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• Artificial Intelligence
• Systems Engineering
• Cyber-Physical Production Systems
• +5 more

Dr. Saber Darmoul is an Associate Professor specializing in Systems Engineering and Multidisciplinary Design. His research bridges artificial intelligence with industrial applications, focusing on cyber-physical production systems, operational resilience, and smart transportation. He actively explores knowledge representation, reinforcement learning, and agent-based modeling to address complex system challenges. Key Research Interests: Operational resilience, AI in manufacturing, multi-agent systems, smart mobility Technical Expertise: Ontology modeling, simulation platforms, immune-inspired control architectures His recent publications (2025-2019) demonstrate a consistent focus on integrating artificial immune systems into control architectures for transportation and manufacturing. Notable trends include: Development of knowledge-based systems for dynamic reconfiguration Application of multi-criteria decision frameworks in production environments Advancing predictive maintenance strategies through distributed systems Exploring 6G system-of-systems engineering While no explicit awards or student advisement information appears in available records, his 15 most recent publications reflect sustained academic productivity and evolving focus from foundational control systems (2017-2019) to advanced applications in Industry 4.0 (2020-2025).

Sybil DerribleView profile

Professor

• Urban Infrastructure Systems
• Smart Cities
• Sustainable Cities
• +5 more

Sybil Derrible is a Professor of Urban Engineering at the University of Illinois Chicago's College of Engineering, with dual appointments as a Research Professor at the Institute for Environmental Science and Policy and a Courtesy Professor in the Department of Computer Science. He directs the Complex and Sustainable Urban Networks (CSUN) Laboratory, focusing on integrated urban infrastructure systems. His research spans urban infrastructure as interconnected systems, including transportation, water, energy, and waste management. Derrible applies complexity science, urban metabolism, and data science to develop sustainable and resilient urban solutions. His work emphasizes environmental justice, smart city technologies, and infrastructure system interdependencies. Derrible's recent publications reveal strong focus on applying machine learning to urban challenges, with significant work on environmental justice metrics, infrastructure burden forecasting, and pandemic-related mobility shifts. His research increasingly integrates AI with traditional engineering approaches to address complex urban problems. Fellow of American Society of Civil Engineers (ASCE) Lead Author on United Nations Environmental Program Seventh Global Environment Outlook Chair of Critical Transportation Infrastructure Protection Committee at Transportation Research Board NSF CAREER Award recipient As an educator, Derrible advises multiple PhD students through the CSUN Laboratory while maintaining active research collaborations. His editorial roles with Scientific Reports and ASCE Journal of Infrastructure Systems demonstrate his standing in the academic community. His forthcoming book "The Infrastructure Book" aims to make complex urban systems accessible to general audiences.

Fang ZhaoView profile

Associate Professor

• Multimedia Learning
• Cognitive Psychology
• Educational Psychology
• +4 more

Fang Zhao serves as Junior Research Group Leader of the Multimedia group at FernUniversität Hagen's Center of Advanced Technology Assisted Learning and Predictive Analytics (CATALPA) since April 2021. As a cognitive and educational psychologist, she conducts interdisciplinary research on multimedia learning and multitasking within this university-funded research center, collaborating with partners across psychological and educational domains. Her academic credentials include a 2024 Habilitation from FernUniversität Hagen, a Ph.D. in Psychology from University of Koblenz Landau (2012-2015), an M.A. in Linguistics and Translation Studies from Durham University, U.K. (2010-2012), and a B.A. in Linguistics and English Language from Henan University, China (2006-2010). Dr. Zhao's research examines how individuals process multimedia information through text-picture integration, interactive simulations, and video-based instruction, with particular focus on exploration-exploitation dynamics in learning environments. Her sequence learning investigations extend to multitasking scenarios involving basic sequences, timing patterns, and complex hierarchical structures like Origami folding. This work bridges cognitive theory with practical educational technology applications through rigorous experimental methodologies. Recent publication analysis reveals consistent emphasis on optimizing visual representations for data comparison, measuring cognitive load in online learning, and evaluating guidance structures in asynchronous courses. Her research demonstrates that while interactive elements are generally preferred by learners, their educational benefits remain context-dependent with significant individual differences in effectiveness. Leading the Multimedia junior research group at CATALPA, Dr. Zhao directs investigations into how interactive and multimedia components influence learning processes across diverse student populations. The team operates within an interdisciplinary framework that integrates psychological theory with technological innovation to develop predictive analytics for learning enhancement.

Noura Al MoubayedView profile

Associate Professor

• Explainable Machine Learning
• Natural Language Processing
• Optimisation
• +6 more

Dr. Noura Al Moubayed serves as an Associate Professor in the Department of Computer Science at Durham University, specializing in Explainable Machine Learning, Natural Language Processing, and Optimisation for high-dimensional data challenges. Education PhD from Robert Gordon University Post-doctoral positions at University of Glasgow and Durham University Research Focus Her work develops machine learning solutions for healthcare, social signal processing, cyber-security, and Brain-Computer Interfaces, specifically targeting noisy and imbalanced datasets through advanced NLP and optimization techniques. Current projects integrate deep learning with explainability frameworks to enhance real-world applicability. Publication Trends Recent publications (2020-2022) demonstrate consistent focus on improving question answering systems via bilinear pooling and paraphrasing techniques, alongside novel deep learning approaches for probabilistic topic modeling. These works bridge computer vision, NLP, and multimodal learning to address data imbalance challenges across healthcare and social computing domains. Academic Service PeerJ Computer Science Editorial Board Member 335 authorship points and 30 reviewer points on PeerJ platform

Anthony BarnhartView profile

Associate Professor

• Cognitive Psychology
• Attention and Perception
• Magic and Cognition
• +3 more

Anthony "Tony" Barnhart is an Associate Professor of Psychological Science at Carthage College in Kenosha, Wisconsin. He previously served as a Lecturer at Northern Arizona University from August 2013 to May 2015. His academic journey began with a Ph.D. in Cognitive Science from Arizona State University in 2013, where he initially focused on language research before expanding into the cognitive science of magic. Dr. Barnhart's educational background includes: Ph.D. in Cognitive Science from Arizona State University (2013) Dr. Barnhart's research uniquely bridges cognitive psychology and the art of magic. As a cognitive scientist and professional magician with over 30 years of performing experience, he examines how magicians function as informal cognitive scientists with hypotheses about the mind that can be empirically tested. His primary academic work focuses on handwritten word perception, a domain largely ignored by traditional psychologists. He also introduces magical methodologies into laboratory settings to increase the ecological validity of experimental studies on attention and perception. His interdisciplinary approach combines cognitive psychology, neuroscience, and performance arts to explore human perception boundaries. His extensive publication record shows a clear progression from traditional cognitive psychology toward the cognitive science of magic, with seminal works including "The exploitation of Gestalt principles by magicians" (2010), "Blinded by magic: eye-movements reveal the misdirection of attention" (2014), and "Microsaccades reflect the dynamics of misdirected attention in magic" (2019). Recent publications increasingly focus on how experiencing and performing magic affects creativity, positive emotions, and wellbeing. Dr. Barnhart has made significant academic contributions through his editorial work at PeerJ, where he has served as both Editor (4,610 contributions) and Reviewer (155 contributions) across multiple subject areas including Psychiatry and Psychology, Neuroscience, and Human-Computer Interaction. His editorial service demonstrates a commitment to advancing knowledge across disciplines. As both scholar and performer, Dr. Barnhart has developed a distinctive research program examining the cognitive mechanisms underlying magical illusions. His work demonstrates how eye movement research can uncover the mechanisms of magical deception and how magicians' practical knowledge can inform laboratory research. He maintains an active research profile with consistent publication output across multiple journals, showing particular expertise in experimental design, eye-tracking methodology, and the cognitive mechanisms of attention and perception.

• Artificial Intelligence
• Natural Language Processing
• Machine Learning
• +3 more

Marcin Sawiński is a Researcher and Teaching Assistant at the Department of Information Systems within the Institute of Informatics and Quantitative Economics at Poznań University of Economics and Business. With expertise spanning computer and information sciences (75%) and management and quality studies (25%), his work focuses on developing AI tools for addressing misinformation and enhancing fact-checking processes. His primary research interests include: Artificial Intelligence applications for fake news detection Natural Language Processing techniques for misinformation analysis Machine learning approaches to credibility assessment Persuasion techniques detection in social media content Development of robust language models for fact-checking systems Analysis of political narratives during crisis events like pandemics Dr. Sawiński's recent publications (2023-2025) demonstrate a concentrated research trajectory focused on applying transformer-based models to misinformation challenges, particularly in Slavic languages. His work spans multiple dimensions of the fake news problem, from detection of persuasion techniques to cross-lingual transfer learning for check-worthiness assessment. He has been actively involved in international competitions like CheckThat! Lab at CLEF, where his team (OpenFact) has developed innovative approaches to fact-checking challenges, including adversarial text generation to test model robustness. His scientific contributions include 15 publications with over 50 citations, reflecting his growing impact in the field of AI for misinformation detection. His research often involves collaboration with colleagues including Krzysztof Węcel, Witold Abramowicz, and Ewelina Księżniak.

• Anatomy
• Postural Control
• Balance Systems
• +7 more

Enis ULUÇAM is a Professor in the Department of Anatomy at Trakya University Faculty of Medicine, with an academic career spanning from his appointment as Research Assistant Doctor in 1999 through his promotion to full Professor in 2016. His educational background includes High School graduation in 1988, Bachelor's Degree in 1995, and Doctoral Degree in 2003, all from Turkish institutions. Professor ULUÇAM's research interests span multiple interdisciplinary domains with a strong anatomical foundation. His primary focus areas include postural control and balance systems , oxidative stress mechanisms , and the physiological effects of formaldehyde exposure . He has conducted extensive research on naringin pharmacology and its protective effects against ischemia/reperfusion injuries, as well as investigations into endometriosis and gait analysis . His work bridges anatomy with neuroscience, toxicology, pharmacology, and sports medicine, demonstrating a unique interdisciplinary approach that connects structural anatomy with functional physiology. Analysis of his publication record reveals a consistent research trajectory focused on experimental models of physiological stress , particularly using rat models to investigate molecular and systemic responses. His work shows increasing sophistication in methodology, moving from basic anatomical observations to complex investigations of oxidative stress pathways, stem cell therapies, and pharmacological interventions. The recurring themes across his publications include postural stability under various stressors , antioxidant protection mechanisms , and gender-specific physiological responses . His recent work (2023-2025) continues to explore sleep deprivation effects on balance and formaldehyde exposure impacts on cognitive function, demonstrating sustained research productivity. Professor ULUÇAM has maintained extensive collaborative networks across multiple Turkish institutions and has contributed to diverse research areas beyond his primary anatomical expertise. His work on airway management predictors, gait analysis in children, and the anatomical basis of difficult intubation demonstrates the breadth of his scholarly contributions. While specific grant information isn't detailed in the available records, his consistent publication output suggests sustained research funding support throughout his career.

Maria Elisabetta CigogniniView profile

Researcher

• Educational technologies
• Technology Enhanced Learning (TEL)
• Personal Knowledge Management
• +7 more

Maria Elisabetta Cigognini is a Researcher at Indire (Istituto Nazionale di Documentazione, Innovazione e Ricerca Educativa), where she has been working since 2014. Her research focuses on educational technologies and technology-mediated learning processes, with expertise in Technology Enhanced Learning (TEL), Personal Knowledge Management (PKM), and teacher professional development. Her institutional affiliations include: Researcher at Indire since 2014 PhD in Telematics and Information Society from Università degli Studi di Trieste (2006-2009) Project coordinator for MENTEP (Mentoring Technology Enhanced Pedagogy) Researcher for NOP1 National Operational Programme Dr. Cigognini's research examines how technology can enhance educational processes, with particular focus on social networking environments for educational purposes, BYOD implementation in learning contexts, and Personal Learning Environments. She investigates the continuum of teacher professional development from initial education through continuous development, exploring documentation and reflection practices through ePortfolios and Open Digital Badges. Her work on self-regulation strategies in technology-mediated learning environments has revealed that while educators can control external distractions, emotional regulation strategies are used less frequently. Analysis of her recent publications shows growing emphasis on practical applications of educational technology, particularly game-based learning environments like Minecraft for remote laboratory teaching and immersive assessment methods for evaluating teachers' digital competencies. Her research consistently bridges theoretical frameworks with classroom applications, demonstrating how technology-enhanced approaches can directly improve teaching practices. Her scientific contributions include: Development of the MENTEP self-assessment tool for teachers' digital skills Research on Minecraft as a remote laboratory for game-based distance learning Studies on distractions and self-regulation strategies in seamless learning environments Investigations into video production processes for teacher professional development Analysis of educational robotics for active learning in primary education Dr. Cigognini employs mixed-methods research approaches, combining qualitative case studies with quantitative surveys to assess the effectiveness of innovative teaching approaches. Her work on the MineClass project demonstrated that teachers who participated in the experimentation reported continuing to use Minecraft for laboratory teaching even after the project's conclusion, indicating the practical value and sustainability of her research findings.