جست‌وجوی استاد و پژوهشگر

Maja J Matarićمشاهده پروفایل

استاد

• Socially Assistive Robotics
• Human-Robot Interaction
• Assistive Technology
• +۷ مورد دیگر

Maja J Matarić is the Chan Soon-Shiong Chaired and Distinguished Professor of Computer Science at the University of Southern California's Viterbi School of Engineering, with courtesy appointments in Neuroscience and Pediatrics. She serves as founding director of the USC Robotics and Autonomous Systems Center, co-director of the USC Robotics Research Lab, and Principal Scientist at Google DeepMind. Previously, she held leadership roles as USC's interim Vice President of Research (2020-2021) and Vice Dean for Research (2006-2019). Her educational background includes: PhD in Computer Science and Artificial Intelligence from MIT (1994) MS in Computer Science from MIT (1990) BS in Computer Science from University of Kansas (1987) Matarić pioneers Socially Assistive Robotics (SAR) , a field her lab named, focusing on human-robot interaction that provides assistance through social rather than physical support. Her research targets critical health and wellness challenges including post-stroke rehabilitation, autism spectrum disorder therapy, cognitive exercises for Alzheimer's patients, ADHD academic support, and mental health interventions. She develops systems modeling user engagement, personality, and motivation, with extensive real-world deployments in schools, rehabilitation centers, and homes. Analysis of her recent publications reveals dominant themes in cognitive health robotics (2025 CHI paper on LLM-powered elder care), pediatric assistive technology (2025 IDC speech therapy review), and adaptive preference modeling (2025 HRI contrastive learning work). Her research consistently bridges machine learning with human-centered design for vulnerable populations. Major scientific recognition includes: ACM Athena Lecturer Award (2024) ACM Eugene L. Lawler Humanitarian Award (2024) ACM Fellow (2020) Presidential Mentoring Award (2011) Multiple society fellowships (AAAS, IEEE, AAAI) As a dedicated mentor, Matarić has championed underrepresented groups through CRA-W, placing numerous women in faculty positions. She leads USC Viterbi's K-12 STEM Outreach Program serving low-income Los Angeles schools and authored The Robotics Prime for student education. Her research has secured significant funding enabling real-world technology transfer, with documented impact in rehabilitation centers and homes through deployable SAR systems. Her Robotics Research Lab at USC drives innovation in embodied AI, with current projects spanning LLM-integrated elder care robots, ADHD academic companions, and autism therapy systems. The lab emphasizes co-design with end-users and rigorous real-world validation across diverse populations.

Guy-Vincent Jourdanمشاهده پروفایل

استاد

• Software Security
• Cybersecurity
• Distributed Systems
• +۶ مورد دیگر

Professor Guy-Vincent Jourdan is affiliated with the School of Electrical Engineering and Computer Science at the University of Ottawa. He holds a Ph.D. from Université de Rennes/INRIA (France, 1995) focusing on distributed systems analysis. Prior to academia, he served as CTO and CEO of Decision Academic Graphics, an Ottawa-based firm. His research interests span software security, cybersecurity (including cybercrime prevention), distributed systems modeling, formal methods, mobile applications, and rich internet applications. Specific technical emphases include phishing detection systems, blockchain fraud analysis, and adversarial machine learning. Professor Jourdan has pioneered tools like D-ForenRIA for reconstructing user interactions in Rich Internet Applications and contributed to cybersecurity frameworks such as HEART for log anomaly detection. His work integrates machine learning techniques with domain-specific challenges in network security and software verification. His publications (2023-2025) reflect advancements in AI-driven vulnerability analysis, blockchain fraud detection, and automated phishing detection systems. Notable projects include SV-TrustEval-C for source code vulnerability analysis and Intellitweet for social media threat detection. While no scientific awards are explicitly listed, his prolific publication record and industry-academia transition highlight sustained contributions to computer science and cybersecurity domains.

Diego Calvaneseمشاهده پروفایل

استاد

• Knowledge Representation and Reasoning
• Virtual Knowledge Graphs
• Ontology-based Data Access and Integration
• +۷ مورد دیگر

Diego Calvanese is a Full Professor in Computer Engineering at the Faculty of Engineering of the Free University of Bozen-Bolzano, Italy. He serves as Spokesperson of the Institute of Computer Science and Artificial Intelligence and Director of the Smart Data Factory technology transfer lab at NOI Techpark. As Coordinator of the Intelligent Integration and Access to Data (In2Data) research group, part of the Research Centre for Knowledge and Data (KRDB), he leads significant research initiatives in knowledge representation and data management. Calvanese's research focuses on virtual knowledge graphs for data access and integration, ontology-based data access, description logics, semantic web technologies, graph data management, and verification of data-aware processes. His work bridges theoretical foundations with practical applications through the Ontop framework, which enables SPARQL query answering over OWL 2 QL ontologies connected to external data sources. His research has substantial practical impact, powering the South Tyrol Open Data Hub Knowledge Graph and supporting numerous European and national research projects. With more than 400 refereed publications and over 39,000 citations (h-index 80), Calvanese's recent work demonstrates continued leadership in virtual knowledge graphs, ontology-based data federation, explainable AI through knowledge representation, and integration of complex data types including 3D city models and raster data. His publications show a clear trajectory from theoretical foundations toward increasingly practical and applied research addressing real-world data integration challenges across multiple domains. ACM Fellow (2019) EurAI Fellow (2015) AAIA Fellow Program Chair of PODS 2015 and KR 2020 General Chair of ESSLLI 2016 Calvanese has secured significant research funding through numerous competitive projects including EU H2020 INFRAEOS Project (INODE), Italian PRIN Project (HOPE), FESR Project (IDEE), and EU FP7 IP Project (Optique), totaling close to 6.4M Euro. As an originator and co-founder of Ontopic, the first spin-off of the Free University of Bozen-Bolzano, he has successfully translated research into commercial applications. He serves as Associate Editor of Artificial Intelligence (AIJ) and has participated in over 200 program committee roles for international conferences. As Director of the Smart Data Factory technology transfer lab and coordinator of the In2Data research group, Calvanese bridges academic research with industry applications, focusing on practical implementations of knowledge graph technologies. His work with the KRDB Research Center has established Bozen-Bolzano as a significant hub for knowledge representation and data management research in Europe.

• Ladybird Ecology
• Invasive Species
• Citizen Science
• +۷ مورد دیگر

Peter Brown is an Associate Professor in the School of Life Sciences at Anglia Ruskin University (ARU), Faculty of Science and Engineering. His research focuses on ladybird ecology, invasive species, and citizen science, with strong collaborations across the UK (especially the UK Centre for Ecology & Hydrology and University of Hull), Europe, and Chile. Education: PhD: The spread of the harlequin ladybird Harmonia axyridis (Coleoptera: Coccinellidae) in Europe and its effects on native ladybirds – Anglia Ruskin University (2010) BSc (Hons) Ecology and Conservation – Anglia Ruskin University (2004) Peter's research interests include ladybird ecology, the impacts of non-native species on native biodiversity, intraguild predation among arthropods using molecular tools, and the use of citizen science in ecological research, particularly through the UK Ladybird Survey and COST Action CA17122. He investigates the global spread and ecological effects of the harlequin ladybird (Harmonia axyridis) and evaluates the benefits and risks of exotic biological control agents. As director of the Citizen Science Research Group and member of the Applied Ecology Research Group, he emphasizes public engagement in science. His recent publications reveal a consistent focus on citizen science, invasive species monitoring, and conservation biology. Themes include volunteer motivations, digital tools for data collection, policy implications of alien species, and recovery strategies for native ladybirds. This body of work demonstrates a strong integration of field ecology, molecular techniques, and public participation. Scientific Awards and Memberships: Fellow, Royal Entomological Society Honorary Fellow, British Naturalists' Association Co-leader, UK Ladybird Survey Editorial board, Nature in Cambridgeshire Member, British Ecological Society Peter supervises postgraduate research in ladybird and insect ecology and welcomes PhD applications. He has secured collaborative research opportunities and leads projects involving citizen science data. He has also contributed to policy and management frameworks for invasive species in Europe. Peter leads the undergraduate module 'Invertebrate Biology' and postgraduate modules in conservation and biodiversity, including field-based learning. He directs the Citizen Science Research Group and is actively involved in public outreach, having appeared on BBC programs such as The One Show, Countryfile Diaries, and The Today Programme, enhancing public understanding of ecology and invasive species.

Catia Pesquitaمشاهده پروفایل

دانشیار

• Semantic Web
• Biomedical Ontologies
• Knowledge Graphs
• +۷ مورد دیگر

Catia Pesquita is an Associate Professor in Computer Science at the Faculty of Sciences of the University of Lisbon , where she is also a Senior Researcher at LASIGE and leads the Health and Biomedical Informatics Research Line . With a multidisciplinary background in Biology and Computer Science, she focuses on Artificial Intelligence and Data Science applications in life and health sciences . Her research spans Semantic Web , Biomedical Ontologies , Knowledge Graphs , and Explainable AI , with significant contributions to ontology matching and semantic similarity . Education: PhD in Computer Science - Bioinformatics (2012) MSc in Bioinformatics (2008) Degree in Cell Biology and Biotechnology (2005) Current Projects: KATY (2021-2024): AI-Empowered Personalized Medicine for cancer treatments. BRAINTEASER (2021-2024): AI for ALS and MS disease progression models. Research Outputs: Developed tools like AgreementMakerLight (AML) , KGsim-benchmark , and the Epidemiology Ontology . Over 133 publications with significant citations (32,909 reads, 3,889 citations). Teaching: Lectures advanced topics in Databases , Data Integration , Bioinformatics , and Big Data . Advocacy: Vice-president of Biodata.pt , promoting biological data valorization in Portugal. Actively involved in initiatives to promote computer science careers to young women .

• Conceptual Modeling
• Ontology
• Domain Modeling
• +۷ مورد دیگر

Tiago Prince Sales is an Assistant Professor in the field of Semantics, Cybersecurity & Services, actively contributing to foundational research in conceptual modeling, ontology, and information systems. His work bridges formal methods with practical applications in digital platforms, cybersecurity, and knowledge representation. Assistant Professor, Semantics, Cybersecurity & Services Active in international research communities (FOIS, ER, BPMDS, RCIS) Key focus: Ontology, Domain Modeling, Interoperability, Digital Platforms Recognized with multiple best paper awards His research centers on the development and application of formal conceptual models using frameworks such as OntoUML and the Unified Foundational Ontology (UFO). He investigates how domain models can enhance system design, improve interoperability, and support risk analysis in complex information systems. His work often integrates empirical insights with theoretical rigor, aiming to address real-world challenges in modeling. The recent publications highlight a strong trend toward ontological engineering in cybersecurity (e.g., phishing attack modeling), digital platform taxonomy, and FAIR data planning. These works demonstrate a consistent focus on creating reusable, semantically rich models that support both human understanding and machine processing across domains. The integration of modeling with data science and security indicates a forward-looking research agenda. Best paper award at FOIS 2023 Best paper award at ER 2022 EMMSAD 2025 Best paper award Tiago Prince Sales actively mentors and collaborates with researchers, though no formal students are listed. He has secured recognition through competitive awards and leads significant research outputs, including datasets and open models. His involvement in organizing top-tier conferences such as FOIS 2024 reflects leadership in the academic community. While specific grants are not listed, his productivity suggests external funding support. He contributes to open science through Zenodo-hosted datasets like the OntoUML Vocabulary and GO-Plan method, and participates in collaborative teams focused on knowledge graphs, FAIRification, and model-driven engineering. His role in organizing the FOIS 2024 conference underscores his integration within leading research networks in formal ontology and conceptual modeling.

• Natural Language Processing
• Text Normalization
• Named Entity Recognition
• +۵ مورد دیگر

Dilara Torunoğlu Selamet serves as a Lecturer in the Department of Computer Engineering within the Faculty of Computer and Informatics at Istanbul Technical University. Holding a PhD, she specializes in Natural Language Processing for Turkish, with research emphases on social media text normalization, named entity recognition, and sentiment analysis. Her academic credentials feature: PhD in Computer Engineering, Istanbul Technical University (awarded circa 2013) Master of Science in Computer and Information Sciences (Non-thesis), Doğuş University (2009-2013) Bachelor of Science in Computer Engineering, Doğuş University (2004-2009) Dilara's scholarship tackles the complexities of Turkish NLP, a language with rich morphology. She has made notable contributions to text normalization for social media platforms, named entity recognition in authentic datasets, and semantic smoothing techniques for sentiment classification. Her work often bridges theoretical NLP with practical applications, as seen in resource-building projects like the ITU Web Treebank and Turkish sign language corpora. Her publication record (2011-2021) demonstrates methodical growth: initial work on text classification (2011) evolved into named entity recognition (2013) and social media normalization (2014, 2017), then expanded to data augmentation (2020-2021) and sign language processing (2020). This trajectory reflects her commitment to advancing Turkish NLP through both foundational research and innovative resource development. While no specific awards are documented, her research impact is evidenced by an h-index of 4 and over 127 citations in Scopus. Available information does not indicate any students supervised or research grants obtained. She is affiliated with Istanbul Technical University's Department of Computer Engineering, but no laboratory or research team memberships are specified in public profiles.

Gergely Kocsisمشاهده پروفایل

دانشیار

• Information spreading
• Agent-based simulations
• Cellular automata
• +۱ مورد دیگر

Dr. Gergely Kocsis serves as an Associate Professor at the University of Debrecen's Faculty of Informatics, Department of Informatics Systems and Networks. His office is located in the Faculty of Informatics building at 4028 Debrecen, Kassai út 26, ground floor, IF13 (Lecturers' room), with contact email kocsis.gergely@inf.unideb.hu and central telephone +36 52 512 900 75013. Dr. Kocsis's research program focuses on: Information spreading phenomena Agent-based and individual-based simulations Cellular automata applications Network structure and dynamics His scholarly output reveals a sophisticated research trajectory evolving from foundational work on cellular automata modeling of social dynamics (2007-2014) to contemporary investigations of transportation networks, VANETs, and AI applications. The 2023-2025 publications demonstrate particular expertise in network extraction methodologies, containerized computing environments, and the application of generative AI to productivity challenges. His work consistently applies computational modeling approaches to understand complex spreading phenomena across diverse network structures. Dr. Kocsis maintains comprehensive scientific profiles across major academic platforms including Google Scholar, ResearchGate, ORCID, Scopus, and Web of Science, demonstrating active participation in the international research community. His departmental colleagues work in complementary areas such as complex networks, embedded systems, and neural networks, suggesting rich collaborative opportunities within the Faculty of Informatics.

Iosif-Viorel Onutمشاهده پروفایل

استاد مدعو

• Cryptography
• Computer and Network Security
• Privacy Technologies
• +۵ مورد دیگر

Iosif-Viorel Onut is an Adjunct Professor at the School of Electrical Engineering and Computer Science, University of Ottawa, and Senior Manager of R&D Strategy at IBM's Center for Advanced Studies. He co-directs the UOttawa Cyber Range, focusing on cybersecurity innovation. Doctor of Philosophy in Computer Science, University of New Brunswick (2008) Master of Science in Computer Science, Technical University of Cluj-Napoca (2003) Bachelor of Engineering in Computer Science, Technical University of Cluj-Napoca (2002) His research spans Cryptography , Computer and Network Security , Privacy Technologies , and Vulnerability Research , with emphasis on phishing detection, malware analysis, and threat intelligence generation. Recent publications highlight trends in semantic-based phishing detection and cryptocurrency scam analysis. Onut has led over 150 research projects involving 35 universities, 90 professors, 360 students, and 330 IBM staff. His work bridges academic research with industry applications in cybersecurity.

Gefei Zhangمشاهده پروفایل

استاد

• Data Science
• Software Engineering
• Model-Driven Software Development
• +۳ مورد دیگر

Prof. Dr. Gefei Zhang is a Professor of Media Informatics at HTW Berlin. He holds a Master’s and PhD from Ludwig-Maximilians-Universität München (LMU). His research focuses on Data Science and Software Engineering, with expertise in aspect-oriented modeling, UML state machines, and model-driven development. He teaches software and data science courses and previously contributed to the Programming and Software Engineering Group (PST) at LMU, now part of the Software and Computational Systems Lab (SoSy). Research interests include aspect-oriented programming, web engineering, and adaptive systems. He has published extensively on topics like UML state machines, software metrics, and HiLA framework applications. Awards include the Best Paper Award at AOM@MoDELS'09. Office hours are by appointment. His work bridges academic research and industry, with past roles in software development for large-scale web applications. Collaborations and grants are part of his ongoing contributions to computer science education and innovation.

• Big data
• Data science
• Data analytics
• +۱۲ مورد دیگر

Paolo Garza is an Associate Professor in the Department of Control and Computer Science (DAUIN) at the Polytechnic University of Turin, where he also serves as Coordinator of the College of Computer, Film and Mechatronics Engineering. He is a member of the DBDM research group and the SmartData@PoliTO laboratory, and actively contributes to academic governance through roles in teaching coordination and PhD program committees. Education: Bachelor’s in Computer Engineering, Polytechnic University of Turin (2001) PhD in Computer and Systems Engineering, Polytechnic University of Turin (2005) His research centers on data science, big data analytics, data mining, and machine learning , with applications in emergency management, real-time communications, Earth observation, and cybersecurity. He has led and participated in numerous national and commercial research projects, including AI4CTI and NODES (PNRR), and has collaborated with industry partners like Cisco Systems. His work bridges theoretical algorithm development and practical deployment in critical systems. The recent publications reflect a strong trend toward multimodal AI, crisis informatics, and intelligent networking . Articles span computer vision for environmental monitoring (e.g., burned area detection, canopy estimation), ML for real-time communication quality, multimodal document understanding, and crisis response systems. His team leverages deep learning, transformers, and vision-language models across diverse domains. Scientific Service: Associate Editor, Knowledge and Information Systems (2024–) Associate Editor, Expert Systems with Applications (2022–) General Co-Chair, IEEE AICT Conferences (2022, 2023) He mentors several PhD students and leads funded research initiatives focused on AI for sustainable industry and cyber threat intelligence. His teaching includes graduate courses on big data processing, distributed architectures, and data science lab methods. He has also directed commercial training programs and research contracts in machine learning and cybersecurity. Research Labs & Teams: DBDM - Database and Data Mining Group (DAUIN) SmartData@PoliTO - Big Data and Data Science Laboratory LAB 5 - Research Laboratory (DAUIN)

• Computer Science
• Artificial Intelligence
• Creativity Support Tools
• +۲ مورد دیگر

Konstantinos Zachos is a Research Fellow and Chief Technology Officer at the Centre for Creativity enabled by AI (Bayes Business School, City, University of London). His work focuses on integrating Artificial Intelligence with Human-Computer Interaction to develop Digital Creativity Tools that enhance innovation across sectors like journalism, manufacturing, social care, and elite sports training. He co-leads the JECT.AI spin-out and the QUEST research project. Expertise : AI for Creativity, Software Engineering, Requirements Engineering, Service Discovery Collaborations : Co-developed tools with Neil Maiden, James Lockerbie, and teams at City, University of London and Miele GmbH His recent publications highlight Generative AI applications in opportunity discovery, with empirical evaluations in newsrooms and manufacturing environments. Key themes include: Creative process modeling Cross-domain AI integration Interactive systems for collaborative innovation Requirements surfacing in evolving systems Konstantinos maintains IEEE membership and actively bridges technical innovation with Human-Centered Design principles.

• Software Engineering
• Web Application Development
• End-User Development
• +۵ مورد دیگر

Christopher Vinod D'Souza is a past researcher focusing on software engineering, web application development, and educational strategies in computing. His work emphasizes end-user development, UI/UX design, and rich internet applications. He has contributed to accessibility control systems, data-intensive web applications, and pedagogical methods for introductory programming courses. His research spans technical domains like automated code generation from mockups, secure access control frameworks, and MVC architecture optimizations. Notably, he has explored modeling languages for UI evolution and strategies to enhance student engagement in multicultural educational settings. Publications include studies on web application scaffolding, visual modeling tools, and architecture patterns for separation of concerns. Despite no listed awards or current institutional affiliation, his work bridges practical software engineering challenges with educational innovation. Christopher has collaborated with institutions on projects involving end-user development tools and strategic approaches to multicultural student needs in higher education.

Diego Garbervetskyمشاهده پروفایل

دانشیار

• Static Analysis
• Dynamic Analysis
• Reverse Engineering
• +۷ مورد دیگر

Diego Garbervetsky is an Associate Professor at the Computer Science Department, School of Sciences, University of Buenos Aires, and a Researcher at ICC/CONICET. He also serves as Director of the Institute of Research in Computer Sciences (ICC). His academic career spans software engineering, programming languages, and formal methods with a focus on program analysis and verification. His research interests include: Static and dynamic program analysis Reverse engineering and compiler optimizations Program understanding and validation Testing and verification of programs featuring rich protocols Automatic symbolic resource analysis (gas consumption, dynamic memory, energy, etc.) Garbervetsky's recent work focuses on smart contract analysis and verification, particularly for Solidity on Ethereum blockchain. His research bridges theoretical program analysis with practical applications in security-critical domains. He has developed several tools including Contractor for behavior validation, JConsume2 for heap memory analysis, and BudaPest for automated software verification. His scientific contributions have been presented at top-tier conferences including ICSE, FSE, ISSTA, and PLDI. Garbervetsky has served on numerous program committees for major software engineering conferences and has advised multiple PhD and undergraduate students through their research.

Diego Garbervetskyمشاهده پروفایل

دانشیار

• Static analysis
• Program verification
• Smart Contract analysis
• +۵ مورد دیگر

Diego Garbervetsky is an Associate Professor at the Computer Science Department, School of Sciences, University of Buenos Aires, and a Researcher at ICC/CONICET. He also serves as Director of the Institute of Research in Computer Sciences (ICC). His academic career spans multiple roles in software engineering research and education. His educational background is not explicitly stated in the provided texts, but his current position reflects extensive academic achievement. Garbervetsky's research focuses on static analysis techniques for Java-like programs and Smart Contracts, automated program verification , program understanding , and validation . His specific interests include program understanding, testing and verification of programs featuring rich protocols, static analysis for program verification, and automatic symbolic resource analysis (gas consumption, dynamic memory, energy, etc.). His research has significant implications for blockchain technology, particularly in smart contract verification. Analysis of his recent publications reveals a strong trend toward smart contract security and verification , with multiple papers on modal abstractions, predicate abstractions, and tools like VeriSol for Solidity smart contracts. His work bridges formal methods with practical software engineering challenges, particularly in the blockchain domain. His scientific contributions include the development of multiple research tools: Contractor: Automated tool for behavior validation Contractor.NET: Visual Studio extension for .NET validation JConsume2: Compositional analysis for Java heap memory Consume.Net: Compositional analysis for .NET heap memory BudaPest: Automated software verifier VInTime: Verification suite for Real Time systems Garbervetsky has supervised numerous PhD students including Daniel Wappner, Javier Godoy, and Alexis Soifer, with former students now working at companies like Microsoft, Veritran, and Dialpad. He has served on program committees for major conferences including ICSE, FSE, ASE, and ISSTA, demonstrating his standing in the software engineering research community. His service includes chairing workshops and serving on artifact evaluation committees, showing his commitment to research quality and reproducibility. He currently teaches Software Engineering 2 at the University of Buenos Aires, having previously taught courses in algorithms, automatic software validation, program analysis, programming paradigms, and computer organization.