جست‌وجوی استاد و پژوهشگر

Noshaba Cheemaمشاهده پروفایل

پژوهشگر

• Computer Graphics
• Machine Learning
• Computer Vision
• +۴ مورد دیگر

Noshaba Cheema is a Researcher at the German Research Center for Artificial Intelligence (DFKI) and a PhD Candidate at the Max-Planck Institute for Informatics, affiliated with Saarland University. She holds dual roles as a Researcher in the Agents and Simulated Reality Group and as a Work Package Manager for the EU-funded Carousel+ project. Her academic journey includes a Master's degree from Saarland University and the International Max-Planck Research School for Computer Science, and a Bachelor's degree in Media Computer Science from the University of Applied Sciences Bremen. Her research focuses on virtual character animation, motion synthesis, and AI-driven interactive systems, with applications in VR/AR, computer graphics, and human-computer interaction. She has pioneered fatigue modeling for virtual characters using reinforcement learning and explored synthetic data generation for deep learning tasks. Her work bridges computational neuroscience and machine learning, as seen in early projects modeling human visual systems. Noshaba has received significant recognition, including the Telekom Women's STEM Award 2020 (AI category), the Best Poster Award at SCA 2018, and a Max-Planck Fellowship. She actively contributes to conferences as a speaker, panelist, and diversity co-chair at venues like High Performance Graphics. Her teaching spans topics in game development, motion synthesis, and signal processing at Saarland University and Bremen. Her research portfolio includes over 20 publications across top venues like SIGGRAPH Asia, ECCV, and CVPR. She advises Master's theses in graphics, vision, and machine learning, and manages EU Horizon 2020 grants. Noshaba also engages in public outreach, advocating for women in STEM through media features and mentoring roles.

Arjun Chandrasekaranمشاهده پروفایل

پژوهشگر

• Computer Vision
• Natural Language Processing
• Machine Learning
• +۴ مورد دیگر

Arjun Chandrasekaran holds dual roles as a Guest Scientist/Postdoctoral Researcher at the Max Planck Institute for Intelligent Systems (Tübingen, Germany) and Head of AI at CONXAI Technologies (Munich, Germany). His research bridges computer vision, natural language processing, and cognitive science, focusing on multimodal machine learning for understanding human actions, interactions, and behavior in 3D environments. Key areas include human-AI team dynamics, embodied AI, and humor/narrative modeling. Education: PhD in Computer Science (Georgia Tech, advised by Devi Parikh) Postdoc under Michael Black at MPI-IS Research Highlights: Developed the BABEL dataset for 3D human behavior analysis Explored Fermi problems as AI reasoning benchmarks Pioneered studies on humor perception in visual contexts Advocated for explainable AI through human-centric evaluation Publications emphasize interdisciplinary approaches, combining vision-language tasks with cognitive insights. Current work at CONXAI applies AI to transform the Architecture, Engineering, and Construction (AEC) industry through strategic AI solutions and team leadership.

• Machine Learning
• Signal Processing
• Computer Vision
• +۴ مورد دیگر

Yuan Liao is an active researcher with a focus on interdisciplinary areas spanning computer science, electrical engineering, and applied mathematics. His work emphasizes innovative solutions in signal processing, machine learning, robotics, and human mobility studies. Notably, he has contributed to advancements in wearable biomedical devices, remote sensing image analysis, and next-generation wireless communication systems like 6G. Collaborations with institutions like Academia Sinica and co-authors such as Vasilis Friderikos highlight his global academic network. Liao's research often bridges theoretical frameworks with practical applications, addressing challenges in healthcare, transportation, and urban planning. Key contributions include developing novel neural network architectures for tasks like image inpainting and emotion recognition from EEG signals. His work on robotic aerial base stations for mmWave backhauling demonstrates expertise in cutting-edge wireless systems. While specific institutional affiliations are not explicitly stated in the provided data, his prolific publication record across top-tier journals and conferences indicates an established academic role, likely as a researcher or faculty member in a technical discipline.

• Biomedical Informatics
• Machine Learning
• Graph Neural Networks
• +۴ مورد دیگر

Yi-Jia Zhang is a Professor at the School of Computer Science and Technology, Dalian University of Technology. They hold affiliations with multiple institutions, including Zhejiang Sci-Tech University and Jilin University. Their research focuses on biomedical informatics, machine learning, and healthcare applications, with significant contributions to medical knowledge fusion, drug recommendation systems, and multimodal analysis. Over 140 publications since 2011 reflect expertise in areas like graph neural networks, natural language processing, and medical image analysis. Key collaborations include work with Hongfei Lin, Mingyu Lu, and Jian Wang on projects such as drug-repositioning models and radiology report generation frameworks. A notable emphasis is placed on applying AI techniques to solve biomedical challenges, including ICD code classification and sentiment analysis in healthcare contexts. No formal awards are listed, but their extensive publication record underscores academic impact.

Jens Siemonمشاهده پروفایل

استاد

• Vocational Education
• Educational Technology
• Learning Analytics
• +۳ مورد دیگر

Prof. Dr. Jens Siemon is a Professor of Educational Science at the University of Hamburg, specializing in Vocational Education and Media Professions. He holds a W3 professorship in the Department of Vocational Education and Lifelong Learning (EW 3) within the Faculty of Education. His academic journey includes a dual vocational training as a data processing clerk, studies in Business Education at Georg-August-Universität Göttingen (Dr. rer. pol., 2002), and international research collaborations in Spain and Australia. He has served as junior professor and later full professor since 2009. Research focuses include video-based learning analysis, game-based learning, computational thinking in education, and vocational training in the knowledge society. Key projects include the VIRTOOL project on virtual simulation tools and the Modellunternehmen A & S GmbH. He co-leads the EU-funded 'Professional teachers’ actions to promote subject-based learning' (ProfaLe) project and has secured over €6 million in third-party funding. Publications emphasize educational technology, video analysis methodologies, and teacher training. His work on automated classroom behavior analysis involves collaborations with Macquarie University and Fudan University. He supervises doctoral candidates like Anja Augsdörfer (2019) and Katharina Baumann (2015). The Videolabor at Hamburg provides technical support for student research in video analysis. Teaching contributions include courses on vocational informatics and media training. Recognized for integrating digital tools into education, he advocates for teacher competencies in the knowledge society. His research spans over 27 publications, emphasizing innovative pedagogical practices and evidence-based educational strategies.

Andrea Antalمشاهده پروفایل

استاد

• Neuroplasticity
• Non-Invasive Brain Stimulation
• Neurology
• +۳ مورد دیگر

Prof. Andrea Antal is a Professor and Group Leader of the Non-Invasive Brain Stimulation Laboratory at the Department of Neurology, University Medical Center Göttingen. Her work focuses on neuroplasticity and developing neuromodulation techniques like transcranial direct current stimulation (tDCS), alternating current stimulation (tACS), and random noise stimulation (tRNS). She investigates how these methods can treat neurological disorders such as chronic pain, depression, and Parkinson's disease. Education: 1990 – Diploma in Biology, Attila József University of Sciences, Szeged, Hungary 1993 – University Doctor, Attila József University of Sciences, Szeged, Hungary 1998 – PhD, Albert Szent-Györgyi Medical University, Szeged, Hungary 2005 – Habilitation, University of Göttingen, Germany 2010 – Extraordinary Professor, University of Göttingen, Germany Research Interests: Inducing and measuring neuroplasticity via external stimulation Modulating cortical oscillations for therapeutic purposes Applications in aging neuroscience and chronic disease management Publications highlight advancements in neuromodulation techniques, including systematic reviews on combining stimulation with meditation and addressing regulatory challenges in neurotechnology. Her work emphasizes translational applications of neurophysiological discoveries.

Beatrice G. Kuhlmannمشاهده پروفایل

استاد

• Cognitive Aging
• Memory Processes
• Metamemory
• +۳ مورد دیگر

Prof. Beatrice G. Kuhlmann is a Professor of Cognitive Psychology at the University of Mannheim, leading the Chair for Cognitive Psychology and Cognitive Aging. Her research focuses on memory processes across the lifespan, particularly in aging contexts, exploring objective memory performance and subjective metamemory beliefs. She investigates strategies to enhance memory in older adults and studies emotional influences on source memory. Prof. Kuhlmann teaches developmental psychology and experimental psychology, emphasizing lifespan perspectives. Her team includes doctoral students like Hilal Tanyaş and Nikoletta Symeonidou, who have successfully defended their theses on source monitoring and emotional memory. She received the 2022 Early Career Award from the Psychonomic Society for her impactful research since her Ph.D. completion. Prof. Kuhlmann also serves as an Associate Editor for Cognitive Research: Principles and Implications . Key research themes include source monitoring, metamemory, and the interplay between emotion and memory. Her work employs advanced methodologies like multinomial processing tree models and diffusion modeling to dissect memory storage and retrieval processes. Teaching and supervision focus on fostering experimental psychology skills and thesis development in cognitive aging domains.

• Computer Vision
• Machine Learning
• Image Processing
• +۵ مورد دیگر

Dr. Xin Lin is a Professor at the School of Computer Science and Technology, University of Science and Technology of China in Hefei. With an extensive publication record spanning computer vision, machine learning, and artificial intelligence, Dr. Lin leads a research group focused on solving challenging problems in image processing, robotics, and wireless communications. His work bridges theoretical advancements with practical applications across healthcare, autonomous systems, and industrial manufacturing. Dr. Lin's research interests encompass computer vision, machine learning, image processing, and artificial intelligence, with particular expertise in image restoration, 3D object detection, and human pose estimation. His laboratory develops innovative approaches to handle multiple image degradations simultaneously and create lightweight, efficient vision systems suitable for real-world deployment. The research demonstrates strong interdisciplinary connections, applying computer vision techniques to medical imaging, satellite communications, and industrial IoT applications. Analysis of Dr. Lin's recent publications reveals a strong focus on multi-task learning approaches that address multiple image degradation problems simultaneously. His work shows increasing sophistication in handling complex real-world scenarios, from low-light conditions to rain interference, while maintaining computational efficiency. The research trajectory demonstrates a clear path from fundamental image processing techniques to practical applications in autonomous driving, healthcare, and industrial systems. Dr. Lin has received recognition for his contributions to the field through numerous publications in top-tier venues including CVPR, IEEE Transactions, and ACL. His work on image restoration, particularly the Dual Degradation Representation framework, has gained significant attention in the computer vision community. Dr. Lin actively supervises graduate students and collaborates with researchers worldwide. His laboratory works on cutting-edge projects involving digital twins for manufacturing, satellite communications, and medical imaging applications. Current research directions include developing more robust and efficient models for real-world deployment scenarios, with particular attention to resource-constrained environments.

• Cognitive Science
• Developmental Psychology
• Information Search Strategies
• +۳ مورد دیگر

Azzurra Ruggeri is an Assistant Professor of Cognitive and Developmental Psychology at the Technical University of Munich's School of Education and an Assistant Professor in the Department of Cognitive Science at Central European University in Vienna. From 2016-2023, she served as a Max Planck Research Group Leader at the Max Planck Institute for Human Development, where she led the iSearch research group focused on information search and active learning across the lifespan. She is also affiliated with the International Max Planck Research School on the Life Course (LIFE). Her educational background includes dual PhDs in Psychology from Humboldt University of Berlin and in Cognitive Science from University of Siena (both 2012), as well as an MA in Philosophy with focus on Decision Making and Philosophy of Science from University of Pisa (2008). Prior to her current positions, she completed postdoctoral training at both the Max Planck Institute for Human Development and the University of California, Berkeley. Ruggeri's research focuses on how children and adults actively search for information when making decisions, drawing causal inferences, and solving categorization tasks. She investigates how adaptive search strategies are to the structure of tasks and how active information generation impacts learning and understanding. Her work bridges cognitive development, decision science, and educational psychology with strong emphasis on ecological validity. Analysis of her recent publications reveals a consistent focus on children's information search behaviors, particularly how preschoolers and toddlers adapt their exploration to task structures, goals, and information gain. Her research employs both experimental paradigms and computational modeling approaches to understand developmental changes in active learning strategies across the lifespan. John Templeton Foundation Virtual Research Network on the Development of Intellectual Humility ($30,000) Volkswagen Foundation - Artificial Intelligence and the Society of the Future, "Towards a theory of curiosity" (€1,500,000, of which €585,800 to Ruggeri) Innovation funds of Museum für Naturkunde Berlin for "Center for Active Learning in Museums" (€15,500) DFG Focus Program: The active self project "Climbing to yourself" (€350,000) Marie Curie Actions International Outgoing Fellowships ($282,000) Best Early Career Developmental Paper, AIP (Italian Psychological Association) ($1,200) Ruggeri has supervised PhD students including C. De Simone ("Active and ecological learning to navigate the social world") and A. Jones ("Active learning strategies in child- and adulthood: An interdisciplinary perspective"). Her research group has received substantial grant funding supporting work on children's information search strategies, active learning, and the development of curiosity across multiple institutions. Her laboratory work focuses on designing ecologically valid experimental paradigms that capture real-world information search behavior while maintaining experimental control, often using games and interactive tasks to examine exploration behavior across development.

Tobias Staudiglمشاهده پروفایل

استاد

• Memory
• Navigation
• Electrophysiology
• +۳ مورد دیگر

Prof. Dr. Tobias Staudigl serves as a Professor in the Department of Psychology at Ludwig Maximilian University of Munich (LMU), where he leads the Cognitive Neuropsychology research group. He holds dual affiliations as a full member of the Graduate School of Systemic Neurosciences (GSN) and a regular member of the Munich Center for Neurosciences (MCN), focusing on neural mechanisms of human memory and navigation through electrophysiological approaches. His research program investigates how brain oscillations support cognitive processes during sleep and wakefulness, with particular emphasis on thalamic function in spatial cognition and memory consolidation. The lab employs multimodal methodologies including invasive intracranial EEG in epilepsy patients and non-invasive techniques to study theta oscillations, memory encoding dynamics, and eye movement-brain activity interactions. Key experimental paradigms explore neural correlates of navigation, memory reactivation during slow-wave sleep, and thalamocortical contributions to attentional processes. Analysis of Staudigl's publication record reveals consistent contributions to understanding electrophysiological signatures of memory across sleep-wake cycles, with increasing focus on thalamic involvement since 2016. His work bridges cognitive psychology with systems neuroscience through human intracranial recordings, demonstrating how specific brain rhythms organize memory processes in both medial temporal and thalamic structures. Scientific recognition includes: ERC Starting Grant for human intracranial research on thalamic mechanisms Staudigl directs an internationally competitive research program funded by prestigious European grants, with his ERC-funded project enabling rare access to human intracranial data. While the text does not enumerate specific advisees, his GSN and MCN affiliations indicate active supervision of graduate students in systemic neuroscience. Current work explores thalamocortical interactions during memory tasks with implications for neurological disorders affecting spatial cognition. The Cognitive Neuropsychology laboratory operates within LMU's Department of Psychology, maintaining close collaborations with neurosurgical units for intracranial recordings and utilizing advanced EEG/MEG facilities for non-invasive studies. The team's technical expertise spans electrophysiological signal processing, spatial navigation paradigms, and multimodal neuroimaging integration to address fundamental questions about memory systems in the human brain.

Virginia L. Flanaginمشاهده پروفایل

دانشیار

• Cognitive Neuroscience
• Behavioral Neuroscience
• Spatial Navigation
• +۵ مورد دیگر

Virginia L. Flanagin serves as an Associate Professor (außerordentlich) at Ludwig Maximilian University of Munich's Graduate School of Systemic Neurosciences (GSN) and leads a research group at the German Center for Vertigo and Balance Disorders (DSGZ). Her work integrates computational modeling with cognitive neuroscience to investigate spatial navigation and perception mechanisms. Research Focus: Specializing in Behavioral & Cognitive Neuroscience , she examines how sensory-motor information converts into cognitive spatial maps, emphasizing the vestibular system and hippocampus. Her methodology combines functional MRI, virtual reality, and psychophysics to explore sociocultural influences on spatial behavior, with secondary focus on Theoretical Neuroscience applications. Publication Trends: Her 15 publications (2005-2021) reveal progression from basic motion detection (fly studies) to complex human navigation research. Recent work incorporates deep learning (e.g., DeepVOG for eye tracking) and investigates neural plasticity in response to vestibular loss and specialized training like slacklining. Mentorship: She has guided nine students including: Phillip Graeff Eva Fraedrich (co-mentored) Nadine Hummel Magdalena Wutte Josephine Henke Theresa Raiser Christopher Roppelt Judita Huber Uma Navare Her research group likely operates through institutional funding at DSGZ. Research Environment: Based at DSGZ within LMU Klinikum, her team operates in a multidisciplinary hub integrating neurology, otolaryngology, and neuroscience to advance balance disorder research through clinical-basic science collaborations.

Martin Baumannمشاهده پروفایل

استاد

• Human Factors
• Cognitive Psychology
• Human-Machine Interaction
• +۱۲ مورد دیگر

Prof. Dr. Martin Baumann is Chair of Human Factors at Ulm University, a position he has held since February 2014. His research is centered on cognitive and behavioral aspects of human interaction with advanced technological systems, particularly in automated transportation. He leads a research group focused on human-machine systems, with strong affiliations to transportation safety and driver assistance technologies. His research interests include: Cognitive Modeling and empirical studies of human behavior in human-machine systems Attention processes, situational awareness, and cognitive distraction Design and implementation of cooperative driver assistance and automation systems Multimodal interaction and transitions between automated and manual driving modes Diagnostic reasoning and decision-making under uncertainty His scholarly work, accessible via Google Scholar, demonstrates a consistent focus on understanding and enhancing human performance in automated environments. Key trends across his recent publications include modeling driver cognition, evaluating multimodal interfaces, and improving the safety of human-automation handovers in vehicles. His work integrates cognitive psychology with engineering design to develop human-centered automation. Scientific Contributions: Developed cognitive models of driver behavior and situational understanding Pioneered research on attentional tunneling and cognitive distraction in automated driving Advanced methodologies for usability evaluation of in-vehicle technologies Influenced design principles for cooperative human-machine interaction Prof. Baumann has supervised numerous research projects and mentored early-career researchers, though specific student names are not listed. His work has been supported by national and institutional research grants related to transportation safety and human factors engineering. He previously led research groups at the German Aerospace Center (DLR) and held postdoctoral positions at Chemnitz University of Technology and BASt, reflecting a deep engagement with applied cognitive science. He is associated with the Human Factors research lab at Ulm University, which conducts empirical studies on driver behavior, cognitive load, and interface design using driving simulators, eye-tracking, and cognitive task analysis. The team focuses on holistic evaluation methods for next-generation driver assistance systems.

Johannes Kellerمشاهده پروفایل

استاد

• Social Psychology
• Self-Regulation
• Psychological Essentialism
• +۱۳ مورد دیگر

Johannes Keller is a Professor and Chair of Social Psychology at Ulm University, where he has been a faculty member since 2009. He leads the Social Psychology Lab and is actively involved in research, teaching, and academic service. His work bridges cognitive and motivational processes in social behavior, with a strong focus on self-regulation, essentialism, empathy, and meaningful work. Research Interests: Self-regulatory processes in social cognition and interaction Psychological essentialism and motivated social cognition Flow experiences and intrinsic motivation Empathy, compassion, and the compassion-hostility paradox Bullshit job perceptions and meaningful work Stereotype threat and performance Behavior in social dilemmas and hand hygiene compliance Psychosis proneness and its social implications His recent publications reveal a consistent focus on the interplay between motivational systems (especially regulatory focus) and social behavior, often integrating physiological measures (e.g., cortisol, heart rate variability) with experimental designs. Themes of moral judgment, prosociality, and the dark side of work have emerged prominently in his latest work. Scientific Service and Recognition: Editorial Board Member, European Journal of Social Psychology (2007–2009; since 2012) Associate Editor, British Journal of Social Psychology (2017–2018) Associate Editor, European Review of Social Psychology (since 2023) Guest Editor, special issue on Self-Regulation and Strategic Motivational Orientations in Economic Contexts (Journal of Economic Psychology) Ad hoc reviewer for major funding agencies including DFG, NSF, ANR, SNSF, and others Reviewer for over 60 journals including JPSP , Psychological Science , and Personality and Social Psychology Bulletin Keller has advised numerous graduate students, many of whom are now co-authors on high-impact publications. His lab fosters interdisciplinary research at the intersection of social, cognitive, and organizational psychology. He has organized major academic events such as the EASP Small Group Meeting on empathy and the German Social Psychology Conference (2017). His university service includes leadership roles in examination boards and curriculum development for psychology programs at Ulm University.

Roman Abelمشاهده پروفایل

پژوهشگر

• Educational Psychology
• Desirable Difficulties in Learning
• Interleaving Effect
• +۴ مورد دیگر

Dr. Roman Abel is a Postdoctoral Researcher at the Department of Educational Psychology, Ruhr University Bochum. He is part of the Institute of Educational Science within the Faculty of Philosophy and Educational Research. His academic career includes a Dr. phil. in Psychology from the University of Kassel (2021), an M.Sc. in Educational Psychology from the University of Hildesheim (2014), and dual B.A. degrees in Educational Science and Educational Psychology from Novgorod University and the University of Hildesheim (2009). Abel’s research focuses on desirable difficulties in learning , including the interleaving effect , generation effect , retrieval practice , and multilingual vocabulary acquisition . His work emphasizes cognitive processes during learning with expository texts and the optimization of instructional strategies. His recent publications explore synergies between generative learning and retrieval practice, metastrategic decision-making in interleaving strategies, and cognitive processes in mushroom foraging as a naturalistic learning context. His research also addresses bilingual vocabulary development and socio-economic factors influencing educational outcomes. Abel’s work bridges theoretical cognitive science with practical educational applications, aiming to improve learning efficiency through evidence-based interventions.

Stefanie Klattمشاهده پروفایل

استاد

• Sports Science
• Cognitive Psychology
• Motor Learning
• +۴ مورد دیگر

Stefanie Klatt is a Professor in the Department of Cognition in Team Sports at the German Sport University Cologne. Her research focuses on integrating cognitive factors into the analysis and optimization of training and movement processes in sports games. Current academic leader in team sports cognition Active editorial contributor to sports science journals International collaborations with institutions like University of Brighton Her research spans Sports Science , Cognitive Psychology , and Motion Analysis , particularly examining attention mechanisms, decision-making dynamics, and cognitive-motor integration in high-pressure sports scenarios. Recent work explores stress responses in referees and novel training interventions for athletes. Key publication trends include team sports cognition , performance optimization , and health promotion initiatives. Awards include the DOSB Science Prize (2016) and Honorary Research Fellowship at University of Brighton (2020). DOSB Science Prize 2016 DVS Publication Prize 2015 Karl Hofmann Research Prize 2015 Honorary Research Fellow, University of Brighton 2020 Excellence in Research Award 2023 She supervises junior researchers like PhD student Benjamin Noël and leads third-party funded projects on referee training, movement analysis, and public health interventions through insurance partnerships.