Università della Svizzera italiana (USI) and a senior research fellow at the Dalle Molle Institute for Artificial Intelligence (IDSIA) . She holds a PhD in Information Science from the University of Strathclyde (1997) and a Laurea in Scienze dell’Informazione from the University of Milan. Her research focuses on Information Retrieval , Design for Children , and Accessibility , with emphasis on inclusive technology for people with intellectual disabilities and ethical considerations in AI. She has led SNSF-funded projects like TADAA and BEST, and co-leads the EUGAIN COST Action’s Working Group 1 on gender balance in informatics education. Key research interests include: Human-Computer Interaction (HCI) with vulnerable populations AI-driven creative tools for neurodiverse users Ethical design for children and educational technologies Multilingual interfaces and cross-cultural UX Accessibility in museums and public spaces Her recent work explores: Social robots for museum accessibility Gendered associations in child-technology interactions AR usability for intellectual disability communities Ethical frameworks for emerging technologies Grants & Projects: - Principal investigator: SNSF projects TADAA (2020–2024), BEST (2018–2022) - Co-lead: EUGAIN COST Action’s WG1 (School-to-University Gender Balance) - Previously: JISC EBONI, EU STAMP/PENG, and other international initiatives Labs & Collaborations: IDSIA’s AI ethics and accessibility teams, participatory design partnerships with museums and schools

Ricardo Baeza-Yatesمشاهده پروفایل

استاد

• Algorithms
• Responsible AI
• Web Search and Mining
• +۷ مورد دیگر

Ricardo Baeza-Yates serves as Director of Research at the Institute for Experiential AI at Northeastern University's Silicon Valley campus. He also maintains part-time professor positions at Universitat Pompeu Fabra in Barcelona and Universidad de Chile in Santiago. Previously, he was VP of Research at Yahoo Labs (2006-2016) and CTO of NTENT, a semantic search technology company. His academic career spans over three decades with significant contributions to both industry research and academia. Dr. Baeza-Yates earned his Ph.D. in Computer Science from the University of Waterloo, Canada, in 1989. His academic journey includes professorships at Universidad de Chile (1989-2004), ICREA Professor at Universitat Pompeu Fabra (2004-2005), and ongoing part-time appointments at both institutions since 2004 and 2006 respectively. His research spans algorithms, information retrieval, web search and mining, data science, with increasing emphasis on responsible AI and ethical considerations in technology. He is particularly renowned for his work on bias in search systems, algorithmic fairness, and the societal impacts of AI. His expertise uniquely bridges technical aspects of search and data mining with ethical and societal implications, making him a leading voice in the responsible AI movement globally. His recent scholarly output demonstrates a strong focus on bias detection, fairness metrics, responsible technology development, and the societal impacts of algorithms. The work spans technical machine learning and information retrieval while increasingly addressing ethical and social dimensions across diverse application areas from finance to healthcare to social media. Dr. Baeza-Yates has received numerous prestigious awards throughout his distinguished career: 2019 Corresponding Member of the Brazilian Academy of Sciences 2019 Award Salvà i Campillo to the Person of the Year 2018 National Research Award for applied research and technology transfer 2012 ASIS&T Best Information Science Book Award for Modern Information Retrieval 2011 IEEE Fellow for contributions to computer science development 2009 ACM Fellow for contributions to information retrieval algorithms 2002 Corresponding member Chilean Academy of Sciences As an educator and mentor, Dr. Baeza-Yates has advised numerous students throughout his academic career at multiple institutions. His textbook 'Modern Information Retrieval' has become a standard reference in the field, influencing generations of computer scientists. He has secured significant research funding through his leadership roles at Yahoo Labs and academic grants, demonstrating his ability to bridge theoretical research with practical applications. Dr. Baeza-Yates is actively involved with the DATA Lab at Northeastern University's Khoury College of Computer Sciences and previously founded the Web Science and Social Computing Research Group at Universitat Pompeu Fabra. He serves on multiple high-impact advisory boards including the Global AI Ethics Consortium, Global Partnership on AI, and IADB's fAIr LAC Initiative for Latin America and the Caribbean, reflecting his global influence in shaping responsible AI practices.

Maryam Majediمشاهده پروفایل

استادیار

• Data Privacy
• Embedded Ethics
• Privacy Policies
• +۳ مورد دیگر

Maryam Majedi serves as an Assistant Teaching Professor within the Department of Computer Science at the University of California, Santa Barbara (UCSB), where she spearheads initiatives integrating ethical frameworks into computing education and practice. Her academic appointment emphasizes pedagogical innovation in addressing critical challenges at the intersection of technology, privacy, and societal impact. Her educational credentials include: PhD in Computer Science from the University of Calgary MS in Computer Science from the University of New Brunswick Majedi's research centers on embedded ethics and data privacy, with pioneering work in developing educational modules that operationalize ethical considerations within computer science curricula. She investigates real-world applications including pandemic contact tracing systems, exposure notification technologies, and social networking platforms, creating unified frameworks for privacy policy modeling and visualization. Her scholarship bridges technical implementation with philosophical dimensions of digital ethics, emphasizing actionable pedagogical strategies for cultivating responsible technologists. Analysis of her 2020-2024 publications reveals a cohesive trajectory addressing ethical trade-offs in public health technologies, empirical validation of ethics-integrated curricula, and standardized approaches to privacy policy interpretation. This body of work demonstrates consistent focus on translating theoretical ethics frameworks into practical computing contexts, with increasing emphasis on pandemic-related technologies and policy compliance mechanisms.