جست‌وجوی استاد و پژوهشگر

• Self-organized criticality
• Neuronal network dynamics
• Excitation/Inhibition balance
• +۵ مورد دیگر

Anna Levina is an Assistant Professor for Computational Neuroscience at the University of Tübingen , affiliated with the Department of Computer Science under the Faculty of Science. Her research focuses on the self-organization of neuronal activity, critical dynamics in neural networks, and the excitation/inhibition balance in cortical circuits. Current positions: Assistant Professor (since 2018), Group Leader (2017-2018), Equality Officer (Computer Science) Previous roles: IST Fellow (2015-2017), Associated Researcher (2011-2015), Postdoc/PI (2011-2015), Postdoc (2008-2011) Her research integrates mathematical modeling , statistical physics , and computational neuroscience to study criticality phenomena, neural avalanches, and adaptive network dynamics. Key interests include: Self-organized criticality in neural systems Excitation/Inhibition balance mechanisms Network topology and dynamics Timescale analysis in neural processing Stochastic modeling of neural activity Recent publications reveal trends in understanding critical dynamics across biological and artificial networks, with applications to memory systems, sensorimotor integration, and disease modeling. She has received recognition as an IST Fellow .

• Sociology of Emotions
• Cultural Sociology
• Social Structure Analysis
• +۷ مورد دیگر

Christian von Scheve is a Professor of Sociology and Head of the Department of Sociology of Emotions at Freie Universität Berlin. He also serves on the board of the Collaborative Research Center (SFB) 1171 'Affective Societies' and is a Research Fellow at the German Institute for Economic Research (DIW Berlin). His academic journey includes positions as a Research Professor at DIW Berlin (2011-2014), Junior Professor at Freie Universität Berlin (2008-2014), and Assistant Professor at the University of Vienna (2007-2008). His research examines the interplay between culture, social structures, and emotions, with emphasis on: The social/cultural constitution of emotions and affective experiences Emotional dimensions of economic action Human/non-human social interaction He employs diverse methodologies including surveys, interviews, and experiments. His recent publications (2022-2025) predominantly explore affective polarization , refugee integration , and the role of emotions in political discourse, utilizing interdisciplinary approaches spanning sociology, neuroscience, and political science. A consistent theme is how emotions shape social cohesion and conflict in contemporary societies. He holds key editorial roles including Co-Editor of Soziale Welt , Associate Editor of Emotion Review , and Editorial Board positions for multiple book series on affective societies and emotion research. He actively advises Master's students, requiring thesis proposals to be submitted six weeks before registration deadlines. His research is embedded in collaborative projects like SFB 1171 'Affective Societies' and the 'Social Cohesion and Civil Society' initiative.

Anna Bonifaziمشاهده پروفایل

استاد

• Discourse Analysis
• Pragmatics
• Cognitive Linguistics
• +۴ مورد دیگر

Prof. Anna Bonifazi holds a Professorship in Discourse Studies at the Department of Linguistics, University of Cologne. Her research spans Discourse Analysis, Pragmatics, Cognitive Linguistics, and Multimodal Communication with a focus on Ancient Greek Linguistics and Oral Epic traditions. She investigates phenomena like anaphoric cohesion in long texts, multimodal storytelling in film and oral traditions, and ancient Greek particles' discursive functions. Her work explores how multimodal elements (e.g., visual, musical, gestural) interact in communication, particularly analyzing films (e.g., mystery genres), ancient texts (e.g., Homeric epics), and South Slavic oral narratives. She examines cross-modal iconicity, viewpoint blending, and the cognitive underpinnings of discourse structures. Recent publications address topics like anaphoric strategies in crime stories and syntactic patterns in ancient Greek conversational frameworks. Prof. Bonifazi's research often bridges classical philology and modern cognitive theories, emphasizing embodied cognition and the interplay between language and other semiotic systems. She collaborates internationally on projects involving gesture analysis in storytelling and ancient papyrological studies. Her interdisciplinary work integrates linguistics with musicology, film studies, and cognitive science. Administratively, she oversees the Discourse Studies research group at Cologne and mentors assistants like Dr. Sandra Debreslioska and Madeleine Frings. Her lab focuses on multimodal discourse analysis using experimental and corpus-based methods.

Almut Sophia Koepkeمشاهده پروفایل

پژوهشگر

• Multi-Modal Learning
• Computer Vision
• Audio-Visual Processing
• +۳ مورد دیگر

Dr. Almut Sophia Koepke is a junior research group leader and TUM Junior Fellow at the Technical University of Munich (TUM) and University of Tübingen. She leads the multi-modal learning research group focusing on video understanding through sound, vision, and text integration. University: Technical University of Munich School: TUM School of Computation, Information and Technology Department: Informatics 9 Academic Rank: Researcher Her research spans multi-modal learning, audio-visual foundation models, and cross-modal attention mechanisms. Key themes include: Advancing zero-shot learning through language-guided audio-visual models Developing explainable AI systems via attention pattern translation in VQA Exploring temporal understanding in video-adverb retrieval Building robust multi-modal representations for self-driving applications Recent publications analyze foundation model capabilities in audio-visual tasks (ICCV 2025), temporal reasoning (ACMMM 2024), and cross-modal attention frameworks (ECCV 2022). She co-organizes CVPR workshops on foundation model evaluations and serves as area chair/reviewer for major conferences.

• Virtual Reality
• Human-Computer Interaction
• Haptics
• +۷ مورد دیگر

Lung-Pan Cheng is an Associate Professor in the Department of Computer Science and Information Engineering at National Taiwan University. His research focuses on creating innovative interfaces that bridge physical and virtual realities, with particular emphasis on virtual reality systems, haptic feedback mechanisms, and perceptual illusions. Dr. Cheng's work explores how to create more immersive and believable virtual experiences through: Novel haptic feedback systems that simulate physical interactions in virtual environments Real walking techniques that overcome physical space limitations in VR Perceptual illusions that enhance the sense of presence in virtual worlds Human actuation approaches that leverage people as part of the VR infrastructure Optical illusions applied to digital media and gaming experiences Advanced fabrication techniques for interactive physical objects His recent publications (2022-2024) demonstrate a continued trajectory of innovation in VR interaction techniques, with work focusing on directional force feedback, infinite vertical navigation, and the integration of optical illusions into virtual experiences. Dr. Cheng's research consistently combines hardware innovation with perceptual psychology to create compelling user experiences that push the boundaries of virtual environments. Dr. Cheng has received notable recognition for his work: Best Paper Award at CHI 2022 for 'AirRacket: Perceptual Design of Ungrounded, Directional Force Feedback to Improve Virtual Racket Sports Experiences' SIC People's Choice Award at UIST 2022 for 'Garnish into Thin Air' His research has been featured in media outlets including MIT News and New Scientist, indicating broader impact beyond academic circles. Dr. Cheng maintains active collaborations with researchers worldwide, as evidenced by his international co-authorship patterns across multiple disciplines including computer science, psychology, and engineering.

• Data Visualization
• Immersive Analytics
• Human-Computer Interaction
• +۳ مورد دیگر

Sarah Goodwin is an academic affiliated with Monash University in Australia, specializing in data visualization, immersive analytics, and human-computer interaction. She holds a PhD in Visualisation for Household Energy Analysis from City University London (2015). Her research focuses on developing innovative visualization techniques for complex data, particularly in energy systems, healthcare, and geographic information. Key contributions include the Australian Cancer Atlas project (2024), which addressed geostatistical uncertainty visualization, and work on mixed-reality technologies embedding human values (2025). She collaborates extensively with researchers like Tim Dwyer and leads the Data Visualisation and Immersive Analytics Research Lab at Monash. Her publications span journals like IEEE Transactions on Visualization and Computer Graphics and conferences such as CHI and IEEE VAST. Research highlights include gaze analytics tools (VETA), tangible immersive systems (Uplift), and energy consumption visualization frameworks.

Federico Visiمشاهده پروفایل

استاد مهمان

• gesture in music
• motion-sensing technologies
• interactive machine learning
• +۴ مورد دیگر

Federico Visi (he/they) serves as Guest Faculty in the Sound Studies and Sonic Arts Master's program at Berlin University of the Arts. Based in Berlin, Germany, Visi is a researcher, composer, and performer whose work bridges technology and artistic expression through innovative musical interfaces and performance systems. Visi completed doctoral research on instrumental music and body movement at the Interdisciplinary Centre for Computer Music Research (ICCMR), University of Plymouth, UK. They have held postdoctoral positions at Luleå University of Technology (Sweden) and Goldsmiths, University of London (UK), establishing a foundation for their interdisciplinary approach to music technology. Visi's research focuses on gesture in music, motion-sensing technologies, interactive machine learning, and embodied interaction. Their work explores how body movement and physiological signals can be harnessed in electronic music creation through both theoretical frameworks and practical implementations. They have developed novel instruments like the Sophtar and biosignal-based performance systems that translate physiological data into sound. Recent scholarly output reveals a trajectory toward increasingly sophisticated integration of machine learning in musical contexts, with significant contributions spanning computer music, psychology, and human-computer interaction domains. Visi's publications demonstrate how algorithmic processes can be embedded in musical instruments to create new forms of musical expression and co-creativity between humans and machines. As an active member of the research community, Visi co-edited a thematic issue of Organised Sound on 'Embedding Algorithms in Music and Sound Art' and organized the Embedding Algorithms Workshop at Berlin University of the Arts. They contribute to the Wilding AI collective that explores creative applications of AI in spatial audio environments. Visi releases music under the moniker AQAXA, combining conventional electronic music production with machine learning exploration of personal sonic memories. Their work has been supported by the European Research Council, Swedish Research Council, Boström Fund, and Helge Ax:son Johnsons foundation.

• Natural Language Processing
• Computational Linguistics
• Machine Learning
• +۴ مورد دیگر

Dr. Lea Frermann is an active researcher in computational linguistics and natural language processing, with a focus on media framing analysis, fairness in AI, and Bayesian modeling of semantic categories. Her work bridges machine learning with social science applications, particularly in political discourse and climate communication contexts. PhD in Bayesian models of category acquisition (University of Edinburgh, 2017) Key collaborations with University of Melbourne, ACL, EMNLP, and CoNLL communities Research emphasizes: Media framing analysis across cultures Explainable AI for bias detection Bayesian approaches to language understanding Word association modeling for value systems Computational methods for political discourse analysis Applications in mental health support forums Recent publications focus on large language models' limitations in hierarchical reasoning, multimodal categorization, and systematic fairness evaluation frameworks. Collaborations show strong connections with researchers like Timothy Baldwin, Trevor Cohn, and Omri Abend.

• Human-Computer Interaction (HCI)
• Tangible User Interfaces (TUIs)
• Smart Home Systems
• +۳ مورد دیگر

Michael B. Chamunorwa is a Research and Design Engineer and PhD candidate at the University of Oldenburg's Department of Computing Science (School II), specializing in Media Informatics and Multimedia Systems. His research focuses on designing user interfaces embedded in everyday objects for smart home control, exploring embodied interaction and repurposing household items as smart home interfaces. He holds a Bachelor of Technology in Software Engineering and a Master's in Computer Science from the Namibia University of Science and Technology. Michael has taught as a tutor and project supervisor in courses such as 'Experiments and Studies' and 'Makers’ Lab - Things that Think', supervising projects like 'Rich Interactive Materials for Everyday Objects in the Home'. His work bridges theoretical research with practical applications, including developing tools for cultural preservation with marginalized communities in Namibia. Key research areas include tangible user interfaces, embodied interaction, and smart home systems. His projects often involve collaborations with industry-standard frameworks and have been published in venues like ACM International Conference on Mobile and Ubiquitous Multimedia (MUM) and Interactive Surfaces and Spaces. Michael's current PhD project investigates secondary affordances of everyday objects to enhance smart home user experiences. He has contributed to open-source tools like the 'Popup Observation Kit' for remote usability testing and the 'Sweet Spots' AR platform for interaction area visualization. He has been actively involved in the Virtual and Augmented Reality Lab (inf174) and the Makers’ Lab, emphasizing hands-on innovation in technology design. His work reflects a commitment to both academic rigor and real-world societal impact through technology.

Mats Küssnerمشاهده پروفایل

پژوهشگر

• Multimodal perception of music
• Music and mental imagery
• 4E music cognition
• +۳ مورد دیگر

Mats Küssner is a Researcher at Humboldt University of Berlin's Department of Musicology, specializing in Transcultural Musicology and Historical Anthropology of Music. Previously, he held a Peter Sowerby Research Associate position at the Royal College of Music in London. He earned his doctorate from King's College London, focusing on cross-modal mappings between sound and visual forms. His work bridges music psychology, cognitive science, and cultural studies, emphasizing how music shapes human thought and emotion through multi-method approaches. Research interests include multimodal perception, music-induced mental imagery, 4E cognition (embodied/embedded/enactive/extended), and performance science. Notable awards include the Aubrey Hickman Award for music psychology research and a teaching excellence award. He teaches courses like 'Diversity in Berlin's Sound Scene' and 'Emotions in Music' at both BA and MA levels. His publications span over 40 peer-reviewed articles across journals like Music & Science , Psychomusicology , and Frontiers in Psychology , with a focus on visual-aural interplay, music cognition disorders (e.g., aphantasia), and cross-cultural performance dynamics. He co-edited the landmark volume Music and Mental Imagery (Routledge, 2022). Recent work explores environmental ecomusicology education and music's role in mitigating social isolation. Küssner leads projects on music-induced emotion prediction using cross-modal correspondences and is part of Berlin's interdisciplinary music psychology scene, collaborating with neuroscientists and cultural anthropologists. His lab employs eye-tracking, EEG, and behavioral experiments to study embodied music cognition processes.

Daniele Cattaneoمشاهده پروفایل

پژوهشگر

• Autonomous Robots
• Deep Learning for Localization
• Sensor Fusion
• +۳ مورد دیگر

Dr. Daniele Cattaneo is a Junior Research Group Leader at the Robot Learning Lab (University of Freiburg, Germany). He specializes in autonomous robotics, deep learning for perception and localization, and sensor fusion. His research focuses on embodiment-agnostic and environment-agnostic systems for robots, with applications in autonomous driving and healthcare robotics. Education: Ph.D. in Computer Science, Università degli Studi di Milano-Bicocca (2016–2020) M.Sc. and B.Sc. in Computer Science, Università degli Studi di Milano-Bicocca (2013–2016, 2010–2013) Research Interests: His work addresses challenges in LiDAR-camera calibration, SLAM (Simultaneous Localization and Mapping), unsupervised domain adaptation, and multimodal fusion for robust perception. Key projects include CMRNext (LiDAR-camera matching), Syn-Mediverse (healthcare scene understanding), and Continual SLAM (long-term autonomy). Awards & Grants: He leads funded projects like AI-Drive (next-gen autonomous driving algorithms) and iSUOR (operating room video analysis). Collaborations include work with the AIS Group and Robotic Learning Lab . Students & Labs: Supervises 12+ students in topics like LiDAR localization, HD maps, and radar-based navigation. Active in the Robot Learning Lab at Freiburg, contributing to open-source datasets and tools for robotics research.

• Neuromorphic Computing
• Embodied Artificial Intelligence
• Robotics
• +۶ مورد دیگر

Dr. Yulia Sandamirskaya is the Head of Research Center "Cognitive Computing in Life Sciences" at Zurich University of Applied Sciences (ZHAW), focusing on neuromorphic computing applications for embodied artificial intelligence. Her work bridges computational neuroscience and robotics, emphasizing neural-dynamic architectures for real-time decision-making, learning, and sensorimotor integration in autonomous agents. Key Research Areas: Neuromorphic hardware, dynamic neural fields, spiking neural networks, spatial language modeling, and autonomous sequence generation. Projects: Developed controllers for UAVs and robotic arms using event-based vision sensors, explored on-chip unsupervised learning, and designed models for spatial language interpretation in robots. Scientific Contributions: Her publications span robotics conferences and journals like Science Robotics and Frontiers in Neurorobotics , addressing topics such as path integration, obstacle avoidance, and cognitive architectures. Recent work (2024) includes visual odometry with resonator networks and hyperdimensional scene factorization on neuromorphic chips. Advising: Supervised multiple MSc theses at ETH Zurich and NSC/INI programs, mentoring students on neuromorphic navigation, spiking networks, and tactile learning. Collaborated with institutions like ETH Zurich, University of Queensland, and INI Bochum. Labs & Collaborations: Leads the "Neuromorphic Computing Applications: Embodied AI" group at ZHAW, partnering with INIvation (Zurich) and Jörg Conradt (KTH) on neuromorphic hardware implementations. Projects integrate cognitive models with robotic platforms, emphasizing energy efficiency and low-latency interaction.

• Continual Learning
• Few-Shot Learning
• Domain Adaptation
• +۷ مورد دیگر

Mahardhika Pratama is a Professor in the Department of Computer Science at Universitas Indonesia's Faculty of Computer Science, where he leads research in machine learning and artificial intelligence. His work bridges theoretical advancements with practical applications across various domains including time series analysis, autonomous systems, and resource-constrained environments. Pratama's research focuses on overcoming fundamental challenges in machine learning systems, particularly in the areas of continual learning and few-shot learning. His work addresses the critical problem of catastrophic forgetting in neural networks while developing efficient learning systems that can adapt to new tasks with minimal data. His publications reveal a strong emphasis on developing practical solutions for real-world applications where data is scarce or constantly evolving. Analysis of his recent publications (2023-2025) shows a clear research trajectory toward more sophisticated approaches for continual learning under data scarcity, with increasing focus on transformer architectures, multi-agent reinforcement learning, and cross-domain adaptation techniques. His work demonstrates a consistent pattern of addressing both theoretical foundations and practical implementations of adaptive learning systems. His research has been supported through numerous collaborative projects with international institutions including UNSW Canberra, Swinburne University of Technology, and University of Alberta, reflecting the global impact of his work in the machine learning community.

Alfred Newenمشاهده پروفایل

استاد

• Philosophy of Mind
• Cognitive Science
• Situated Cognition
• +۵ مورد دیگر

Prof. Dr. Alfred Newen is a Professor of Philosophy at Ruhr-Universität Bochum since 2007 (W3 since 2010), specializing in philosophy of mind and cognition. He leads the Research Training Group 'Situated Cognition' (DFG-funded) and the Center for Mind and Cognition. His research focuses on embodied cognition, consciousness studies, animal cognition, and emotion attribution. He has held visiting positions at Oxford, Berkeley, and UC San Francisco. Notable awards include the Bennigsen-Förderpreis and the Psychiatry Philosophy Prize. Education: PhD from University of Bonn (1994), Habilitation in Philosophy (2002) Leadership roles: Vice President (2016–2018) and President (2018–2020) of the German Society for Cognitive Science (GK) Key Projects: FOR 2812 'Constructing Scenarios of the Past', ALARM Theory of Consciousness Research interests span animal consciousness, episodic memory, predictive processing, and interdisciplinary cognitive science. He co-authored The Oxford Handbook of 4E Cognition (2018) and frequently publishes in journals like Cognition and Philosophical Psychology . Awards highlight contributions to cognitive science and philosophy, including collaborative work with neuroscientists and empirical researchers.

Sebastian Otteمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Recurrent Neural Networks
• +۱۲ مورد دیگر

Sebastian Otte is a Professor at the Institute for Robotics and Cognitive Systems at the University of Lübeck, where he leads the Adaptive AI research group. Prior to this, he was a postdoctoral researcher and substitute professor at the University of Tübingen, contributing significantly to the Cognitive Modeling and Distributed Intelligence groups. University of Lübeck, Professor (since 2023) University of Tübingen, Postdoc and Substitute Professor (2016–2023) Centrum Wiskunde & Informatica (CWI), Humboldt Fellow (2022–2023) His research focuses on recurrent and spiking neural networks, bio-inspired computing, efficient learning, and adaptive AI systems. He explores how neural models can perform online learning, handle multiple time scales, and solve complex cognitive tasks such as binding, prediction, and motor control. His work bridges machine learning with cognitive science and robotics. The recent publications show a strong trend toward physics-informed neural networks, finite volume methods for PDE modeling, and explainable AI via counterfactual reasoning. His work integrates deep learning with scientific computing, emphasizing robust, interpretable, and efficient models for real-world applications. Scientific awards include: Best Paper Award at ICANN 2019 Humboldt Research Fellowship Editor's Highlight in Water Resources Research He has supervised over 70 bachelor’s and master’s theses and actively mentors students in areas such as spiking neural networks, reservoir computing, and robotics. His teaching includes core computer science and advanced neural network courses. He has been involved in research projects with industry partners like Daimler AG and Mercedes-Benz AG. Otte leads the Adaptive AI research group, which focuses on developing next-generation AI systems that learn efficiently, adapt dynamically, and model complex cognitive and physical processes using biologically inspired architectures.