جست‌وجوی استاد و پژوهشگر

• Neuroscience
• Cognitive Psychology
• Autism Spectrum Disorders
• +۴ مورد دیگر

Cristina Becchio is a Professor at the Universität Hamburg's Medizinische Fakultät within the Department of Neurology and Psychiatry. Her research focuses on action understanding, autism spectrum disorders, robotics, and social neuroscience. She leads projects investigating how movement kinematics encode intentions and their implications for social cognition and clinical applications. Her work bridges neuroscience, psychology, and engineering, with notable contributions to theories of embodied cognition and human-robot interaction. She collaborates internationally on studies involving neuroimaging, wearable technologies, and AI models to decode mental states from motion patterns. Key research areas include developmental aspects of motor control, theory of mind in autism, and the design of rehabilitation robotics. Her interdisciplinary approach addresses both fundamental science and translational applications in healthcare and technology.

Gemma Roigمشاهده پروفایل

استاد

• Computer Vision
• Artificial Intelligence
• Neuroscience
• +۷ مورد دیگر

Gemma Roig is a Professor of Brain-inspired Artificial Intelligence at the Computer Science Department of Goethe University Frankfurt since 2020. She holds an honorary research affiliate position at MIT's Center for Brains Minds and Machines and is a member of hessian.ai. Her research focuses on computational models of human vision and their application to AI systems. Previously, she served as an Assistant Professor at Singapore University of Technology and Design (SUTD) and conducted postdoctoral research at MIT, exploring connections between AI and neuroscience. Education: BEng and MSc in Telecommunication Engineering from Ramon Llull University (Barcelona), PhD in Computer Vision from ETH Zurich, and extensive postdoctoral training at MIT and EPFL. Career highlights include establishing a research group in Singapore and securing a tenure position in Frankfurt after relocating for family reasons. Research interests span computational vision, neural networks, and the intersection of AI with human cognition. She leads the CVAI lab, developing tools like Net2Brain to bridge artificial and biological neural systems. Her work emphasizes ethical AI, explainability, and multimodal learning. Labs/Teams: Director of the CVAI lab; collaborator with MIT's CBMM and Ernst Strüngmann Institute. Active in interdisciplinary projects like the Algonauts Challenge. Supervises 10+ PhD students and postdocs in topics ranging from neuro-symbolic AI to molecular dynamics simulations. Grants & Funding: Supported by DFG, ERC, and DAAD scholarships. Net2Brain receives funding from German Research Foundation (DFG) and European Research Council (ERC).

Olaf Eisenمشاهده پروفایل

استاد

• Glaciology
• Climate Science
• Polar Research
• +۳ مورد دیگر

Prof. Olaf Eisen is a glaciologist at the Alfred Wegener Institute (AWI) and a Professor at the University of Bremen. His research focuses on ice sheet dynamics, glacial interactions with climate systems, and the role of ice masses in Earth's climate. He leads projects like the Beyond EPICA ice core drilling initiative to study ancient climate records. Key research areas include ice-ocean interactions, radar stratigraphy analysis, and the impact of climate change on polar regions. Education and affiliations include dual roles at AWI and the University of Bremen, with extensive fieldwork in Greenland and Antarctica. His work integrates advanced radar technology, machine learning for data analysis, and international collaborations to map ice sheet structures and model future climate scenarios. Awards include the Heinrich Award (2021). Current projects involve subglacial topography mapping, ice stream dynamics, and developing automated methods for tracing ice layers. His research bridges glaciology with geophysics, environmental science, and climate modeling to address global climate challenges.

• Internet of Things (IoT)
• Wireless Sensor Networks
• Cyber-Physical Systems
• +۳ مورد دیگر

Fernando Boavida is a Professor at the University of Coimbra, Portugal, specializing in Internet of Things (IoT), Cyber-Physical Systems (CPS), and Human-in-the-Loop systems. His work focuses on integrating privacy-preserving technologies, sustainable smart city solutions, and industrial IoT frameworks. Research Interests : IoT and Wireless Sensor Networks Cyber-Physical Systems (CPS) Data Privacy and Security Human-in-the-Loop Systems Industrial IoT and Federated Learning Smart City Sustainability Key Contributions : Developed models for Human-in-the-Loop CPS, emphasizing privacy and edge computing. Advanced federated learning frameworks for LoRaWAN-enabled IIoT. Designed systems for unobtrusive healthcare sensing and pandemic response. Published extensively on IoT management protocols and industrial automation. Grants and Projects : Co-PI on projects addressing IoT integration in construction and healthcare sectors. Contributed to EU-funded initiatives on smart city sustainability and privacy preservation. Teams and Labs : Boavida leads interdisciplinary teams at the University of Coimbra, collaborating with industry partners to deploy real-world IoT solutions, including the iSenior elderly support system and iHorse equine monitoring platform.

• Semantic Web
• Natural Language Processing
• Recommender Systems
• +۳ مورد دیگر

Francisco García-Sánchez is a Professor at the University of Murcia, Faculty of Computer Science, with 20+ years of expertise in Semantic Web , Natural Language Processing , and Recommender Systems . He collaborates with institutions like Simón Bolívar University and the University of Guadalajara, focusing on ontology-driven information systems, semantic analysis of political ideology, and financial data integration. His research bridges Artificial Intelligence and Information Retrieval , particularly in Spanish-language domains. Key projects include: PolticES: Political Ideology Detection FinancES: Financial Sentiment Analysis AllergyLESS: Smart City Health Systems His recent work (2023-2024) evaluates Transformer models for disinformation detection, emotion recognition, and multilingual hope speech analysis, emphasizing linguistic features and knowledge-based systems . He contributes to platforms like UMUTeam and FD, integrating semantic technologies with social networks and financial data.

• Machine Learning
• Biomedical Engineering
• Human-Computer Interaction
• +۴ مورد دیگر

Woojin Kim is a Professor in the Department of Mathematics at Duke University, Durham, NC, USA. His research spans interdisciplinary domains including Machine Learning , Biomedical Engineering , Human-Computer Interaction , and Wireless Sensor Networks . He has made significant contributions to medical imaging analysis , autonomous driving systems , and AI in education , with recent work focusing on fairness evaluation in machine learning and vision-language models for healthcare applications . His publications demonstrate expertise in: AI-driven medical diagnostics (CT scans, MRIs) Exoskeleton and robotic systems Autonomous vehicle transition dynamics Privacy-preserving clinical data processing Memory hardware testing frameworks Knowledge tracing algorithms in education Recent article trends highlight increasing emphasis on AI ethics (fairness evaluation), multimodal models (vision-language), and knowledge graph applications for scientific data organization. Collaborations with interdisciplinary teams across biomedical, engineering, and computer science domains underscore his cross-domain impact.

• Control Systems
• Traffic Engineering
• Image Processing
• +۴ مورد دیگر

Liguo Zhang is a prominent academic specializing in control systems, traffic engineering, and machine learning. His research focuses on advanced control strategies for traffic flow, autonomous systems, and image processing. He has contributed significantly to the development of observer designs for complex systems, adaptive control methodologies, and cyber-physical systems. His work bridges theoretical control frameworks with practical applications in transportation, robotics, and computer vision. Key areas include stabilization of traffic patterns, decision-making in autonomous vehicles, and vulnerability detection in smart contracts. Zhang's research also spans digital twin technologies for railway systems, diffusion models for font generation, and robust Bayesian neural networks. His collaborative efforts with institutions and co-authors highlight interdisciplinary innovation in both foundational and applied domains.

Linda Baumbachمشاهده پروفایل

پژوهشگر

• Bioinformatics
• Medical Informatics
• Federated Learning
• +۵ مورد دیگر

Dr. Linda Baumbach is a Researcher at the University of Hamburg's Center for Bioinformatics (ZBH), affiliated with the Genome Informatics department. Her work focuses on bioinformatics applications in healthcare, particularly federated learning, privacy-preserving technologies, and osteoarthritis management. She investigates personalized medicine, physical activity impacts on chronic conditions, and healthcare system improvements. Research Interests Her interdisciplinary research spans federated machine learning for biomedical data, predictive modeling in osteoarthritis treatment outcomes, and leveraging AI for systematic literature analysis. She explores innovative approaches to data privacy in genomic studies and evaluates cost-effectiveness of physiotherapy interventions. Key Contributions Dr. Baumbach co-developed the FeatureCloud platform for federated learning, enabling collaborative research while adhering to data protection laws. Her studies on GLA:D® programs highlight exercise therapy benefits for knee osteoarthritis patients. She also addresses challenges in implementing personalized predictive models and advancing LLM-driven literature screening. Professional Activities She contributes to academic committees at the Center for Bioinformatics and collaborates internationally on projects like the GLA:D initiative and JIGSAW-E quality improvement program. Her work bridges computational methods with clinical needs, emphasizing translational research.

Moritz Kreinsenمشاهده پروفایل

پژوهشگر

• AI Education
• AI Literacy
• Data Literacy Education
• +۵ مورد دیگر

Moritz Kreinsen is a Researcher and Project Coordinator at the University of Hamburg's Faculty of Education, specifically in the Department of Didactics of Social Sciences and Mathematics and Natural Sciences (EW 5). He holds an M.Ed. and B.Sc. in secondary school teaching with a focus on computer science and physics from the University of Hamburg. His research focuses on AI Education, Data Literacy, and conceptual change in teaching AI and data concepts. He coordinates the Digital and Data Literacy in Teaching Lab (DDLitLab) and leads projects like the Interdisciplinary AI + Data Lab in Teacher Education (Teacher AID Lab), integrating AI and data literacy into STEM teacher training. He teaches seminars on AI literacy and data literacy in schools and teacher education. Recent publications emphasize AI ethics, conceptual change strategies, and project-based learning methods. Kreinsen actively participates in international conferences and collaborates with institutions like the Stiftung Innovation in der Hochschullehre. His work bridges educational theory and practice, emphasizing transformative teaching methods through student research centers and interdisciplinary labs.

• Artificial Intelligence
• Computer Science
• Data Science
• +۳ مورد دیگر

Florian Marwitz is a doctoral researcher at the University of Hamburg affiliated with the Cluster of Excellence 'Understanding Written Artefacts' (UWA) and the Artificial Intelligence in Humanities (Prof. Dr. Möller) department. His work focuses on advancing computational methods for humanities research, including graph algorithms, probabilistic models, and AI applications in cultural heritage preservation. He contributes to projects like the Data Linking Infrastructure and ChatHA chatbot development, emphasizing sustainable information systems and efficient prediction techniques. His research bridges computer science and humanities, addressing challenges in data representation and decision-making systems. Marwitz holds an MA and is based at the Centre for the Study of Manuscript Cultures. His activities include organizing workshops on data linking and AI ethics, reflecting commitments to interdisciplinary collaboration. He is part of the Institut für Humanities-Centered Artificial Intelligence (CHAI), actively involved in training programs and public engagement initiatives.

• Human-Robot Interaction
• Augmented Reality
• Virtual Reality
• +۵ مورد دیگر

Doris Aschenbrenner is a researcher specializing in human-robot interaction and augmented reality applications for industrial maintenance systems at Julius Maximilians University Würzburg. Her work bridges computer science, engineering, and human factors disciplines to develop practical solutions for Industry 4.0 environments. Her research focuses on Human-Robot Interaction , Augmented and Virtual Reality for industrial applications , Human-in-Command systems , and Industry 4.0 technologies . She has conducted extensive work on AR-assisted maintenance operations, digital twins for production environments, and human factors considerations in collaborative robotics systems. Her research demonstrates how immersive technologies can enhance manufacturing processes while maintaining appropriate human oversight and control. Her publication record shows significant contributions to conferences like ISMAR, VR, and Frontiers in Robotics and AI, with a consistent output from 2013 through 2024. Her recent work has focused on regulatory aspects of AI implementation in manufacturing, particularly regarding the EU AI Act, and developing platforms for digital remote maintenance services. Her research has practical implications for manufacturing industries seeking to implement advanced human-machine collaboration systems while addressing regulatory requirements and human factors considerations.

• Human-Computer Interaction
• Mixed Reality
• Smart Built Environments
• +۴ مورد دیگر

Denis Gracanin is a Professor at Virginia Tech's Department of Computer Science, College of Engineering. His research spans Human-Computer Interaction, Mixed Reality, Smart Built Environments, and Generative AI, with a focus on immersive technologies, cybersecurity, and assistive systems. Research highlights include: Developing frameworks for XR-based security in zero-trust networks Advancing real-time 3D object generation in augmented reality using generative AI Designing smart environments for stress management and mobility assistance His recent work explores AI-driven design optimization, sonification in immersive analytics, and privacy-centric IoT systems. Articles emphasize applications in healthcare, cybersecurity, and smart lighting, leveraging machine learning and multimodal data. Gracanin collaborates extensively with researchers like Kresimir Matkovic, Mohamed Azab, and Majid Behravan, publishing in top venues such as IEEE Transactions on Visualization and Computer Graphics, CHI, and VR Workshops.

• Virtual Reality
• Augmented Reality
• Technology-Enhanced Learning
• +۵ مورد دیگر

Ekaterina Prasolova-Førland is a Professor at the Norwegian University of Science and Technology (NTNU) , specializing in the application of Virtual Reality (VR), Augmented Reality (AR), and 3D Collaborative Virtual Environments (CVEs) across diverse educational contexts. Her research spans medical education , military training , cross-cultural collaboration , and emergency management . She has led editorial efforts for journals like Educational and Information Technologies and Frontiers in Virtual Reality . Her work focuses on immersive technologies to enhance learning outcomes, including projects like the Virtual Operating Room for surgical nurses and 3D reconstructions of historical sites . She explores how VR/AR can address complex pedagogical challenges, such as teaching protection of civilians to military officers and neuroanatomy to medical students. Publications highlight her expertise in collaborative learning , digital career guidance , and XR lab management during the pandemic. Recent articles emphasize physiological data collection in military XR training and peer learning through AR applications. Her contributions to boundary objects and community memory repositories in virtual worlds underscore her interest in collaborative knowledge-building. Despite no explicit scientific awards listed, her extensive publication record (over 60 works) and editorial leadership reflect significant academic impact.

• Computer Science
• Human-Computer Interaction
• Virtual Reality
• +۴ مورد دیگر

Efe Bozkir is a researcher affiliated with the University of Tübingen, Germany. His work focuses on advancing virtual reality (VR) and augmented reality (XR) technologies through eye tracking, privacy-preserving data techniques, and integrating large language models (LLMs) into immersive systems. He explores human-computer interaction challenges, particularly in educational settings and ethical AI applications. Research interests include: privacy in eye-tracking data, generative AI for synthetic media analysis, and optimizing federated learning algorithms. He has co-authored over 50 publications in top-tier venues such as CHI, VR, and ACM Transactions on Applied Perception. Recent articles highlight innovations like CUIfy (an LLM integration toolkit for XR), privacy benchmarks for iris obfuscation, and AI-driven video assistants for active learning. His work consistently bridges technical advancements with societal implications, addressing GDPR compliance in metaverse environments and ethical AI use in education. Bozkir collaborates closely with interdisciplinary teams, including Enkelejda Kasneci (co-author in 49 works) and Süleyman Özdel. His PhD (2022) laid groundwork for 'Everyday Virtual Reality through Eye Tracking.' Though no formal awards are listed, his prolific publication record reflects significant contributions to XR research.

• Ethics of Artificial Intelligence
• Philosophy of Science
• Machine Learning Interpretability
• +۵ مورد دیگر

Thomas Grote is a Research Fellow at the Ethics and Philosophy Lab of the University of Tübingen’s Cluster of Excellence "Machine Learning: New Perspectives for Science" . Trained in philosophy, he works at the intersection of ethics and philosophy of science, focusing on interpretability, fairness, and reliability of machine-learning systems, especially in medicine and the social sciences. Research Interests: Ethics & epistemology of AI, particularly healthcare AI Interpretability, fairness, and reliability of ML models Methodology of AI ethics and cross-disciplinary integration Computational psychiatry and predictive modelling in psychopathology His recent publications analyse foundational questions such as how to ensure ML models fulfil their intended socio-technical functions and what guardrails guarantee safe deployment. Empirical domains of concern span clinical decision support, public health prediction, and computational psychiatry, unified by an overarching interest in the epistemic conditions for trustworthy AI. Grants & Conference Roles: Co-supervisor, Carl-Zeiss-Stiftung project "Certification and Foundations of Safe Machine Learning Systems in Healthcare" Former co-supervisor, Baden-Württemberg Stiftung project "AI, Trustworthiness, and Explainability (AITE)" Co-organiser, "Philosophy of Science Meets Machine Learning" conference series (with Genin, Freiesleben, Zezulka) Program Chair, 4th European Workshop on Algorithmic Fairness (EWAF 2025), Eindhoven He welcomes collaboration inquiries and enjoys coordinating workshops, joint grant applications, and interdisciplinary paper projects.