جست‌وجوی استاد و پژوهشگر

Valentina Grossiمشاهده پروفایل

مدرس

• Sociology of Work
• Journalism
• Media Studies
• +۷ مورد دیگر

Valentina Grossi is a Lecturer in Sociology at the University of Strasbourg, affiliated with the SAGE laboratory (Sociétés, acteurs, gouvernement en Europe) and the University Center for Journalism Education. Her research focuses on the sociology of journalism, media labor, and digital transformations in news organizations. Position: Lecturer in Sociology Institution: University of Strasbourg Research Unit: SAGE (Sociétés, acteurs, gouvernement en Europe) Professional Affiliation: University Center for Journalism Education Research Axis: State, work, government systems Her research centers on the evolving nature of journalistic work, particularly photojournalism, in the digital era. She investigates how professional autonomy is negotiated amidst increasing reliance on metrics, algorithmic systems, and organizational pressures toward versatility. Drawing on ethnographic methods, she explores the practices, values, and tensions within newsrooms, especially at institutions like Agence France-Presse. Her work engages with broader themes in the sociology of work, organizational behavior, and science and technology studies (STS), often inspired by Bruno Latour’s theoretical contributions. She pays close attention to how visual content is produced, valued, and assembled in contemporary media environments. The analysis of her publications reveals a consistent focus on media labor, professional identity, and the impact of digital technologies. Key trends include the tension between journalistic autonomy and managerial metrics, the reconfiguration of photojournalism through digital tools, and the ethnographic challenges of representing fieldwork. Her work spans multiple languages and engages with international scholarly conversations in sociology and media studies. She has presented her research at numerous academic forums, including seminars at EHESS (Paris), workshops at the University of Lausanne, and conferences of the French Sociological Association. Notable presentations include studies on "connectionist" press companies, the construction of news images, and the interpretation of audience metrics. "How to regulate journalistic activity and the news media?", EHESS, 2025 "Ethnographing Journalistic Practices", University of Lausanne, 2025 "The production of news images: a chain of translations", EHESS, 2024 "Seeing statements, reading images: a Latourian sociology of perception?", 2023 "What does a 'connectionist' press company do to journalistic work?", 2019 Valentina Grossi has contributed to academic discourse through her editorial work and collaborative research. She co-edited the volume Doing sociology at LIER (2023) and has engaged critically with works on algorithmic culture, such as her review of Angèle Christin’s Metrics at Work . She has no listed scientific awards in the provided text. She is actively involved in research networks related to journalism, sociology of arts and culture (RT14), and sociology of media (RT37). Her work is conducted within the SAGE laboratory, a vibrant research environment focused on societal actors and governance in Europe.

Jörn Ostermannمشاهده پروفایل

استاد

• Video Coding
• Computer Vision
• Machine Learning
• +۹ مورد دیگر

Prof. Jörn Ostermann is a Full Professor and Head of the Institut für Informationsverarbeitung at Leibniz Universität Hannover since 2003, with prior roles at AT&T Bell Labs and AT&T Labs-Research. He served as Dean of the Faculty of Electrical Engineering and Computer Science (2011–2013) and member of the Senat (since 2020). His research spans video coding, computer vision, machine learning, 3D modeling, and computer-human interfaces , with applications in SAR imaging, predictive maintenance, children's speech analysis, and cochlear implants. Key projects include Next Generation Video Coding , Conditional Coding for Learned Compression , and GreenAutoML4FAS . Notable trends in his recent publications (2025–2023) include Neural network-based video compression Uncertainty estimation in speech recognition Zero-delay coding for cochlear implants Domain adaptation for aerial image segmentation 3D mesh compression standards Error concealment in VVC coding Scientific recognitions: AT&T Standards Recognition Award (1998) ISO Award (1998) IEEE Fellow (2005) Distinguished Lecturer, IEEE CAS Society (2002/2003) MPEG Convenor (2020–2023) He co-authored a graduate textbook on Video Communications , holds >30 patents, and has led >20 research projects. His work bridges academic research and industrial standardization, particularly in MPEG and IEEE committees.

• Complexity Sciences
• Quantum Technologies
• Artificial Intelligence
• +۹ مورد دیگر

Carlos Pedro Gonçalves is an Associate Professor at the Lusophone University of Humanities and Technologies , where he conducts research in Complexity Sciences , Quantum Technologies , and Artificial Intelligence . He holds a PhD in Management with specialization in Quantitative Methods (Risk Mathematics) and has developed innovative software like the Strategy Analyzer and QNeural , preserved in GitHub's Arctic Code Vault. Research Focus: Quantum machine learning, chaos theory, financial risk modeling, and AI in strategic decision-making. Software Contributions: Open-source tools for quantum computing, cybersecurity, and agent-based simulations in NetLogo. His recent publications examine chaotic patterns in pandemic hospital occupancy and quantum neural network dynamics. He has also contributed to Arctic Code Vault as a GitHub-recognized developer. Scientific Awards: Arctic Code Vault Contributor (GitHub)

Jelle Zuidemaمشاهده پروفایل

دانشیار

• Natural Language Processing
• Explainable AI
• Cognitive Modelling
• +۶ مورد دیگر

Dr. Jelle Zuidema is Associate Professor in Natural Language Processing, Explainable AI and Cognitive Modelling at the Institute for Logic, Language and Computation (ILLC) of the University of Amsterdam, with primary affiliation in the Natural Language Processing research group and secondary affiliation in Language & Music Cognition. He directs the Cognition, Language and Computation lab (CLC-lab) within the Faculty of Science. His research bridges artificial intelligence, cognitive science and linguistics with focus on interpretable deep learning models for text and sound. He pioneered techniques including diagnostic classification (probing), attention rollout, TreeLSTM, and masked language modeling. His work addresses fundamental questions about hierarchical compositionality in language and how neural networks can represent linguistic structure. Analysis of his publication record reveals consistent innovation in neural network interpretability methods, with recent work focusing on bias detection in language models and attention flow quantification. His research trajectory shows evolution from foundational neural parsing work to current emphasis on explainable AI and cognitive plausibility of deep learning models. Dr. Zuidema actively supervises PhD and MSc students while teaching courses including Evolution of Language and Music, Foundations of Neural and Cognitive Modelling, and Interpretability & Explainability in AI. He coordinates the Cognitive Science track in the Brain & Cognitive Sciences master's program. He directs the CLC-lab which pursues both hypothesis-driven methods (diagnostic classifiers, representational similarity analysis) and data-driven methods (layer-wise relevance propagation, contextual decomposition) for neural network interpretation. The lab's InDeep project focuses on interpreting deep learning models for text and sound processing.

Rudy Setionoمشاهده پروفایل

دانشیار

• Data Science
• Business Analytics
• Intelligent Systems
• +۴ مورد دیگر

Rudy Setiono is an Associate Professor and Assistant Dean of Graduate Studies at the School of Computing, National University of Singapore (NUS). He has been with NUS since August 1990, following the completion of his Ph.D. in Computer Science from the University of Wisconsin-Madison. Previously, he served as Vice Dean (Undergraduate Affairs) from November 2001 to July 2005 at the School of Computing. B.Sc. in Computer Science from Eastern Michigan University (1984) M.Sc. in Computer Science from University of Wisconsin-Madison (1986) Ph.D. in Computer Science from University of Wisconsin-Madison (1990) Professor Setiono's research focuses on neural networks, particularly in rule extraction, neural network construction and pruning, and applications in optimization. His work spans theoretical foundations to practical implementations in credit scoring, poverty analysis, and business intelligence. He has made significant contributions to making neural networks more interpretable through rule extraction techniques, bridging the gap between black-box models and transparent decision systems. His recent publications show a strong trend toward practical applications of neural network rule extraction in credit scoring, poverty analysis, and document processing. The research demonstrates consistent evolution from theoretical neural network construction to real-world applications across finance, social sciences, and business analytics, with an emphasis on model interpretability and practical implementation. Senior Member of IEEE Associate Editor of IEEE Transactions on Neural Networks (2000-2005) Professor Setiono has supervised numerous research projects and taught courses including BT4103 Business Analytics Capstone Project, BT4240 Machine Learning for Predictive Data Analytics, IS5152 Data-Driven Decision Making, and IS4240 Business Intelligence Systems. His work has been published in reputable journals including IEEE Transactions on Neural Networks, IEEE Transactions on Data and Knowledge Engineering, and Neurocomputing.

Fawad Raufمشاهده پروفایل

دانشیار

• Nonlinear Adaptive Filters
• Signal Processing
• Chaos Theory
• +۲ مورد دیگر

Fawad Rauf is an Associate Professor of Electrical Engineering with expertise in nonlinear adaptive filters, signal processing, and chaos theory. His research spans adaptive filtering algorithms, neural network architectures, and sustainable energy solutions for developing regions, alongside contributions to engineering curriculum development. Rauf's technical publications focus on nonlinear adaptive filters, chaotic systems modeling, and parallel implementation of adaptive algorithms. Recent work explores sustainable building technologies and energy solutions for mountain communities. His educational research addresses ABET accreditation standards and curriculum improvement methodologies.

David Swansonمشاهده پروفایل

مدرس

• Mathematics Education
• Critical Social Theory
• Cultural Studies
• +۵ مورد دیگر

David Swanson serves as a Lecturer in Education at the Manchester Institute of Education, University of Manchester, specializing in mathematics education and critical social theory. His work intersects educational practice with cultural and political analysis, contributing to UN Sustainable Development Goals related to quality education and reduced inequalities. His research interests focus on mathematics education , particularly teacher development and pedagogical approaches for algebra and multiplicative structures, alongside critical examinations of cultural capital and identity politics within capitalist frameworks. Key areas include lesson study implementation, occupational identity formation, and historical analysis of educational policy. Swanson's publication trends reveal dual emphases: (1) practical educational guides for mathematics teachers addressing classroom implementation challenges, and (2) theoretically rigorous critiques of cultural fields using Marxist and Vygotskian frameworks. His work consistently bridges empirical classroom research with broader sociopolitical analysis. Professional contributions include collaborative research projects like the ICCAMS initiative and editorial work on teacher mentoring frameworks. His network shows significant engagement with UK-based educational researchers and international collaborators in critical pedagogy. Swanson actively supervises doctoral candidates and participates in research teams focused on educational equity. His laboratory work centers on classroom-based action research within Manchester secondary schools, particularly examining mathematics teaching methodologies through both quantitative and critical theoretical lenses.

Masoud Jasbiمشاهده پروفایل

استادیار

• Semantics
• Pragmatics
• Language Acquisition
• +۴ مورد دیگر

Masoud Jasbi is an Assistant Professor in the Department of Linguistics at the University of California, Davis, specializing in experimental and theoretical approaches to natural language semantics and pragmatics. His research focuses on: Semantic and pragmatic interpretation of logical connectives (negation, conjunction, disjunction) Cross-linguistic studies across English, Persian, Mandarin Chinese, Spanish, and Hungarian Language acquisition in child and adult populations Integration of generative linguistics with artificial intelligence Experimental methodologies for testing linguistic hypotheses Recent publications demonstrate consistent emphasis on scalar implicature, context effects, and frequency-dependent processing, with increasing exploration of AI-linguistics intersections. His work bridges formal theory with empirical validation through experimental paradigms, examining how prior beliefs and contextual factors shape linguistic meaning across diverse populations. No scientific awards are documented in available sources. Information regarding student advising, research grants, laboratory facilities, or collaborative teams is not publicly specified in current materials.

Andrea E. Martinمشاهده پروفایل

پژوهشگر

• Language Processing
• Neural Oscillations
• Computational Linguistics
• +۳ مورد دیگر

Andrea E. Martin, PhD, is a researcher at the Max Planck Institute for Empirical Aesthetics specializing in the neural mechanisms of language processing. Her work focuses on how the brain converts perceptual features into hierarchical linguistic representations across multiple timescales. Her research interests center on the intersection of language, cognition, and neural computation. Dr. Martin investigates how hierarchical relationships between words, phrases, and sentences are processed in the brain, with particular attention to oscillatory patterns that resemble human cortical responses to linguistic stimuli. She explores how the brain repurposes neurobiological subroutines to handle the computational demands of language. Dr. Martin's work demonstrates that symbolic-connectionist models of analogy can oscillate while processing sentences, suggesting a formal alignment between representational structure building and cortical oscillations. This research has significant implications for understanding the first principles of linguistic computation in the human brain. Her methodology combines computational modeling with neuroscience approaches to bridge linguistic theory and cortical computation, examining how time can be used to encode hierarchy across layered networks while preserving compositionality.

Ashraf Abdelbarمشاهده پروفایل

استاد

• Artificial Intelligence
• Data Mining
• Neural Networks
• +۴ مورد دیگر

Dr. Ashraf Abdelbar is a Professor in the Department of Mathematics and Computer Science at Brandon University. He holds a BSc in Computer Science from the American University in Cairo (1991), an MSc (1994), and a PhD (1996) in Computer Science from Clemson University, USA. His primary research focuses on artificial intelligence, optimization algorithms, and machine learning, with notable contributions to ant colony optimization, particle swarm optimization, and genetic algorithms. Research Interests: Development of swarm intelligence algorithms for optimization problems (e.g., ant colony optimization, particle swarm optimization). Applications of neural networks in classification, data reduction, and training methodologies. Integration of evolutionary computation techniques with classical optimization methods. Publications Trends: His work spans theoretical algorithm development and practical applications in domains like classification systems, recommendation systems, and combinatorial optimization. Recent trends include hybrid approaches (e.g., combining ant colony optimization with crossover operators) and parameter adaptation strategies for improved algorithm performance. Over 90 publications since 1996 reflect his sustained research output across conferences and journals in computational intelligence, swarm intelligence, and neural networks. Labs/Teams: While no specific lab names are mentioned, collaborations with researchers like Khalid M. Salama, Donald C. Wunsch, and others indicate active participation in interdisciplinary projects focusing on optimization, machine learning, and neural network applications.

Alfred Taudesمشاهده پروفایل

استاد

• Production Management
• Strategic Management in High-Tech Industries
• Real Options
• +۵ مورد دیگر

Prof. Dr. Alfred Taudes is a faculty member at the Vienna University of Economics and Business, affiliated with the Department of Information Processing and Process Management under the Institute for Production Management. His research spans Production Management, Strategic Management in High-Tech Industries, Real Options, Supply Chain Management, and SAP R/3 integration, with significant contributions to Quantitative Models of Learning Organizations. Key research areas: Production/Operations Management, Strategic High-Tech Industry Analysis, Real Options Theory Notable collaborations with researchers like Mild, Natter, and Dorffner Focus on empirical validation of models in marketing, supply chain optimization, and software platform decisions His publications demonstrate interdisciplinary trends combining Management Science , Information Systems , and Machine Learning . Recurring subfields include Neural Network Applications , Real Options Valuation , Consumer Behavior Modeling , and Process Migration in Distributed Systems . While no explicit scientific awards are listed, his work has been disseminated through leading journals and conference proceedings.

David Plautمشاهده پروفایل

استاد

• Computational Neuroscience
• Cognitive Psychology
• Neural Networks
• +۵ مورد دیگر

David Plaut is a Professor at Carnegie Mellon University's Neuroscience Institute and Department of Psychology , with secondary appointments in computational neuroscience. His work combines connectionist modeling with empirical studies to explore cognitive processes in high-level vision, reading, language, and semantics. Holding a Ph.D. in Computer Science (CMU, 1991) and a B.A. in Cognitive Science & Mathematics (Rochester, 1984), Plaut's research spans three decades of computational neuropsychology. Education Ph.D., Computer Science, Carnegie Mellon University (1991) B.A., Cognitive Science & Mathematics, University of Rochester (1984) His research focuses on distributed neural networks and cognitive impairments . Key contributions include modeling semantic over-activation in N400 ERP components, hemispheric lateralization mechanisms, and topographic organization of visual cortex. Recent work examines visual word form networks and face processing through iScience and Imaging Neuroscience publications. Scientific recognition includes the Troland Research Award (2003), Fulbright Scholarship (2000), and NIH FIRST award (1997). Current grants (2022-26: NIH R01EY027018; 2021-25: NSF BCS-2123069) support studies on cortical reorganization and hemispheric specialization. Training initiatives include teaching Introduction to PDP (1994-present) and Cognitive Neuropsychology (2023-present). The Plaut Lab trains graduate students in Neural Computation and Psychology , with postdocs like Kelly Martin (2024-) and Masataka Nakayama (2016-18) now holding academic positions.

Rick Cooperمشاهده پروفایل

استاد

• Cognitive Control
• Executive Functions
• Computational Modeling
• +۴ مورد دیگر

Prof. Rick Cooper is the Executive Dean of the Faculty of Science at Birkbeck, University of London. He holds a Ph.D. (1990, University of Edinburgh) and B.Math (1986, University of Newcastle). His roles include leading Science Central and overseeing academic programs like the MSc in Cognition and Computation. He chairs committees such as the College Working Party on Open Research and served as Executive Editor of Cognitive Science (2015–2020). Research focuses on cognitive control mechanisms, computational modeling of executive functions, and neurological impairments. Key themes include routine sequential behavior, dual-task interference, and hierarchical goal management. He has developed influential models like the Goal Circuit Model for routine action control. Prof. Cooper has received prestigious awards, including Fellow of the Association for Psychological Science and the British Academy Medal (2013). His lab, the Computational Cognitive Neuroscience Lab, explores neural and computational bases of cognition. He has supervised over 15 doctoral students, including recent completions in neurocomputational modeling and semantic cognition. Teaching spans modules like Computational Approaches to Mind and Neuropsychology . His outreach includes public lectures on cognitive science and media commentary on AI and brain-inspired computing.

Jo Nobleمشاهده پروفایل

عضو هیئت علمی

• Information Visualization
• Big Data
• Demography
• +۳ مورد دیگر

Dr. Jo Noble is a Principal Lecturer in the Department of Computing & Games at Teesside University's School of Computing. With over 20 years of affiliation to the School, she actively engages in teaching software development, systems analysis and design, and contributes to external events like Animex and ExpoTees. Her career bridges industry experience and academia, having worked as a senior programmer, systems analyst, and project manager before returning to academia. Education: BSc (Hons) Mathematics, Teesside University (1998) PhD: IS Project Management: An Interpretive View of IS Project Failure in the Stakeholders' Domain (2014) Jo's research focuses on Information Visualization and Big Data , with significant contributions to Attribute-Based Access Control and Agent-Based Modeling . Her work connects computational approaches with demography and explores how data-driven models can mitigate industry project failures. She also engages in consultancy with regional businesses on Big Data and Info Vis initiatives. Her recent publications highlight interdisciplinary trends combining Big Data Applications , Demographic Modeling , and Information Systems . Key collaborations include projects with E. Silverman, J. Bijak, and V. Cao, focusing on artificial population models and data tyranny. Industry Experience: CapGemini Ernst & Young (logistics/finance systems), MDC Technology (mathematical modeling software) Academic Leadership: Co-designed first pathways in Information Visualization and Big Data at the School of Computing Consultancy: Advises regional businesses on innovative Big Data projects Jo leads external events showcasing the School of Computing's work, emphasizing real-world applications of computational methods in education and industry partnerships.

• Wireless Communication
• Cognitive Radio Networks
• Network Protocols
• +۴ مورد دیگر

Urban Bilstrup is a Senior Lecturer at the School of Information Technology, Halmstad University. His professional role focuses on advancing wireless communication technologies and computational intelligence applications. Research Interests: Dr. Bilstrup's work spans wireless network optimization, cognitive radio systems, and predictive modeling using computational intelligence. His research includes solar activity forecasting, cyber conflict analysis, and military communication protocols. Publications: His scholarly output demonstrates expertise in ad hoc networks, dynamic spectrum allocation, and neuro-fuzzy systems for space weather prediction, with a publication history from 2000-2020.