جست‌وجوی استاد و پژوهشگر

Ying-Tung Linمشاهده پروفایل

دانشیار

• Philosophy of Mind
• Philosophy of Consciousness
• Cognitive Enhancement
• +۶ مورد دیگر

Ying-Tung Lin is an Associate Professor at the Institute of Philosophy of Mind and Cognition , National Yang Ming Chiao Tung University (NYCU), Taipei, Taiwan. His research sits at the intersection of philosophy of mind, cognitive science, and AI ethics, with a focus on self-experience in mental simulation, algorithmic bias, and authenticity in memory interventions. Education: PhD in Philosophy from Johannes Gutenberg-Universität Mainz (2014). Research interests include: Philosophy of Mind & Consciousness Cognitive Enhancement via Neurotechnology Algorithmic Fairness in AI Episodic Memory & Bodily Self-Identification Observer Perspective in Mental Simulation Autobiographical Self-Modeling His publication trends show interdisciplinary engagement between 2014-2024, covering topics like dream epistemology , AI governance frameworks , and neuroethical policy . Key methodologies involve conceptual analysis combined with empirical data from cognitive studies. Advising information is not explicitly available in provided texts. Grants or funding sources aren't mentioned in the scraped content. Dr. Lin participates in cross-disciplinary initiatives like the Philosophy, Intelligence, Brain, and Mind Program at NYCU, and contributes to academic events including the International Society for the Philosophy of the Sciences of the Mind conference (2025).

Leonardo Banhمشاهده پروفایل

پژوهشگر

• Generative AI
• Artificial Intelligence
• Machine Learning
• +۶ مورد دیگر

Leonardo Banh is a Researcher at the University of Duisburg-Essen within the Faculty of Computer Science and its Chair of Business Information Systems and Software Engineering . M.Sc. in Business Information Systems (University of Duisburg-Essen, 2022) B.Sc. in Business Information Systems (University of Duisburg-Essen, 2020) Semester abroad at Instituto Superior Técnico, Lisbon (2021) His research focuses on Generative AI and its socio-technical implications, particularly in Machine Learning and Deep Learning applications. He explores intersections with NeuroIS , Smart Tourism , and E-commerce Ecosystems , emphasizing sustainability and digital transformation. Recent publications analyze Generative AI in Software Engineering , AI in Music Sentiment Analysis , and AI-Based Sign Language Translation . His work often involves design science research and grounded theory frameworks. Best Paper in Track Award (ICIS 2024) Nominated for Best Paper Award (ICIS 2024) Outstanding Reviewer (ICIS 2024) As advisor, he supervises theses on topics including AI-Based Mental Health Chatbots , Generative AI in HR , and Smart Tourism Applications . He also contributes to the Institute of Computer Science and Information Systems and serves on appointment/habilitation committees.

• Intelligent Information Systems
• Human-Centered & Generative AI
• Internet of Things (IoT) & Smart Services
• +۴ مورد دیگر

Gero Strobel is an Assistant Professor at the Chair of Business Informatics and Software Engineering, Faculty of Computer Science, University of Duisburg-Essen. His research focuses on intelligent information systems, generative AI, and IoT-enabled smart services with applications in sustainability, healthcare, and industrial transformation. Academic Roles: Assistant Professor (2022–present), Postdoctoral Researcher (2021), Research Assistant (2017–2021) Key Research Areas: Generative AI, Smart Service Systems, E-commerce Ecosystems, Digital Health, Sustainable Business Models His work develops design principles for VR training systems, AI healthcare communication, and smart agriculture architectures. He leads the SOFTEC IoT Innovation Lab and contributes to data ecosystems research as guest editor of Electronic Markets (2024 special issue). Scientific Recognition: 2021 Science Prize of Sparkasse Essen 2021 University of Duisburg-Essen Dissertation Prize Best Paper in Track Award at ICIS 2021 Strobel co-edits the Electronic Markets special issue on data ecosystems (2024) and serves as track chair for data ecosystems at HICSS and AMCIS. His research combines design science methodology with empirical studies across 135+ e-commerce initiatives, 100+ AI startup analyses, and 183 IoT architectures.

• Neuroengineering
• Brain-Computer Interfaces (BCI)
• Human-Robot Interaction (HRI)
• +۳ مورد دیگر

Stefan Ehrlich is a Researcher at the Institute for Cognitive Systems (ICS) at the Technical University of Munich (TUM). His work focuses on neuroengineering, particularly non-invasive brain-computer interfaces (BCI) for human-robot interaction (HRI), neuroadaptive systems, and EEG-based neurotechnology. He collaborates closely with Prof. Gordon Cheng and contributes to projects involving error-related potentials (ErrPs), affective neurofeedback, and neuroprosthetics. His research integrates cognitive neuroscience principles with robotics to enhance human-machine collaboration and adaptive systems. Key research areas include: Development of passive BCI systems for real-time robotic adaptation Design of co-adaptive human-agent interfaces using neural signals EEG-based assessment of exoskeleton and humanoid robot performance Neuroimaging techniques for music-brain interactions His publications emphasize interdisciplinary approaches, combining neuromorphic engineering, machine learning, and social robotics. Ongoing work explores low-power neuromorphic hardware for EEG decoding and neurophysiological mechanisms underlying human-robot trust dynamics. Collaborations involve institutions like the Bernstein Center for Computational Neuroscience and industry partners in wearable robotics. Labs/Teams: Active contributor to the EEG Laboratory and projects like the Soft Wearable Robotics initiative. Engages in international conferences (IROS, IEEE EMBC) and co-organizes workshops on HRI and neurotechnology.

Armin Iskeمشاهده پروفایل

استاد

• Numerical Approximation
• Applied Mathematics
• Kernel Methods
• +۴ مورد دیگر

Prof. Dr. Armin Iske is a Full Professor of Numerical Approximation at the University of Hamburg's Department of Mathematics, within the Faculty of Mathematics, Computer Science and Natural Sciences. He holds a PhD from the University of Göttingen (1994) and habilitation from TU Munich (2002). His research focuses on numerical approximation, kernel-based methods, computational fluid dynamics, and medical imaging. He has held academic positions globally, including visiting roles at ANU (Australia) and the University of Leicester (UK). Research interests include scattered data approximation, adaptive particle methods for flow simulation, and high-dimensional data analysis. He has authored 118+ publications, including works on kernel interpolation, medical imaging reconstruction, and machine learning applications. He serves on editorial boards for journals like Advances in Computational Mathematics and Sampling Theory . His contributions span interdisciplinary projects, such as SFB/TRR 181 on energy transfer in atmosphere and ocean, and collaborations in nanotechnology for brain interfaces. His work bridges theoretical mathematics with practical applications in engineering and biosciences.

• Virtual Reality
• Augmented Reality
• Educational Technology
• +۷ مورد دیگر

Roghayeh Barmaki is a researcher with extensive publications in virtual reality, augmented reality, and educational technology. Her work spans rehabilitation systems, autism therapy, and neuroimaging analysis using fNIRS. She collaborates with institutions including Georgia Institute of Technology and University of Florida. Key Collaborators : Anjana Bhat, Jicheng Li, Shayla Sharmin, Vuthea Chheang Research Themes : Wearable sensors, LSL framework, movement synchrony, multimodal learning analytics Research Interests She focuses on immersive technologies for education and therapy, with expertise in: Functional Near-Infrared Spectroscopy (fNIRS) for cognitive engagement Wearable sensor integration in rehabilitation Gender perspectives in AR/VR education Multimodal affect analysis for autism Privacy-preserving behavioral analytics 3D visualization for anatomy training Publication Trends Recent work emphasizes fNIRS applications in gaming environments and hybrid deep learning models for cognitive analysis. Earlier studies focused on gesture recognition, movement synchrony estimation, and autism intervention datasets. Impactful Projects She developed the MMASD dataset for autism research and contributed to VR therapy systems. Her collaborations include: Georgia Tech's Autism Technology Research University of Florida's TeachLivE virtual classroom Germany's AIxVR conference contributions International collaborations on sensor systems

• Computer Science
• Machine Learning
• IoT
• +۷ مورد دیگر

Ali Hassan is a researcher affiliated with the National University of Sciences and Technology (NUST), School of Electrical Engineering and Computer Science, Department of Computer and Software Engineering. His work spans multiple domains in computer science, engineering, and applied mathematics, focusing on areas such as machine learning, IoT, energy systems, and medical informatics. His research explores: Reinforcement learning applications for battlefield information systems IoT antenna design and performance evaluation Optimization of second-life battery systems in electric vehicles Transformers for real-time vehicle collision avoidance Image hashing techniques using visual attention models Neural network-based phasor estimation for power grids Biomedical sensor systems for non-invasive health monitoring Mathematical modeling of viral dynamics Recent publications demonstrate his emphasis on interdisciplinary approaches combining AI, signal processing, and sustainability. He has collaborated with institutions across Pakistan, France, Saudi Arabia, and the USA, with a focus on practical implementations in cybersecurity, energy optimization, and healthcare technology.

• Cognitive Robotics
• Augmented Reality
• Traffic Telematics
• +۳ مورد دیگر

Prof. Dr.-Ing. Gerd-Jürgen Giefing serves as Professor of Information and Communication Technology at Georg Agricola University of Applied Sciences since 2003, concurrently leading the Electrical and Information Engineering Master's Program, Digital Signal Processing Laboratory, and serving as Deputy Head of the Software Engineering Laboratory. His academic foundation includes: Electrical engineering studies with data processing focus at University of Karlsruhe and Technical University of Munich (1983-1988) Doctorate in neuroinformatics and technical vision from Ruhr University Bochum (1988-1993) Research spans cognitive robotics with emphasis on behavior-oriented scene analysis and distributed communication frameworks, augmented reality systems, and traffic telematics applications including driver face recognition. His foundational work in biologically inspired computer vision established video-based facial capture systems using multiprocessor architectures, later evolving into cognitive robotics frameworks. Current investigations focus on brain-computer interfaces and nomadic point cloud calibration for mobile robotics. Publication trends reveal a progression from neurobiological vision models (1990s) to cognitive robotics infrastructure (2010s), consistently addressing real-world applications in automation and human-machine interaction through IEEE conference proceedings. Key recognitions: Innovation Award '94 from Bochum Technology Transfer Association European Information Technology Award 1996 from European Council for Applied Sciences and Engineering As IEEE Systems Man and Cybernetics Society member, he maintains active research leadership without documented grant specifics. His laboratory direction fosters applied research in signal processing and software engineering for cognitive systems development.

• Neuromorphic Electronics
• Neuroscience
• Biointerfaces
• +۳ مورد دیگر

Dr. Hongwei Tan serves as Group Leader at the Department of Molecular Electronics, Max Planck Institute for Polymer Research (MPIP) in Mainz since November 2024. Previously, he was Research Fellow (2022-2024) and Postdoctoral Fellow (2017-2022) at Aalto University's Department of Applied Physics, following postdoctoral work at the University of Massachusetts Amherst on neurointerface devices. His academic credentials include: Bachelor of Physics, Nankai University (2011) Doctorate in Materials Physics and Chemistry, University of Chinese Academy of Sciences (2016), focusing on neuromorphic photomemristors Tan's research pioneers neuromorphic biointerfaces—integrating brain-inspired electronics with biological systems to enable energy-efficient computation and seamless biointeraction. His work targets transformative applications in brain-machine interfaces, prosthetics, and diagnostics through interdisciplinary convergence of neuroscience, materials science, and engineering. His publication portfolio (2015-2024) reveals a clear evolution from foundational optoelectronic memristor research toward complex neuromorphic systems for sensory processing. Key thematic trajectories include photomemristor-based vision systems, tactile coding with spiking nerves, and nanoionic human-machine interfaces, demonstrating consistent innovation in bioinspired hardware. As MPIP Group Leader, Tan directs research strategy and team mentorship within his neuromorphic electronics program, though specific advisees and grant details remain unlisted in available materials. His laboratory focuses on developing integrated neuromorphic systems—from novel materials and devices to algorithms—that facilitate bidirectional communication between electronic and biological neural networks for next-generation neurotechnologies.

• Neuroergonomics
• Human-Machine Interaction
• Human Factors
• +۳ مورد دیگر

Dr. Julian Elias Reiser is a Research Fellow in the Experimental Ergonomics and Stress & Work Design group at the Leibniz Research Centre for Working Environment and Human Factors (IfADo), affiliated with TU Dortmund University. His work focuses on applying mobile neuroimaging techniques, particularly EEG, to assess cognitive workload and human performance in real-world settings such as driving and walking. His educational background includes: PhD in Psychology (2020) from TU Dortmund University, with a thesis titled "Neuroergonomics in the wild - Workload assessment using mobile EEG" M.Sc. Psychology from the University of Ulm (2016) B.Sc. Business Psychology from Leuphana University Lüneburg (2014) Dr. Reiser's research interests lie at the intersection of neuroscience and human factors. He investigates how cognitive processes unfold during complex tasks in natural environments, using mobile EEG and eye-tracking to measure workload, attention, and operator state. His work aims to improve human-machine interaction and workplace design by providing objective neurophysiological measures of mental effort. His recent publications (2023-2025) highlight a strong emphasis on real-world applications of neuroergonomics. Key themes include the use of eye blink-related potentials as indicators of cognitive load, the impact of automation on driver attention, and the development of signal processing methods for decoding brain activity in dynamic settings. His research spans transportation, occupational health, and human-computer interaction. No scientific awards are listed in the available information. There is no information provided regarding students advised or research grants obtained. Dr. Reiser is part of the Experimental Ergonomics team led by Prof. Dr. Edmund Wascher within the Ergonomics department at IfADo. The team conducts cutting-edge research on human factors in various work contexts, with a focus on developing and applying neuroergonomic methods to assess and enhance human performance in real-world environments.

• Environmental Toxicology
• Cellular Resilience
• Genetic Buffering
• +۵ مورد دیگر

Andrea Rossi is a Research Group Leader at the Leibniz Institute for Environmental Medical Research (IUF) in Düsseldorf, Germany, where they lead the Environmental Adaptation and Cellular Resilience research group. Their work bridges environmental science and molecular biology, focusing on how pollutants influence cellular resilience and disease expression. The research group collaborates extensively with national and international institutions including Heinrich-Heine-Universität Düsseldorf, Leibniz Institute for Food Systems Biology, and ETH Zürich. Dr. Rossi's research interests center on understanding phenotypic plasticity in monogenic inherited diseases, particularly how environmental pollutants affect cellular resilience and trigger compensatory genetic mechanisms. Their work explores how cellular systems adapt under environmental stress with genetic mutations, develops advanced iPSC models for studying disease mechanisms, and employs whole-genome CRISPR screening to identify novel genetic modifiers. A significant aspect of their research investigates how cellular resilience mechanisms impaired during aging may contribute to age-related diseases. The research group's publications over the past five years demonstrate a strong focus on stem cell technology, genome editing, and environmental toxicology. Their work spans from basic molecular mechanisms to translational applications, with particular emphasis on developing precise genome editing techniques like Prime Editing and improving quality control standards for induced pluripotent stem cells. The research has important implications for understanding environmental influences on genetic diseases and developing new therapeutic approaches. Dr. Rossi's team includes postdocs Stephanie Binder and Jochen Dobner, scientific staff member Marianthi Papadopoulou, several master's students, and technical assistance from Vanessa Baltruschat. Their research is supported by multiple funding sources including the Leibniz Association, German Research Foundation (DFG), AFM Téléthon, and the European Union. The Environmental Adaptation and Cellular Resilience group operates several cutting-edge projects including modeling environmental pollution effects on taste perception using organoids, investigating genetic buffering mechanisms, improving Prime Editing efficiency, analyzing genome editing risks, studying epilepsy in mitochondrial diseases, and enhancing hiPSC quality control standards. These projects employ advanced techniques including iPSC modeling, CRISPR screening, and multi-omics approaches.

• Explainable AI
• Machine Learning
• Social Media Analysis
• +۶ مورد دیگر

Professor Alun D. Preece is a distinguished academic at Cardiff University's Crime and Security Research Institute, UK, with significant contributions to artificial intelligence, particularly in explainable AI (XAI), social media analysis, and neuro-symbolic approaches. His research spans over three decades with continuous publication output through 2024, demonstrating sustained scholarly impact in the AI community. His research interests focus on creating transparent and interpretable AI systems that can effectively collaborate with humans in complex environments. Key areas include explainable AI methodologies, social media analysis for misinformation detection, neuro-symbolic integration for robust reasoning, and collaborative perception-cognition-communication-action frameworks. His work bridges theoretical AI foundations with practical applications in security, public safety, and coalition operations. Recent publications (2022-2024) reveal a strong focus on cutting-edge AI challenges, with particular emphasis on neuro-symbolic approaches, vector symbolic architectures, and human-AI teaming. His work consistently addresses the critical challenge of creating AI systems that are not only effective but also transparent, trustworthy, and capable of meaningful collaboration with human users. Professor Preece has established extensive collaborations across the AI research community, with notable co-authors including Dave Braines, Federico Cerutti, Ian J. Taylor, and Mani Srivastava. His research has been published in top venues including FUSION, IEEE Transactions, and AAAI workshops. His work on verifiable credentials for AI model transparency, collaborative perception frameworks, and misinformation analysis demonstrates practical applications of his theoretical contributions to real-world security and information challenges. The trajectory of his recent publications indicates continued leadership in addressing the critical challenges of trustworthy and explainable AI systems.

• Brain-Computer Interfaces
• Neural Engineering
• Electroencephalography (EEG)
• +۷ مورد دیگر

Prof. Dr. Gernot R. Müller-Putz is a leading academic in neural engineering and brain-computer interfaces at the Institute of Neural Engineering , Graz University of Technology , within the Faculty of Computer Science and Biomedical Engineering . He leads both the institute and its associated Laboratory of Brain-Computer Interfaces , driving cutting-edge research in non-invasive neurotechnology and assistive systems. Research Interests: His work spans Brain-Computer Interfaces , EEG signal processing , neurorehabilitation , neuroprosthetics , and cognitive neuroscience . He focuses on decoding motor intentions, sensory feedback restoration, and developing interpretable AI models for neural data. His research bridges engineering, neuroscience, and clinical applications to enhance human-machine interaction and improve quality of life for individuals with disabilities. Recent Research Trends: Analysis of his latest publications (2024–2025) reveals a strong emphasis on EEG-based decoding of gait and reaching movements , cross-subject generalization using deep learning, sensory and proprioceptive restoration in amputees, and cognitive processing in augmented reality . These reflect a cohesive trajectory toward real-world, clinically viable BCI systems with robust and interpretable performance. Scientific Leadership and Editorial Roles: Specialty Chief Editor, Brain-Computer Interfaces , Frontiers in Human Neuroscience Associate Editor, Neuroprosthetics , Frontiers in Neuroscience Review Editor, Health Informatics , Frontiers in Digital Health Topic Editor, Neurophysiological foundations of videoconference fatigue He plays a significant role in shaping discourse in BCI and neural engineering through editorial leadership. Advising and Research Leadership: As head of the Institute of Neural Engineering and the BCI Laboratory, he mentors students and researchers, oversees multiple funded projects, and collaborates internationally. While specific students are not listed, his high publication output and editorial roles suggest active supervision and team leadership. His research is supported by ongoing grants in neural engineering and assistive technologies, though specific funding sources are not detailed here. Laboratories and Teams: Institute of Neural Engineering , Graz University of Technology Laboratory of Brain-Computer Interfaces (affiliated with the institute) These units form a hub for interdisciplinary research in neural signal processing, BCI development, and clinical translation.

Manfred Reichertمشاهده پروفایل

استاد

• Business Process Management (BPM)
• Service-Oriented Architectures
• E-health
• +۷ مورد دیگر

Prof. Manfred Reichert is a full professor at the University of Ulm, serving as Director of the Institute of Databases and Information Systems and Dean of Studies at the Faculty of Engineering and Computer Science. He holds dual expertise in Computer Science and Mathematics, with academic leadership roles including chairing examination boards and strategic research initiatives. His interdisciplinary affiliations include co-opted membership in the Faculty of Mathematics and Economic Sciences. Reichert's research focuses on Business Process Management (BPM), IoT-driven processes, service-oriented architectures, and e-health applications. Notable contributions include co-developing the ADEPT process management system and pioneering object-centric process modeling. He has led over 20 international research projects (EU FP7, DFG, Industry) and authored >200 peer-reviewed papers, earning an h-index of 60+ and prestigious awards like the Merckle Forschungspreis. Education: PhD in Computer Science & Mathematics Diploma Leadership: Former associate professor at University of Twente, former director of CTIT research center Service: Conference chair for BPM, CoopIS, EDOC; steering committee member for GI SIG Databases Recent work explores IoT integration in BPM, generative AI for process models, and neuroscience-informed usability studies. His research bridges technical innovation with human-centric design, addressing challenges in process lifecycle management, federated learning, and mobile health interventions. Awards: IFIP TC2 Manfred Paul Award, doIT Software Award Key Projects: BPMN extensions for IoT, data-driven healthcare solutions

• Explainable AI
• Interpretable Machine Learning
• Deep Learning
• +۱۳ مورد دیگر

Wojciech Samek is a Professor in the Department of Electrical Engineering and Computer Science at the Technical University of Berlin and Head of the AI Department at Fraunhofer Heinrich Hertz Institute (HHI), Germany. He holds a joint appointment, bridging academic research and industrial application in artificial intelligence. He is a Fellow at BIFOLD and ELLIS Unit Berlin, and a Principal Investigator in several DFG projects including DeSBi and BIOQIC. PhD (Dr. rer. nat.) with distinction, Technical University of Berlin, 2014 Studies in Computer Science, Humboldt University, Heriot-Watt University, University of Edinburgh His research centers on Explainable AI (XAI) , Trustworthy Deep Learning , and Efficient AI . He pioneered Layer-wise Relevance Propagation (LRP), a foundational method for interpreting deep neural networks. His work spans model interpretation, robustness against adversarial attacks, neural network compression, federated learning, and applications in healthcare, communications, and multimedia. The recent articles highlight a strong trend toward extending explainability beyond deep models , with research on concept-level explanations, unsupervised learning interpretability, and XAI-driven model improvement. There is a consistent focus on robustness, privacy, and efficiency in distributed learning settings, particularly for federated and edge AI. Applications in medical AI and neuroscience are prominent, emphasizing safety and interpretability in high-stakes domains. Best Paper Award, Pattern Recognition (2020) Digital Signal Processing Best Paper Prize (2022) Fellow, BIFOLD - Berlin Institute for the Foundation of Learning and Data Member, Germany's Platform for Artificial Intelligence Senior Editor, IEEE TNNLS; Associate Editor, Pattern Recognition, Digital Signal Processing, PLoS ONE Area Chair, NeurIPS, ICML, NAACL Program Chair, IEEE MLSP 2023 Contributor to ISO/IEC MPEG-17 NNC standard Prof. Samek advises a large group of PhD students and leads a vibrant research team at Fraunhofer HHI and TU Berlin. His group has secured significant funding through DFG, BIFOLD, and industrial collaborations. He has co-authored over 200 peer-reviewed papers, many of which are ESI Hot or Highly Cited. He is deeply involved in organizing workshops and tutorials on XAI, federated learning, and neural compression at top venues like NeurIPS, ICML, CVPR, and IEEE conferences. His lab develops open-source tools such as the LRP Toolbox , Keras Explanation Toolbox , DeepCABAC , and Quantus , promoting reproducibility and adoption of interpretable and efficient AI methods. The team is actively working on next-generation AI that is not only accurate but also transparent, robust, and trustworthy.