جست‌وجوی استاد و پژوهشگر

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

Juergen Schmidhuber is Associate Professor at the Faculty of Informatics of Università della Svizzera italiana and a leading researcher at the Dalle Molle Institute for Artificial Intelligence (IDSIA USI-SUPSI). He is also Chief Scientist at NNAISENSE, a company dedicated to building practical general-purpose AI. His work has profoundly influenced modern artificial intelligence, particularly through the development of Long Short-Term Memory (LSTM) networks in 1991, now deployed across billions of devices for speech recognition, machine translation, and virtual assistants. His research interests span Artificial Intelligence, Deep Learning, Recurrent Neural Networks, Universal AI, Meta-Learning, Algorithmic Information Theory, Artificial Curiosity, Robotics , and Low-Complexity Art . He has pioneered mathematically rigorous frameworks for self-improving AI systems and formal theories of creativity and beauty. His work bridges theoretical foundations with real-world applications in computer vision, natural language processing, and autonomous robotics. The recent articles reflect a consistent trajectory of innovation, combining deep theoretical insights with scalable machine learning architectures. His publications emphasize sequence modeling, universal learning, intrinsic motivation, and computational creativity , demonstrating both foundational contributions and industrial impact. From LSTM to Goedel machines, his work consistently targets the long-term goal of self-improving general AI. Scientific Awards: Numerous awards in AI and machine learning (specific names not listed) Schmidhuber leads a research group at IDSIA, where he mentors students and researchers in advancing the frontiers of AI. His lab has secured significant recognition and industrial collaboration, though specific grants are not detailed. He promotes the 'New AI'—general, sound, and relevant to physics—and continues to explore the convergence of intelligence, computation, and the universe. Labs and Teams: Dalle Molle Institute for Artificial Intelligence (IDSIA USI-SUPSI) NNAISENSE (as Chief Scientist)

Siyu Tangمشاهده پروفایل

استادیار

• Computer Vision
• Machine Learning
• Digital Humans
• +۵ مورد دیگر

Siyu Tang is an Assistant Professor in the Department of Computer Science at ETH Zürich, where she leads the Computer Vision and Learning Group (VLG) at the Institute of Visual Computing. Her research focuses on computational models for human perception and digitalization through computer vision and machine learning. Her educational background includes: PhD in Computer Science, Max Planck Institute for Informatics (2017), supervised by Prof. Bernt Schiele Master of Science in Media Informatics, RWTH Aachen University Bachelor of Science in Computer Science, Zhejiang University, China Dr. Tang specializes in human-centric computer vision, developing statistical models for motion analysis, pose estimation, and digital human creation. Her work integrates machine learning with optimization techniques to enable machines to interpret human activities from visual data, with applications spanning virtual reality, healthcare, and human-computer interaction. Key research thrusts include generative models for content creation, egocentric vision, and human motion synthesis. Her recent publications (2024-2025) demonstrate intense focus on 3D human modeling and neural rendering, with Gaussian splatting emerging as a dominant technique for efficient avatar creation and scene reconstruction. Significant themes include text-driven motion synthesis using diffusion models, relightable avatars, surgical training applications, and egocentric multimodal pretraining. This work bridges computer vision, graphics, and machine learning to advance human digitalization. No scientific awards were mentioned in the provided text. Dr. Tang leads the VLG research group at ETH Zürich, mentoring PhD and Master's students in human-centric AI. She previously secured an early career research grant from the Max Planck Institute for Intelligent Systems to establish her independent research program. Her group actively pursues funding for projects in human motion analysis, 3D reconstruction, and generative modeling, with strong industry and clinical collaborations. The Computer Vision and Learning Group (VLG) operates within ETH's Institute of Visual Computing, maintaining dedicated facilities for motion capture, 3D scanning, and high-performance computing. The team collaborates internationally with institutions like the Max Planck Society and focuses on scalable solutions for real-world human digitalization challenges, including surgical training systems and immersive virtual environments.

Jinjin Guمشاهده پروفایل

استادیار

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

Jinjin Gu is a tenure-track Assistant Professor at Sofia University "St. Kliment Ohridski" 's INSAIT (Institute for Computer Science, Artificial Intelligence, and Technology), leading research on visual cognition and intelligence. Her work spans visual perception, processing, generation, and reasoning. Education: Ph.D. in Electrical and Computer Engineering (2024), University of Sydney B.Sc. in Computer Science and Engineering (2020), Chinese University of Hong Kong, Shenzhen Her research focuses on visual cognition , including agentic systems , diffusion models , GAN architectures , model interpretability , super-resolution , and multimodal vision-language systems . She has developed novel paradigms like HYPIR for diffusion-quality restoration at GAN speeds. Recent publications highlight advancements in image/video restoration , generative modeling , and visual reasoning . Her work addresses critical challenges in model generalization , causal interpretation , and real-world application robustness . Scientific Awards: Stanford University's World's Top 2% Scientists (2024) Yunfan Award at World Artificial Intelligence Conference (WAIC) (2023) She has advised students contributing to TPAMI, CVPR, and ICLR publications, and serves as Area Chair for ICLR 2026, NeurIPS 2025, and ICML 2025.

Jing Zengمشاهده پروفایل

استادیار

• Computational Social Science
• Digital Media Studies
• Communication Science
• +۵ مورد دیگر

Jing Zeng is an Assistant Professor of Computational Communication Science at the University of Zurich, Switzerland. She holds a PhD in Media and Communication from Queensland University of Technology (2017), an MSc in Social Science of the Internet from the Oxford Internet Institute (2013), and a BA in International Communications from the University of Nottingham (2012). Her research focuses on digital platforms, computational social science, AI governance, and misinformation dynamics. She has held academic appointments at Utrecht University (2022–2024) and fellowships at institutions including the Max Planck Institute for the History of Science and the Weizenbaum Institute. Zeng is a leader in digital media research, serving on editorial boards for journals such as Big Data & Society and Convergence , and co-editing the Technology, Power & Society book series. Her work bridges critical platform studies with empirical analyses of conspiracy theories, climate communication, and TikTok culture. Zeng’s research has been recognized through awards including the ICA Computational Methods Interest Group Top Paper (2020) and the Utrecht University Teaching Award (2023). She actively engages in public discourse through media commentaries in The Guardian , The Atlantic , and Science|Business , addressing topics like AI ethics, platform governance, and disinformation. Her current projects explore AI imaginaries, visibility moderation on TikTok, and cross-cultural digital activism. Education: PhD (QUT), MSc (Oxford), BA (Nottingham) Affiliations: Association of Internet Researchers (AoIR Executive Board), IPIE Scientific Network

Sabine Süsstrunkمشاهده پروفایل

استاد

• Computational Imaging
• Computational Photography
• Color Image Processing
• +۴ مورد دیگر

Sabine Süsstrunk is a Full Professor and Director of the Images and Visual Representation Laboratory (IVRL) at EPFL's School of Computer and Communication Sciences. She holds a BS in Scientific Photography from ETH Zürich, MS from Rochester Institute of Technology, and PhD from University of East Anglia. Her career includes positions at Hewlett-Packard Labs and Corbis Corporation. Her research explores computational imaging, computational photography, color processing, computer vision, and image quality. Key interests include near-infrared applications, multispectral imaging, and computational aesthetics. Her work bridges hardware and software solutions for imaging challenges. Publications demonstrate consistent focus on advancing generative models (diffusion models, neural cellular automata), 3D reconstruction (NeRF variants), and media integrity (DeepFake detection). Recent trends show increased emphasis on 3D vision, robustness in generative AI, and video analysis. Awards & Honors: IS&T/SPIE Electronic Imaging Scientist of the Year (2013) Raymond C. Bowman Teaching Award (2018) EPFL AGEPoly IC Polysphere Award (2020) 8 Best Paper/Demo Awards Fellowships: IEEE, IS&T, ELLIS, AIIA She leads the IVRL lab and advises PhD candidates while serving as President of the Swiss Science Council. Research is supported through competitive grants and industry collaborations.

Nathalie Pignard-Cheynelمشاهده پروفایل

استاد

• Digital Journalism
• Social Media Communication
• Audience Engagement
• +۳ مورد دیگر

Nathalie Pignard-Cheynel is a Full Professor of Journalism and Digital Communication at the University of Neuchâtel since 2020, where she leads cutting-edge research on digital transformations in journalism. Previously, she held academic positions at the University of Neuchâtel (Assistant Professor, 2016-2020), University of Lorraine (2013-2016), and Grenoble 3 University (2005-2013), where she earned her doctorate in Information and Communication Sciences (2004). Doctorate in Information and Communication Sciences, University of Grenoble 3 (2004) Full Professor of Journalism and Digital Communication, University of Neuchâtel (2020-present) Assistant Professor in Digital Journalism, University of Neuchâtel (2016-2020) Lecturer in Information and Communication Sciences, Grenoble 3 University (2005-2013) Her research focuses on: Mutations in journalistic practices during digital transformations Social media usage by journalists, media, and audiences Participatory journalism and media-audience relationships Journalism and data practices Disinformation content dissemination and reception Platformization of information and algorithmic roles Digital formats analysis in journalism She has led multiple funded research projects including: PANDA (2023-2026, CHF 499,986) on pandemic data communication #sad2 (2021-2022, CHF 138,460) on disinformation architectures LINC (2018-2021, CHF 184,586) on local journalism innovation International collaborations on pandemic communication and digital media Her teaching includes: Digital technology courses for economics students NewsLab projects for journalism master's students Advanced seminars on digital media and communication Innovative journalistic format production She serves in leadership roles for: President of the Scientific Council, Initiative for Media Innovation (2018-2022) Board Member, Hirondelle Foundation (2021-present) Editorial Board Member, Cahiers du journalisme (2020-present) Qualis Commission, University of Neuchâtel (2019-present)

Aravind Rajeswaranمشاهده پروفایل

پژوهشگر

• Reinforcement Learning
• Representation Learning
• World Models
• +۵ مورد دیگر

Aravind Rajeswaran is a Research Scientist at Meta AI (FAIR) and Visiting PostDoc/Collaborator at Berkeley AI Research Lab (BAIR) at UC Berkeley's College of Engineering, Department of Electrical Engineering and Computer Sciences. He completed his PhD in Computer Science at the University of Washington under Profs. Sham Kakade and Emo Todorov, with additional collaborations with Sergey Levine and Chelsea Finn, and previously earned his bachelor's degree with the best undergraduate thesis award from IIT Madras working with Balaraman Ravindran. His research focuses on building generalist AI agents that operate in open worlds, combining reinforcement learning, representation learning, and world models. Key projects include Locate 3D for real-world object localization, OpenEQA for embodied question answering with foundation models, VC-1 as an artificial visual cortex for embodied intelligence, and R3M as a universal visual representation for robot manipulation. His work demonstrates how pre-trained visual representations can significantly enhance robotic capabilities with minimal supervision. Rajeswaran's publication record shows consistent high-impact contributions across premier AI conferences including NeurIPS, ICML, CVPR, and RSS from 2018 through 2025, with research spanning reinforcement learning, representation learning, robotics, and computer vision. His work on Decision Transformer demonstrated how sequence modeling frameworks can effectively train reinforcement learning policies. Best Paper Award, Scaling Robot Learning Workshop at ICRA 2022 best undergraduate thesis award from IIT Madras As an educator and mentor, Rajeswaran has guided numerous PhD students who have gone on to positions at Stanford, MIT, CMU, Berkeley, and top AI companies including Meta, DeepMind, and Anthropic. He designed and co-taught the Deep Reinforcement Learning course (CSE599G) at UW in 2018, with materials adopted by courses at MIT and CMU, and served as lead TA for Machine Learning for Big Data (CSE547). His research has been supported through his role as Principal Investigator for the Cortex Team at FAIR.

• Crisis Communications
• Sustainability Literacy
• Hospitality Management
• +۳ مورد دیگر

Dr. Laura Zizka is a Professor at the EHL Hospitality Business School, part of the HES-SO university network. She specializes in higher education strategies, crisis communication, and sustainability in hospitality and STEM sectors. Her research bridges academic theory with industry practice, focusing on organizational resilience during crises, digital education transformation post-pandemic, and embedding sustainability literacy in curricula. Education**: BSc HES-SO in Hospitality and Tourism Management Research Themes**: Crisis communication strategies in tourism and hospitality Digital transformation in higher education Pro-environmental behavior in hospitality operations Sustainability integration in STEM and business programs Her work emphasizes bridging educational practices with real-world challenges, such as pandemic communication, stakeholder engagement in sustainability, and employability skills for STEM graduates. Recent studies include analyzing Swiss hoteliers' pandemic communication evolution and exploring AI's role in academic writing through Microsoft Copilot case studies. Grants & Projects**: HES-SO Rectorate-funded project (2019–2020) on destination image and pictorial content impact (CHF 99,000) Longitudinal studies on student/faculty perceptions of digital education (2020–2023) Dr. Zizka collaborates with industry partners like KITRO (food waste tech) and actively contributes to conferences on topics ranging from trauma-informed pedagogy to blended learning models. She advocates for holistic sustainability education and has advised on CSR communication strategies for airlines and hospitality firms.

• Artificial Intelligence
• Embodied AI
• Robotics
• +۴ مورد دیگر

Roozbeh Mottaghi is a Senior AI Research Scientist Manager at Meta's Fundamental AI Research (FAIR) division and an Affiliate Associate Professor at the Paul G. Allen School of Computer Science & Engineering, University of Washington. His career spans roles as Research Manager at the Allen Institute for AI and Postdoctoral Researcher at Stanford University. He holds a Ph.D. in Computer Science from UCLA, advised by Alan Yuille, and advanced degrees from Simon Fraser University, Georgia Tech, and a B.Sc. from Sharif University of Technology. Ph.D., Computer Science, UCLA (2016) M.Sc., Computer Science, Simon Fraser University M.Sc., Electrical Engineering, Georgia Institute of Technology B.Sc., Computer Engineering, Sharif University of Technology His research focuses on Embodied AI, Robotics, Computer Vision, and Multimodal Learning, with key contributions to human-robot collaboration benchmarks (PARTNR), 3D scene understanding, and adaptive navigation systems. Recent work explores zero-shot manipulation via video tracking (Track2Act) and lifelong navigation benchmarks (GOAT-Bench). Publications span 3D vision, reinforcement learning, and visual reasoning, including NeurIPS 2022 Outstanding Paper Award for "Ask4Help" and leadership in organizing challenges at CVPR and ICCV workshops. He advises students and interns who have transitioned to leading institutions like AI2, Stanford, and Brown University.

Julia Gelshornمشاهده پروفایل

استاد

• Contemporary Art (19th-21st centuries)
• French 18th-century Art and Theory
• Artistic Appropriation
• +۵ مورد دیگر

Julia Gelshorn is a full professor of modern and contemporary art history at the University of Fribourg , Switzerland, since 2013. She specializes in strategies of appropriation, repetition, and translation in art, with a focus on 21st-century practices and 18th-century French art theory. Her research explores artistic subjectivity, realism, and the intersection of art, politics, and economy. Education: Art History, Theater Science, and Italian Literature at the Universities of Cologne and Bern. Key Roles: Post-doctoral fellow at the German Center for Art History (2006-2008); visiting professor at HfG Karlsruhe (2008-2010); professor at Universities of Vienna (2010-2011) and Hamburg (2011-2013). Research Interests center on: (1) artistic appropriation as a critical and affective tool; (2) realisms across historical contexts; (3) artist interviews as legible texts; (4) art’s engagement with political and economic systems; (5) theoretical frameworks for visual culture. Her current Real Abstractions project (2023-2027) rethinks realism through social abstractions like financialization and digital networks. Scientific Contributions include the Lazarus Prize from the University of Bern’s Faculty of Humanities (2003) for her dissertation on Richter and Polke. Her publications span books like Aneignung und Wiederholung (2012) and edited volumes on artists such as Jean Tinguely (2016), while her recent articles address Martin Kippenberger, Rosemarie Trockel, and Benjamin Buchloh’s historiography. Notable Projects include the completed SNSF-funded Cinema in Art and Literature (2016) and the ongoing Real Abstractions initiative, which also involves a traveling exhibition and interdisciplinary workshops.

Davide Scaramuzzaمشاهده پروفایل

استاد

• Robotics
• Computer Vision
• Autonomous Navigation
• +۴ مورد دیگر

Davide Scaramuzza is a Professor and Director of the Robotics and Perception Group at the University of Zurich. He holds a Ph.D. from ETH Zurich and has conducted postdoctoral research at the University of Pennsylvania and Stanford. His research focuses on autonomous drone navigation using visual and event-based sensors, leading to breakthroughs like AI drones outperforming human pilots in racing (Nature 2023). He pioneered algorithms for Mars helicopter navigation and developed the PX4 autopilot system. Key awards include the Kiyo-Tomiyasu IEEE Technical Field Award (2024), ERC Consolidator Grant (2019), and multiple best paper awards. His entrepreneurial ventures include co-founding Zurich-Eye (later Meta Zurich) and SUIND for agricultural drones. He co-authored the textbook Introduction to Autonomous Mobile Robots , widely used in academia. Research spans event camera algorithms, visual-inertial SLAM, and reinforcement learning for agile flight. His lab's work is featured in IEEE Spectrum, The Guardian, and Forbes. He advises UN initiatives on AI for disaster response and nuclear safety. Current projects include Graph-Generating State Space Models (CVPR 2024) and event-based vision for automotive systems (Nature 2024).

Emily Crossمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Social Neuroscience
• Embodied Cognition
• +۵ مورد دیگر

Emily Cross is a Full Professor at the Department of Humanities, Social and Political Sciences at ETH Zurich, leading the Social Brain Sciences Professorship since spring 2023. She previously held professorships at Bangor University (Wales), University of Glasgow (Scotland), Macquarie University (Australia), and Western Sydney University's MARCS Institute (Australia). Her research centers on how embodied experience shapes social learning and perception across diverse contexts. Key contributions include identifying neural signatures of embodied expertise using dancers, developing embodied neuroaesthetics theory, uncovering neurocognitive foundations of visual learning across lifespans, and pioneering paradigms for human-robot social engagement. Her interdisciplinary approach bridges technology, performing/visual arts, and social sciences to explore experience-dependent plasticity at brain and behavioral levels. Recent publications (2024-2025) demonstrate intense focus on human-robot interaction dynamics, aesthetic movement perception, and context-dependent social cognition. Work increasingly examines self-disclosure mechanisms to robots, cultural influences on robot acceptance, and neural correlates of movement synchrony, reflecting her expanding influence at the neuroscience-robotics intersection. Scientific awards include: Philip Leverhulme Prize for Psychology Jacob Bronowski Award from British Science Foundation Young Talent Award from Dutch Neuroscience Society RoboHub and Insight Analytics top women in robotics listings Australia’s Superstars of STEM (2022) Cross passionately trains next-generation scientists with emphasis on research ethics. Her work attracts major funding from ERC, NIH, Fulbright Commission, ESRC, EPSRC, and UK Ministry of Defence. She serves on UNESCO’s International Bioethics Committee (co-rapporteur for neurotechnology ethics report) and as Associate Editor for International Journal of Social Robotics. She leads ETH Zurich's dynamic Social Brain Sciences group, which embraces interdisciplinarity through research paradigms bridging technology, performing/visual arts, and biological/social sciences, while maintaining active roles in editorial boards and conference committees including Intelligent Virtual Agents and Affective Computing meetings.

Sophie Schwartzمشاهده پروفایل

استاد

• Sleep Neuroscience
• Cognitive Neuroscience
• Neuroimaging (fMRI, hd-EEG, MEG)
• +۷ مورد دیگر

Prof. Sophie Schwartz is a leading neuroscientist at the University of Geneva , where she heads the Sleep & Cognition Lab within the Faculty of Medicine . Her research integrates neuroimaging (fMRI, hd-EEG, MEG) , behavioral testing , and computational modeling to unravel the neural mechanisms underlying memory consolidation , emotion processing , and dreaming during sleep, while also developing clinical interventions to enhance sleep in neurological and psychiatric disorders.

• Data Ethics
• Machine Ethics
• Artificial Intelligence
• +۷ مورد دیگر

Sylvie Delacroix is the Inaugural Jeff Price Chair in Digital Law and Director of the Centre for Data Futures at King's College London. She is also a Visiting Professor at Tohoku University, focusing on bridging theory and practice in ethics and public policy initiatives. Her research spans Data & machine ethics Ethical agency and habit Social sustainability of data ecosystems Participatory infrastructure for AI systems Uncertainty communication in LLMs Legal theory and digital law Recent publications address LLM interfaces as transitional spaces for democratic revival and sustainable data rivers in generative AI. Her work has attracted significant grant funding from the Patrick J. McGovern Foundation, Wellcome Trust, and Omidyar Network. Scientific awards include the Leverhulme Prize Peter Birks 2d Prize for Outstanding Legal Scholarship Montgomery Fellowship at Dartmouth College She supervises PhD research on large language models and uncertainty communication, as well as habit in ethical lives. Her policy contributions include advising the Law Society of England and Wales on algorithmic justice systems.

• Affective Neuroscience
• Emotional Processing
• Behavioral Psychology
• +۳ مورد دیگر

David Sander is a Professor at the Faculty of Psychology and Educational Sciences, University of Geneva, affiliated with the Department of Psychology and the Centre interfacultaire en sciences affectives. He leads the Emergence et expression de l'émotion (E3 Lab) research group. His work focuses on affective neuroscience, emotional processing, and their applications in health, education, and social behavior. With 185 publications and 141 supervised works, his research spans topics like emotion appraisal mechanisms, reward systems, and developmental psychology. Key themes include neural correlates of emotional responses (e.g., amygdala activity), behavioral effects of sensory stimuli (odors, visual cues), and interventions addressing mental health and physical activity. His studies employ fMRI, EEG, and clinical trials, often integrating interdisciplinary methods. Notable contributions include frameworks for understanding emotional valence, appraisal-driven brain processes, and the role of affect in decision-making. Recent articles highlight innovative methodologies (e.g., virtual reality for pediatric pain management) and societal impacts (e.g., materialism’s influence on consumer behavior). His work bridges basic science and applied contexts, such as improving education through emotional development strategies and addressing obesity via neural mechanisms.