جست‌وجوی استاد و پژوهشگر

Aristidou Andreasمشاهده پروفایل

دانشیار

• Human Motion Analysis
• Computer Graphics
• Machine Learning
• +۳ مورد دیگر

Aristidou Andreas is an Associate Professor at the Department of Informatics, University of Cyprus. His academic journey includes a BSc from National and Kapodistrian University of Athens (2005), MSc from King's College London (2006), and a PhD from the University of Cambridge (2011). He has held postdoctoral positions at multiple institutions and served as a visiting professor at the University of Nicosia. His research focuses on human motion analysis, computer graphics, cultural heritage digitization, and geometric algebra applications. He is a senior member of IEEE, ACM, and Eurographics, and serves on editorial boards for journals like The Visual Computer. Research highlights include the FABRIK algorithm (widely used in game engines) and motion capture innovations for cultural heritage preservation. Awards include the DIDAKTOR scholarship, Erasmus Mundus Grant, and NVIDIA GPU grant. He leads projects funded by EU initiatives (e.g., ITN-DCH, SCHEDAR) and collaborates internationally on digital twins, virtual museums, and AI-driven motion synthesis. Key contributions span 3D motion analysis, motion reconstruction from sparse data, and emotion recognition in theater performances. His work bridges computational methods with cultural preservation, biomedical applications, and interactive VR systems.

Sean Bechhoferمشاهده پروفایل

استاد

• Semantic Web
• Ontologies
• Knowledge Representation
• +۳ مورد دیگر

Sean Bechhofer is a Professor in the Department of Computer Science at the University of Manchester, specializing in teaching and scholarship. His research focuses on Semantic Web technologies, ontologies, knowledge representation, and linked data. He has held roles including Discipline Head of Education for Computer Science (2019–2023) and contributed to projects like the Information Management Group and WF4EVER initiative. Education: BSc Mathematics from the University of Bristol (1988), postgraduate work in Category Theory at the University of Manchester. Research interests include ontology engineering, semantic web languages, and workflow preservation. He co-developed the OWL API and contributed to standards like SKOS and the Research Object Model. Teaching responsibilities include courses on Operating Systems, Computational Thinking, and Algorithms. Key projects include the SCAPE preservation framework and myExperiment workflow repository. His work aligns with UN Sustainable Development Goals through contributions to Digital Futures and data science initiatives.

• Children's Literature
• Intertextuality
• Image Analysis
• +۴ مورد دیگر

Eléonore HAMAIDE-JAGER is a Senior Lecturer in French Literature at the School of Letters and Arts , Université d’Artois , since 2010. Her academic work bridges children’s literature and Shoah representation , with a focus on intertextuality , visual analysis , and Oulipo influences in contemporary texts. Research Interests: Intertextual and intericonic dynamics in picture books Shoah and war narratives for youth audiences Oulipo constraints in children’s literature Transfictional structures and digital adaptations Cartographic and spatial representations in youth media Genre hybridity and pedagogical implications Her publications emphasize photographic imagiers , pop-up temporality , and ethical storytelling about historical trauma. She co-edits the Strenae journal and contributes to editorial committees for Cahiers Georges Perec and Cahiers Robinson . She has organized international symposia on documentary youth literature and children's book mediation , serving as a scientific expert in European research programs.

Ivan Chorbevمشاهده پروفایل

استادیار

• Combinatorial optimization
• Heuristic algorithms
• Constraint programming
• +۵ مورد دیگر

Ivan Chorbev, Ph.D. is an Assistant Professor at the Institute for Computer Science and Engineering , Faculty of Electrical Engineering and Information Technologies (FEIT), Ss. Cyril and Methodius University in Skopje, North Macedonia. Since 2009 he has taught courses ranging from Structured Programming to Computer Animation and consulted on numerous EU and national ICT projects. Education B.Sc., Faculty of Electrical Engineering, Skopje, 2004 M.Sc., Faculty of Electrical Engineering, Skopje, 2006 Ph.D., Faculty of Electrical Engineering and Information Technologies, Skopje, 2009 Research Interests His work integrates combinatorial optimization and machine learning to solve complex real-world problems. Core themes include designing heuristic algorithms and constraint programming models for scheduling, resource allocation and telemedicine systems, developing medical expert systems that leverage knowledge extraction and predictive modeling, and creating web-based platforms for e-health, smart living and educational services. Publication Trends Over 70 peer-reviewed works (2005-2014) reveal a clear trajectory from foundational optimization and constraint-solving research toward interdisciplinary applications in telemedicine , social media analytics , and assistive technologies . A notable 2011-2014 surge focuses on cloud-supported e-health systems, 3-D printing for assistive devices, and mining social media for epidemiological insights. Scientific Awards Golden engineering ring – awarded by the Organization of Engineers of Macedonia for best student of his generation. Projects & Funding Risk Assessment for Customs in Western Balkans – FP6 COST IC0602 Algorithmic Decision Theory – management committee member (FP6) COST IC1002 MUMIA – management committee member (FP7) E-HFISN – e-Health applications using folksonomy & social networks (FP7) TEMPUS – Innovation and Knowledge Management toward eStudent Information System Laboratory & Team He conducts research within the Institute for Computer Science and Engineering laboratories, supervising graduate projects in optimization, medical informatics and smart environments.

Haohan Wangمشاهده پروفایل

استادیار

• Trustworthy Machine Learning
• Computational Biology
• Healthcare Applications
• +۵ مورد دیگر

Haohan Wang is an Assistant Professor at the University of Illinois Urbana-Champaign's School of Information Sciences, with affiliations to the Carl R. Woese Institute for Genomic Biology and the National Center for Supercomputing Applications. His research focuses on developing trustworthy machine learning methods for computational biology and healthcare applications , emphasizing robustness , causality , and interpretability in vision-based models. Recent research trends in his work include: Large Language Model interactions with biomedical challenges (GenoAgent, GenoTex) Adversarial security in language and vision models (Guard, Jailbreakzoo) Genomic data analysis through robust machine learning frameworks (Precision Lasso, Kernel Mixed Models) Interactive toolkits like Robustar for data annotation and model training Scientific awards include recognition as Baidu's Top 50 AI+X Rising Young Scholars (2022), Best Paper Honorable Mention at WSDM 2023, and Broad Institute's Next Generation status (2019). Current projects explore AI-made scientists for biomedical discovery and Robustar development for GUI-based robust vision learning.

Philippe Rigauxمشاهده پروفایل

استاد

• Music Information Retrieval
• Database Systems
• Spatial Databases
• +۶ مورد دیگر

Philippe Rigaux is a Professor at the Conservatoire national des arts et métiers (CNAM) in Paris, France, where he conducts research at the CÉDRIC laboratory (Centre d'études et de recherche en informatique et communications). His academic career spans over 25 years with continuous publication output from 1995 through 2024, demonstrating sustained research activity in computer science with a specialized focus on music information retrieval and database systems. Rigaux's research interests center on the intersection of music and computer science, particularly in music score processing, representation, and querying. His work explores graph-based approaches to music representation, topological querying of music scores, and quality assessment in digital music libraries. He has made significant contributions to the development of tools and frameworks for music information retrieval, including the GioQoso quality assessment tool and the FACETS exploration system for large symbolic music collections. His research often bridges theoretical database concepts with practical music applications, focusing on scalable solutions for music content search and pattern matching. Analysis of his recent publications (2018-2024) reveals a consistent research trajectory focused on improving music information systems through innovative database techniques, graph theory applications, and quality assessment methodologies. His work shows increasing emphasis on multimodal music sources, collaborative music digitization, and advanced representation techniques for rhythm and structure. Rigaux frequently collaborates with researchers across Europe, particularly on projects related to digital music libraries and music information systems. Rigaux has contributed to major projects including NEUMA (a collaborative digital score library), CollabScore (integrating optical recognition with multimodal music sources), and GioQoso (a quality assessment tool for music notation). His research has been published in prestigious venues including Data and Knowledge Engineering, International Journal on Digital Libraries, and proceedings of the International Society for Music Information Retrieval (ISMIR).

• Computer Vision
• Multimedia Systems
• Machine Learning Applications
• +۷ مورد دیگر

Timothy K. Shih is an active academic researcher with over 30 years of scholarly contributions, evidenced by his extensive publication record from 1991 through 2025. With more than 380 publications spanning numerous prestigious venues including IEEE Access, Multimedia Tools and Applications, and Lecture Notes in Computer Science, he maintains a robust research profile with consistent annual output (20+ papers in peak years). His work demonstrates leadership through frequent senior/corresponding author positions and collaborations with numerous researchers across international institutions. Dr. Shih's research interests encompass a diverse range of computer science disciplines with particular emphasis on Computer Vision , Human-Computer Interaction , and AI Applications . His work bridges theoretical advancements with practical implementations in educational technology, accessibility solutions, and multimedia systems. Recent publications reveal a strategic focus on applying deep learning techniques to solve real-world problems in sign language recognition, gesture analysis, and wireless sensing applications. Analysis of his publication trends over the past five years shows increasing specialization in multimodal AI systems, with significant contributions to sign language technology (including Arabic Sign Language recognition), WiFi-based human activity recognition, and music technology applications. His research demonstrates strong interdisciplinary connections between computer vision, machine learning, and human-centered computing, with practical applications spanning educational technology, accessibility solutions, and smart environments. Through his mentorship, Dr. Shih has guided numerous junior researchers who have become frequent collaborators, including Chih-Yang Lin, Hsin-Hung Cho, and Tipajin Thaipisutikul. His research program appears well-funded through consistent publication output across multiple project areas, suggesting successful grant acquisition in computer vision, AI, and educational technology domains. Current work indicates active involvement in cutting-edge research on diffusion models for audio processing, enhanced sign language recognition systems, and novel approaches to WiFi-based human interaction analysis.

• Human-Computer Interaction
• Affective Computing
• Multimodal Interaction
• +۴ مورد دیگر

Overview Gualtiero Volpe is a Professor affiliated with the Department of Informatics at the University of Genoa, Italy. His research focuses on Human-Computer Interaction (HCI), Affective Computing, and Multimodal Interaction, with particular emphasis on analyzing social interactions, embodied cognition, and expressive movement qualities in contexts such as music performance and education. He has collaborated extensively with researchers like Antonio Camurri, contributing to interdisciplinary projects that bridge computer science, cognitive science, and the arts. Research Interests Analysis of human movement and affect through computational methods Design of multimodal interactive systems for education and healthcare Investigation of laughter and social dynamics in human interactions Development of technologies for music performance and collaborative creativity Key Contributions Volpe's work spans over 140 publications in top-tier venues such as IEEE Transactions on Affective Computing, ACM Conference on Human Factors in Computing Systems (CHI), and International Conference on Multimodal Interaction (ICMI). His research has led to innovations in: Automated analysis of movement qualities using machine learning Sonification platforms for exergames and rehabilitation Embodied interaction frameworks for children's education Computational models of group cohesion and synchronization Recent Trends in Publications Recent studies emphasize the integration of cognitive science principles into movement analysis and the application of multimodal systems to address challenges in post-pandemic social interaction (e.g., digital commensality). His work on 'Embodied Multisensory Training' and 'Hybrid Co-Working in Industry 5.0' highlights a growing focus on real-world applications of HCI research. Awards & Grants No specific awards or grants are explicitly mentioned in the provided data, though his prolific publication record and leadership in collaborative projects suggest sustained academic recognition and funding support. Labs & Teams Volpe is part of the EyesWeb XMI research group at the University of Genoa, developing open-source platforms for real-time multimodal interaction analysis. He collaborates with institutions like the University of Trento and Goldsmiths, University of London on projects related to music technology and social robotics.

Yong Zhengمشاهده پروفایل

دانشیار

• Data Science
• Machine Learning
• Artificial Intelligence
• +۷ مورد دیگر

Dr. Yong Zheng is an Associate Professor and tenured faculty member in the Department of Information Technology and Management (ITM) at the College of Computing, Illinois Institute of Technology. He holds a Ph.D. in Computer and Information Sciences from DePaul University. His research focuses on Data Science, AI, Recommender Systems, and Human-Centric Computing. He directs the Center for Decision Making and Optimization (DMO) and co-directs the ITM PhD program. Dr. Zheng’s academic roles include service as General Chair for ACM HT 2025, Track Co-Chair for multiple conferences, and editorial roles at journals like Education and Information Technologies (EAIT) and Frontiers in Big Data. He has received awards such as the Springer Nature Editorial Contribution Award (2025) and NSF grants for conference participation and research. His research spans multi-objective optimization in finance, context-aware recommendations, educational technologies, and FinTech. He has developed open-source libraries like CARSKit, DeepCARSKit, and MOPO-LSI. His work has been published in top venues including ACM RecSys, IUI, and SIGIR. Dr. Zheng teaches courses in Data Science, AI, and Applied Data Analytics. He advises numerous PhD and master’s students, focusing on topics like multi-criteria recommendations and financial systems. His industry collaborations include roles at Pandora Media and Morningstar, Inc.

Simon Coxمشاهده پروفایل

استاد

• Brain and Cognitive Ageing
• Neuroimaging
• Lifecourse Correlates of Brain Structure
• +۳ مورد دیگر

Professor Simon Cox is a leading academic in brain and cognitive ageing at the University of Edinburgh's School of Philosophy, Psychology and Language Sciences. As a Sir Henry Dale Fellow and Director of the Lothian Birth Cohort Studies, he investigates lifecourse determinants of brain structure and cognitive differences using multi-cohort neuroimaging and genomic data. Principal Investigator on Age UK, BBSRC, ESRC, and NIH-funded projects Research focuses on neurodevelopment, epigenetics, and environmental influences on ageing Research Interests span: Brain-cognition relationships across the lifespan Multi-omics approaches to neurodegeneration Environmental and genetic mediators of cognitive decline Neuroimaging methodology development Frailty and multimorbidity in ageing populations Life-course epidemiology of brain health Selected Publications (2023-2025) reveal trends in: Epigenetic biomarkers of brain ageing Genomic structural equation modeling Environmental impacts (air pollution, socioeconomic status) Neuroinflammation and mental health Connectomic analysis of depression Vascular risk and brain structure Scientific Awards : Sir Henry Dale Fellowship National Institute on Aging R01 funding NIH RF1 grant for Alzheimer's research PhD Supervision includes projects on: PRENCOG cohort (preterm birth effects) Wellcome-funded mental health data science Translational neuroscience (15+ students)

Luis Alberto Barron Cedenoمشاهده پروفایل

دانشیار

• Natural Language Processing
• Information Retrieval
• Machine Learning
• +۷ مورد دیگر

Luis Alberto Barron Cedeno is an Associate Professor at the Department of Interpretation and Translation, University of Bologna since 2022, where he previously served as Senior Assistant Professor from 2019-2022. He holds a PhD in Computer Science from Universitat Politècnica de València (2012) and has worked at Qatar Computing Research Institute (2014-2019) and TALP Research Center (ERCIM fellowship, 2012-2014). PhD: Universitat Politècnica de València (2012) MSc: AI (Universitat Politècnica de València, 2009) MSc: Computing Science (UNAM, 2007) BEng: Computing (UNAM, 2004) His research focuses on NLP applications for analyzing text qualities like originality (plagiarism detection) and intent (hate speech, propaganda). Recent work includes persuasion techniques in spam emails , misogyny detection using argumentation theory, and Spanish language varieties analysis. He has published over 100 papers with 20+ in top-tier conferences. Key awards include SemEval 2020 Best Task for propaganda detection and ACL 2020 Best Demo . He serves as Specialty Chief Editor for Frontiers in Artificial Intelligence (NLP) since 2023. His students include PhD candidates Arianna Muti (misogyny detection), Katerina Korre (hate speech), and Paolo Gajo (inceldom analysis). 2020: SemEval Best Task 2020: ACL Best Demo 2012: PhD International Mention 2009: Best MSc Thesis 2007: MSc Cum Laude 2004: BEng Cum Laude He organizes the annual CheckThat! lab at CLEF since 2018 and chaired CLEF 2022. His teaching includes NLP courses, computational linguistics, and game localization for translation students.

• Recommender Systems
• Multimodal Learning
• Music Emotion Recognition
• +۳ مورد دیگر

Marta Moscati works at the Institute of Computational Perception at Johannes Kepler University Linz , focusing on advanced recommendation systems and multimodal learning. Her research spans emotion-based music recommendation, privacy-preserving machine learning, and graph neural networks. Recent work includes: Developing multimodal single-branch architectures for cold-start scenarios Creating preference obfuscation techniques in implicit feedback systems Advancing music emotion recognition with semi-supervised graph networks Contributing to the FAME Challenge for multilingual face-voice association She has published extensively in top AI venues while maintaining technical expertise in both deep learning and theoretical physics , with early work on lepton universality violation. At JKU, she contributes to: Recommendation algorithms development Multimodal representation learning research Musical affective computing applications Privacy-preserving AI frameworks

• Artificial Intelligence
• Machine Learning
• Data Mining
• +۱ مورد دیگر

Farzaneh Etminani is a Senior Lecturer at the School of Information Technology, Halmstad University. Her research focuses on Artificial Intelligence , Machine Learning , and Healthcare Informatics , with specific projects including CAISR Health , Evaluation of deep learning for LBD diagnosis , AIR – Artificially Intelligent use of Registers , and iMedA – Improving Medication Adherence . Her recent work includes explainable AI frameworks, synthetic electronic health records evaluation, and temporal modeling of clinical data. Key collaborations span neuroimaging, chronic disease prediction, and human-centered AI systems. She contributes to interdisciplinary research bridging computer science and clinical applications. Her publications cover topics such as: 3D deep learning for dementia diagnosis Transfer learning in neuroimaging Temporal fidelity in synthetic medical data Graph neural networks for clinical risk prediction Behavior change strategies in digital health interventions

Zachary J. Osterمشاهده پروفایل

دانشیار

• Requirements engineering
• Formal methods
• Preference reasoning
• +۵ مورد دیگر

Zachary J. Oster serves as Associate Professor and Chair of the Department of Computer Science within the College of Letters & Sciences at the University of Wisconsin-Whitewater. His office is located in McGraw 108 (150 Hamilton Green Way, Whitewater, WI 53190) where he can be reached at (+1) 262-472-5006 or osterz@uww.edu. Oster completed his academic journey with a Ph.D. in Computer Science from Iowa State University in August 2013 under advisor Samik Basu, following an M.S. from the same institution in December 2009. His undergraduate education at South Dakota State University yielded dual degrees in May 2007: a B.S. in Computer Science and a B.A. in Music. Dr. Oster's research program focuses on enhancing requirements engineering practices through innovative integration of formal methods and computational techniques. He specializes in modeling and analyzing stakeholder preferences using conditional importance networks (CI-Nets), developing efficient algorithms for identifying preference conflicts, and creating visualization tools for requirement preferences. His work bridges theoretical formal methods with practical requirements engineering challenges, particularly in component-based systems and service composition. He actively collaborates with researchers at Iowa State University including Samik Basu and Ganesh Ram Santhanam. His publication trajectory reveals an evolution from foundational service composition research toward more human-centered requirements engineering approaches. Early work focused on service substitutability and composition algorithms, while recent publications emphasize listening techniques for requirements elicitation and scalable preference analysis. The consistent thread throughout his career is applying formal verification methods to practical software engineering problems, particularly in preference reasoning and requirements analysis. Recipient of the 2017 University Faculty/Staff Academic Advising Award Dr. Oster has demonstrated exceptional commitment to student mentorship, recognized by his 2017 advising award. Since October 2022, he has coordinated UW-Whitewater's cybersecurity programs, overseeing curriculum development and student pathways. His research has received support including a UW-Whitewater Strategic Initiative grant (with Lopamudra Mukherjee as PI) for visualizing requirement preferences. He has mentored undergraduate researchers including Josh Leinberger and Pablo Martinez on visualization projects. While not leading a formally named research lab, Dr. Oster has established productive research collaborations through the Formal Methods & Verification Group at Iowa State University. His work on the UW-Whitewater Software Development Center (noted in 2018-2019 course listings) represents an applied effort to connect classroom learning with industry experience. His research group has focused on practical applications of formal methods to real-world requirements engineering challenges.

Vito Walter Anelliمشاهده پروفایل

استادیار

• Recommender Systems
• Artificial Intelligence
• Machine Learning
• +۷ مورد دیگر

Vito Walter Anelli is an Assistant Professor specializing in the technical and ethical aspects of Recommender Systems. His work focuses on fairness, privacy, adversarial robustness, and regulatory compliance in AI-driven recommendation frameworks. He actively contributes to the development of evaluation methodologies, frameworks for reproducible research, and counterfactual reasoning techniques to assess model fairness. His research spans multiple domains including federated learning for privacy preservation, adversarial attacks on visual and graph-based recommenders, and applications in healthcare such as predicting kidney disease progression. He has organized workshops on Knowledge-Aware Recommender Systems (KaRS) and contributed to conferences like RecSys and Dagstuhl Seminars. Anelli's publications emphasize interdisciplinary approaches, blending computer science with legal and ethical considerations. He has developed frameworks like ELLIOT for rigorous recommender system evaluation and explored the integration of knowledge graphs to enhance recommendation interpretability and user control over data. Key themes in his work include addressing bias in graph collaborative filtering, auditing algorithmic fairness in compliance with regulations, and advancing techniques to protect against adversarial manipulation. His contributions bridge technical innovation with societal impact, particularly in ensuring transparency and accountability in AI systems.