جست‌وجوی استاد و پژوهشگر

• Visual Attention
• Cognitive Psychology
• Psychophysiology
• +۳ مورد دیگر

Anna Schubö is a Professor at the Philipps-Universität Marburg , leading the Cognitive Psychophysiology Group within the Department of General and Biological Psychology (College of Psychology). Her research focuses on the role of attention in visual information processing, examining how humans select visual data from complex environments and how factors like salience, prior knowledge, and intention influence this selection. Using experimental and neurocognitive methods (behavioral measurements, motion tracking, EEG), her work explores attentional control, distractor suppression, and the interplay between action planning and perception. Recent publications analyze algorithmic models of selection history, dual-target visual search trade-offs, semantic categorization effects, and natural scene attentional dynamics. She collaborates with projects like TRR 135 ('Cardinal Mechanisms of Perception') and GRK 2271 ('Breaking Expectations') as part of her research framework. Her team includes doctoral candidates and research associates, though individual student lists are not explicitly provided. No scientific awards are documented in the available text.

• Natural Language Processing
• Machine Learning
• Computational Linguistics
• +۳ مورد دیگر

Susanna Rücker serves as a Researcher at the Institute of Computer Science within Humboldt University of Berlin's Faculty of Mathematics and Natural Sciences, actively contributing to the Machine Learning (J) research group. Her institutional affiliation includes the Rudower Chaussee 25 campus in Berlin-Adlershof with direct contact via susanna.ruecker@hu-berlin.de and office phone 030 2093-41177. Her research program centers on advancing Natural Language Processing through Machine Learning methodologies, with specialized expertise in Entity Disambiguation, Named Entity Recognition, and Multilingual Systems. Rücker's work bridges theoretical innovation and practical resource development, particularly in cross-lingual applications and noise-robust dataset creation for NLP tasks. Analysis of her recent publications reveals a cohesive trajectory toward improving entity resolution systems and multilingual lexicon development. Her 2025 work on dual encoder architectures for entity disambiguation builds upon foundational contributions like the CleanCoNLL dataset (2023) and 91-language emotion lexicons (2020), demonstrating consistent focus on evaluation frameworks and resource quality in computational linguistics. Scientific Awards: No awards documented in available materials. Advising and Grants: Current documentation provides no details regarding doctoral supervision, research grants, or funded projects under her leadership. Laboratory Affiliations: Rücker operates within the Machine Learning (J) group at Humboldt University's Institute of Computer Science, which specializes in cutting-edge algorithm development and NLP system implementation.

John A Greenwoodمشاهده پروفایل

پژوهشگر ارشد

• Visual Perception
• Psychophysics
• Amblyopia Treatment
• +۴ مورد دیگر

Dr. John A Greenwood is a MRC Career Development Fellow at the Department of Experimental Psychology, University College London . His research focuses on the mechanisms of visual perception and clinical disorders of vision , particularly amblyopia. He leads the Eccentric Vision Lab ( eccentricvision.com ), which investigates crowding effects, spatial vision topologies, and cortical processing idiosyncrasies. Key Research Themes: Visual crowding, interocular suppression, orientation selectivity, and neural correlates of perception Methodologies: fMRI adaptation, psychophysical experiments, and computational modeling His work reveals that crowding is a regularization process altering object appearance, and that binocular treatments for amblyopia improve compliance without reducing suppression. He has published extensively in Scientific Reports , Journal of Vision , and Investigative Ophthalmology & Visual Science . Scientific Awards: MRC Career Development Fellow

Alexander Bauerمشاهده پروفایل

پژوهشگر

• Deep Learning
• Computer Vision
• Natural Language Processing
• +۲ مورد دیگر

Alexander Bauer is a Postdoctoral Researcher in the Machine Learning Group at Technical University of Berlin, and a member of BASLEARN—a joint lab between BASF and TU Berlin focusing on machine learning applications. His academic background includes a PhD in Computer Science (2017) and a Diploma degree in Computer Science (2012), both from TU Berlin, alongside a B.Sc. in Mathematics (2011) from the same institution. His research interests span Deep Learning , Computer Vision , and Natural Language Processing . In Computer Vision, he specializes in visual anomaly detection , image classification , and semantic segmentation , with industry applications in automotive quality assurance. In NLP, he focuses on transformer architectures and foundation models for tasks like question answering and textual entailment. His earlier work centered on structured prediction , including optimization techniques for MAP inference in graphical models. His publications emphasize algorithmic efficiency and practical applications, with recent work exploring self-supervised learning and model interpretability. Bauer has contributed to both theoretical advances (e.g., exact inference algorithms) and applied solutions (e.g., anomaly detection in manufacturing). He collaborates with industry partners like BASF through BASLEARN, bridging academic research and industrial challenges. His technical expertise spans neural network design, optimization frameworks, and interdisciplinary problem-solving in vision and language domains.

• Wireless Charging Networks
• Mobile Computing
• Edge Computing
• +۶ مورد دیگر

Haipeng Dai is a Professor at Nanjing University, affiliated with the State Key Laboratory for Novel Software Technology and also associated with Tianjin University's School of Computer Science and Technology. His research spans multiple areas of computer science with a strong focus on wireless systems and mobile computing. Dr. Dai's research interests primarily center on wireless charging networks, mobile computing, edge computing, UAV systems, sensor networks, and data management. His work demonstrates a strong theoretical foundation combined with practical applications, particularly in the areas of wireless power transfer and mobile sensing technologies. He has made significant contributions to understanding wireless charger networks, developing novel techniques for acoustic sensing, and optimizing resource allocation in edge computing environments. His research often bridges the gap between theoretical models and real-world implementations, with many papers published in top-tier conferences and journals. Analysis of Dr. Dai's recent publications reveals a strong trend toward interdisciplinary research combining wireless power transfer with mobile computing and sensing applications. His work shows increasing focus on practical implementations of theoretical concepts, particularly in the areas of wireless charging infrastructure, acoustic sensing for health monitoring, and optimization of UAV-based systems. The research demonstrates a clear progression from fundamental wireless charging concepts to more complex integrated systems involving multiple technologies. Dr. Dai has collaborated extensively with researchers including Guihai Chen (129 joint publications), Jiaqi Zheng (47 papers), Chao Dong (36 papers), and Rong Gu (35 papers), indicating strong research group leadership and collaborative networks across institutions. His work has significant implications for the development of next-generation wireless systems, particularly in the areas of energy-efficient mobile computing, contactless health monitoring, and intelligent resource allocation in distributed computing environments. The research portfolio demonstrates both depth in specific technical areas and breadth across multiple related domains within computer science and networking.

• Visual Analytics
• Data Visualization
• Machine Learning
• +۳ مورد دیگر

Cagatay Turkay is a Professor in the Department of Computer Science at the University of Warwick, UK. Previously affiliated with City University London, his research focuses on visual analytics, data visualization, and integrating machine learning techniques into interactive systems. He has contributed to advancements in dashboard design, uncertainty quantification in AI, and healthcare applications. His work emphasizes bridging computational methods with human-centric interfaces to enhance decision-making in fields like epidemiology, cybersecurity, and finance. Key roles: Organizer of EuroVis workshops on Visual Analytics, contributor to NFDI4DataScience infrastructure projects. Research interests include: Human-Computer Interaction, Explainable AI, and FAIR data principles. His publications span journals like IEEE Transactions on Visualization and Computer Graphics and conferences such as AAAI and CHI. He has pioneered frameworks for visualizing complex data patterns, including TransforLearn for transformer models and LEVA leveraging large language models.

Annabell Halfmannمشاهده پروفایل

پژوهشگر

• Media Use and Effects
• Digital Well-being
• Self-control in Media Consumption
• +۳ مورد دیگر

Dr. Annabell Halfmann is an academic researcher at the University of Mannheim’s Institute for Media and Communication Studies, affiliated with Prof. Teresa Naab’s chair. She holds a PhD from Prof. Peter Vorderer’s research group, focusing on self-regulation in mobile communication. Her work bridges communication theory, quantitative methods, and digital well-being. She teaches BA/MA seminars on communication theories and experimental research designs, and manages course approval processes. Her research examines media selection, effects, and self-control challenges in mobile media use. Key themes include social norms governing smartphone behavior, guilt associated with digital communication, and entertainment media’s psychological impact. She has developed frameworks like the IM³UNE model explaining mobile media’s well-being effects. Notable contributions include analyzing maternal smartphone guilt (2025), messaging-induced emotions (2024), and digital detox metaphors (2022). Her work spans peer-reviewed journals like Mobile Media & Communication and the Annals of the International Communication Association. Awarded the German Academic Scholarship Foundation’s PhD fellowship until 2022, she combines empirical research with practical teaching. Current projects explore digital parenting, task-related media distraction, and salutogenic approaches to media use.

• Magnetic Resonance Imaging
• Multiple Sclerosis
• Neurodegenerative Disorders
• +۱ مورد دیگر

Prof. Dr. Mark Mühlau serves as a Professor and Research Group Leader at the Department of Neurology, School of Medicine, Technical University of Munich (TUM). He holds dual affiliations as a full member of the Graduate School of Systemic Neurosciences (GSN) and regular member of the Munich Center for Neurosciences (MCN). His research centers on voxel-based structural magnetic resonance imaging with primary applications in multiple sclerosis and neurodegenerative disorders . Key methodologies include FLAIR-hyperintense lesion detection and voxel-based morphometry for analyzing gray/white matter interactions. His work bridges clinical neurology with advanced computational neuroimaging techniques to investigate disease progression mechanisms. Publication analysis (2008-2013) reveals consistent focus on MRI innovation for neurological conditions, particularly multiple sclerosis and Huntington's disease. His studies demonstrate how white-matter lesions drive secondary gray-matter atrophy, while developing automated tools for lesion quantification. This trajectory highlights translational research connecting structural brain changes to clinical manifestations. Prof. Mühlau leads a dedicated research group at TUM's Neurological Clinic and Polyclinic (Klinikum rechts der Isar), operating within specialized neuroimaging facilities focused on advancing diagnostic precision for neurodegenerative conditions.

• Medical Imaging
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Jiliu Zhou is an active academic researcher with a focus on medical imaging, artificial intelligence, and biomedical engineering. His work spans topics such as PET image reconstruction, radiotherapy dose prediction, and domain adaptation, often employing advanced deep learning techniques like GANs, Transformers, and diffusion models. Collaborations with experts like Yan Wang, Xi Wu, and Dinggang Shen highlight his interdisciplinary approach. Research interests include Medical Imaging: Developing algorithms for PET and MRI reconstruction. Deep Learning: Applying GANs, Transformers, and diffusion models to medical data. Domain Adaptation: Enhancing robustness in multi-source environments. Image Processing: Innovating segmentation and super-resolution methods. His recent publications demonstrate trends in semi-supervised learning , contrastive strategies , and multi-task frameworks for medical applications. Despite no explicit awards or grants mentioned, his prolific output in top journals and conferences underscores significant contributions to biomedical image analysis.

Benjamin Serfasمشاهده پروفایل

استادیار

• Consumer Behavior
• Impulsive Buying
• Self-Regulation
• +۴ مورد دیگر

Dr. Benjamin Serfas is an Assistant Professor in the Department of Human-centered Computing and Cognitive Science at the Universität Duisburg-Essen. He leads the Economic Psychology research group within the Faculty of Computer Science. His academic career includes roles at the Universität Wien, where he earned a Diplom in Psychology (2012) and a PhD in Natural Sciences (Psychology, 2017). Research Interests: Serfas focuses on consumer behavior, particularly impulsive buying, self-regulation, motivation, attention, implicit processing, and eye-tracking methodologies. His work explores how contextual triggers and arousal influence consumer decisions, with applications in retail environments and behavioral interventions. Education: PhD in Psychology (2017), Universität Wien Affiliations: Department of Human-centered Computing and Cognitive Science Key Research Themes: Attentional biases, consumer psychology in shopping contexts, and strategies to mitigate impulsive behavior Publications highlight his contributions to understanding how arousal and visual attention shape consumer choices, with studies on implicit self-esteem measures and the impact of advertising on children. His recent work (2023–2024) examines ADHD symptoms and social media usage in the context of impulsive behaviors. He has advised numerous projects in Austria and Germany, focusing on applied consumer psychology. His lab integrates eye-tracking technology and behavioral experiments to study decision-making processes in real-world settings.

Jörgen Wolfمشاهده پروفایل

پژوهشگر

• Teaching and learning history in post-migration societies
• Knowledge, competencies and beliefs of prospective history teachers
• Career choice motivation of history teachers
• +۴ مورد دیگر

Dr. Jörgen Wolf serves as a Scientific Assistant at the Department of History Didactics at the University of Osnabrück since August 2024. He completed his PhD in History Didactics in 2021 with a dissertation examining lesson planning knowledge of prospective history teachers. Previously, he worked as a Scientific Assistant at Ruhr-Universität Bochum from 2013-2019 and taught at various secondary schools including Westfalenkolleg and Ottilie-Schoenewald Kolleg. Wolf earned his doctorate (Dr. phil.) in History Didactics in 2021. His academic background includes studies in History, Social and Legal Sciences at Ruhr-Universität Bochum and Universitá degli Studi di Pisa (1996-2003), where he completed his First State Examination with research on Italian colonial and war crimes processing. He completed his teacher training at Friedrich-Albert-Lange-Schule in Solingen (2004-2006). His research focuses on teaching and learning history in post-migration societies , examining the knowledge, competencies and beliefs of prospective history teachers . Key areas include career choice motivation , professional identity development , and the impact of digital tools on history education . His empirical approach combines theoretical frameworks with practical applications for history educators. Wolf's publications reveal a consistent trajectory in history teacher education research, with growing emphasis on digital transformation in recent years. His 2023-2024 work increasingly addresses AI tools for lesson planning, showing adaptation to emerging educational technologies. Collaborative research with scholars like Martin Rothland and Nicola Brauch demonstrates methodological rigor in assessing teacher competence development. Wolf actively supervises Master's students, including recent theses on emotions in historical learning and historical argumentation in political discourse. He teaches courses on historical cultural analysis, digital history education, and contemporary historical understanding. His current research projects include 'Cross the border close the gap,' 'Trotz alledem?' examining empowerment in migration contexts, and 'Digitale Helfer?' investigating AI tools for lesson planning. As a member of the Conference for History Didactics (Association of History Didacticians of Germany), Wolf contributes to the 'Empirical Approaches to History Didactics' working group, bridging research with practical classroom applications through his dual experience in university and secondary education settings.

Daniel Darnstaedtمشاهده پروفایل

پژوهشگر

• Mechanisms of task-order control in dual-task situations
• Training of task-order control
• Multitasking in driving simulations
• +۱ مورد دیگر

M.Sc. Daniel Darnstaedt is a researcher at Martin Luther University Halle-Wittenberg, affiliated with the Faculty of Philosophy I and the Department of Psychology. His work focuses on cognitive control mechanisms in multitasking environments. Research Interests Mechanisms of task-order control in dual-task situations Training of task-order control Multitasking in driving simulations Cognitive modeling Notable Publications 2024: Frontiers in Psychology - Examined equivalence of lab vs. online training for task-order coordination 2022: Zeitschrift für Arbeitswissenschaft - Analyzed expert knowledge representation during industrial robot teach-in Darnstaedt collaborates with Prof. Dr. Torsten Schubert and colleagues on cognitive performance optimization, with applications in both laboratory and real-world environments.

• Cognitive Psychology
• Neuroscience
• Dual-Task Processing
• +۳ مورد دیگر

Dr. Sebastian Kübler is a researcher at the Institute of Psychology, Faculty of Philosophy I, Martin Luther University Halle-Wittenberg. His work focuses on dual-task processing, task-order coordination, and the neural implementation of multitasking mechanisms using non-invasive brain stimulation techniques. His research explores how multitasking demands modulate neural activation patterns, the role of working memory in dual-task situations, and task-order control from an embodied cognition perspective. Collaborations include Marco Steinhauser (KH Eichstätt), Andrea Kiesel (ALU Freiburg), Dietrich Manzey (TU Berlin), Rico Fischer (EMAU Greifswald), Roman Liepelt (DSHS Köln), and Veit Kubik (HU Berlin/SU Stockholm). 2024: Electrophysiological analysis of dual-task order coordination 2024: Memory hypothesis in dual-task improvement 2023: Food stimuli and fasting effects on task switching 2022: Working memory and task-order coordination 2021: EEG correlates of task-order preparation Kübler employs transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) to investigate neural causality in cognitive control. His studies also compare multitasking paradigms and examine motor cortex involvement in memory processes.

Torsten Schubertمشاهده پروفایل

استاد

• Cognitive Psychology
• Neuroscience
• Experimental Psychology
• +۳ مورد دیگر

Prof. Dr. Torsten Schubert is a full professor and chair holder at the Martin-Luther-University Halle-Wittenberg , Department of Psychology (Faculty of Philosophy I), and Managing Director of the Center for Media-Enhanced Learning and Teaching (LLZ) . He has held academic positions at prestigious institutions including Humboldt University Berlin and Ludwig-Maximilians-University Munich. Education: Diploma in Psychology (St. Petersburg, 1987), PhD (Berlin, 1994), Habilitation (Berlin, 2005) His research focuses on executive control, working memory, attention , and non-conscious information processing . He explores these through fMRI and functional neuroanatomy, particularly in dual-task situations and age-related cognitive changes. Recent work examines how action video gaming and working memory training influence cognitive control mechanisms. His publications span topics in cognitive neuroscience , experimental psychology , and neuropsychology , with a strong emphasis on neural plasticity, executive function training, and attention dynamics in aging populations. PhD Advisees : Current: Leif Langsdorf, Daniel Darnstaedt, Teresa Schurer, Antonia Reindl Former: Andre Szameitat, Grit Hein, Rico Fischer, Roman Liepelt, Christine Stelzel, Claudia Preuschhof, Yiquan Shi, Tilo Strobach, Elisabeth Hendrich, Tiina Salminen, Alexander Soutschek, Luke Tudge, Sebastian Kübler

Jörg D. Jescheniakمشاهده پروفایل

استاد

• Cognitive Psychology
• Psycholinguistics
• Speech Production
• +۳ مورد دیگر

Professor Jörg D. Jescheniak is a Cognitive Psychology professor at the University of Leipzig, holding his position since 2003. He directs the Wilhelm Wundt Institute for Psychology (2010-2024) and serves on the Faculty Council and multiple university committees. His academic journey includes doctoral studies at the Max Planck Institute for Psycholinguistics and postdoctoral work at the Center for Cognitive Sciences in Leipzig. 1990: Diplom (Psychology), Ruhr University Bochum 1994: Ph.D. (Psychology), University of Nijmegen 2000: Habilitation (Psychology), University of Potsdam His research focuses on cognitive mechanisms underlying speech production, lexical access, and semantic-phonological processing. He employs experimental paradigms like picture-word interference tasks and dual-task experiments to investigate competitive lexical selection, grammatical planning, and cross-modal integration in language production. His work bridges cognitive psychology with neuroscience through ERP methodologies. Recent publications demonstrate consistent contributions to understanding semantic interference effects, phonological encoding dynamics, and developmental differences in speech planning. His research shows particular interest in how cognitive load impacts grammatical advance planning and how object-related sounds influence picture naming processes. Heisenberg Fellowship (DFG, 2001-2003) Habilitation Fellowship (DFG, 1999-2000) As an academic leader, he serves as director of the Wilhelm Wundt Institute for Psychology and chairs multiple university committees. His current DFG-funded research explores incremental learning in word production through picture-word interference experiments. He actively reviews for major journals including Journal of Experimental Psychology and Cognition , and maintains memberships in the Psychonomic Society and European Society for Cognitive Psychology.