جستجوی استاد راهنمای دانشگاهی

Silvestro Miceraمشاهده پروفایل

استاد

• Neural Engineering
• Neuroprosthetics
• Robotics
• +۳ مورد دیگر

Silvestro Micera is a Full Professor at the Swiss Federal Institute of Technology Lausanne (EPFL) and holds the Bertarelli Foundation Chair in Translational Neuroengineering. He directs the Translational Neural Engineering Laboratory and teaches courses including Neural signals and signal processing and Translational neuroengineering . His research bridges neural interfaces, robotics, and neuroprosthetics to restore motor functions in spinal cord injuries, stroke, and amputations. Micera's research integrates implantable neural interfaces, robotic rehabilitation, and hybrid neuro-prosthetic systems. Key focus areas include: Robotic neurorehabilitation for mobility restoration Neural control mechanisms in movement CNS/PNS neural interface development Bioelectronic modulation for sensory feedback His recent publications emphasize machine learning-driven motor recovery prediction, closed-loop sensory feedback systems, and minimally invasive neuroprosthetics. Trends include AI-optimized stimulation protocols, multimodal data fusion for rehabilitation, and clinical translation of neural bypass technologies. Awards: IEEE EMBS Early Career Achievement Award (2009) IEEE EMBS Technical Achievement Award (2021) Micera leads EU-funded projects such as TIME, CLONS, and NeuWalk, focusing on neural prostheses. He advises 8 current and 18 former PhD students in neuroengineering. His lab collaborates with MIT, Harvard, and industry partners (e.g., Plexon) to advance translational neurotechnologies.

Alexander Mathisمشاهده پروفایل

استادیار

• Computational Neuroscience
• Machine Learning
• Sensorimotor Control
• +۶ مورد دیگر

Alexander Mathis is an Assistant Professor at the École Polytechnique Fédérale de Lausanne (EPFL) in the Brain Mind Institute (School of Life Sciences). His research bridges computational neuroscience and machine learning to decode sensorimotor behaviors and develop AI tools for behavioral analysis. Pure Mathematics MSc, Ludwig Maximilians University Munich PhD in Computational Neuroscience, Ludwig Maximilians University Munich His work focuses on understanding how the brain generates behavior through computational models and algorithms. Key contributions include the DeepLabCut toolbox, hBehaveMAE , and other frameworks for pose estimation, action segmentation, and brain-inspired AI. His group also explores proprioception, motor control, and neural coding theories. Recent publications include unsupervised hierarchical behavior modeling via masked autoencoders (ECCV 2024), synthetic basketball benchmarks (Shot7M2), and extensions of BABEL into hBABEL. These works highlight his interest in temporal hierarchies in behavior and scalable AI solutions for neuroscience. Scientific Honors Robert Bing Prize (2024) Eric Kandel Young Neuroscientists Prize (2023) Frontiers of Science Award (2023) Marie Skłodowska-Curie Postdoctoral Fellowship Studienstiftung des deutschen Volkes scholarship He advises PhD candidates in neuroscience and life sciences, leads courses on brain-like computation and software engineering for life sciences , and collaborates across AI4Science initiatives. His group actively participates in competitions, such as NeurIPS' MyoChallenge, where brain-inspired reinforcement learning algorithms have won awards.

Giacomo Indiveriمشاهده پروفایل

استاد

• Neuroscience
• Computer Science
• Machine Learning
• +۶ مورد دیگر

Giacomo Indiveri is a dual Professor at the Faculty of Science of the University of Zurich and the Department of Information Technology and Electrical Engineering of ETH Zurich . He serves as the Director of the Institute of Neuroinformatics at both institutions. Indiveri holds an M.Sc. in Electrical Engineering (1992) from the University of Genoa and a Ph.D. in Computer Science (2004) from the same university. Primary Affiliation: University of Zurich (Faculty of Science, Institute of Neuroinformatics) Secondary Affiliation: ETH Zurich (Department of Information Technology and Electrical Engineering) Indiveri's research bridges neuroscience , computer science , and machine learning to develop neuromorphic cognitive systems . His work focuses on spike-based learning , recurrent neural networks , and analog/digital circuit design for real-time sensory-motor systems . He integrates emerging memory technologies into fault-tolerant event-based architectures, enabling brain-inspired computing paradigms in applications like robotics and medical monitoring. His recent publications emphasize neuromorphic hardware for epileptic seizure detection , spiking neural networks in robotic painting , and scalable processors with on-chip learning . These works explore biologically plausible neurons , delay lines , and memory arrays for temporal processing, with applications in healthcare , edge computing , and adaptive control . Scientific Awards & Recognitions: 2021 IEEE Biomedical Circuits and Systems Best Paper Award Senior Member of IEEE Society ERC Fellow with three European Research Council grants Indiveri's group at the Institute of Neuroinformatics develops event-based systems for real-world validation of brain-inspired computing. His work includes multi-core processors , feedback optimizers , and dynamic routing architectures , supported by grants for advancing neuromorphic technologies .

Elisa Donatiمشاهده پروفایل

پژوهشگر

• Neuromorphic Engineering
• Biomedical Signal Processing
• Wearable Healthcare Technologies
• +۵ مورد دیگر

Dr. Elisa Donati is a researcher and independent group leader at the Institute of Neuroinformatics , affiliated with both the University of Zurich and the Swiss Federal Institute of Technology Zurich . Her work bridges neuromorphic engineering, biomedical signal processing, and wearable healthcare technologies, with a focus on creating brain-inspired systems for neuroprosthetics and rehabilitation. Affiliation: Institute of Neuroinformatics, University of Zurich & ETH Zurich Email: elisa@ini.uzh.ch Elisa’s research emphasizes developing neuromorphic signal processing strategies for wearable and embedded systems, enabling real-time closed-loop interactions with the nervous system. She specializes in translating neuroscience insights into energy-efficient technologies for digital health applications, including neuroprosthetics and personalized biomedical devices using neuromorphic hardware. Her recent publications (2024–2025) highlight advancements in gesture recognition via EMG and event-based systems, neuromorphic heart rate monitoring , and spiking neural network architectures . These works span biomedical signal processing, low-power computing, and adaptive algorithms, reflecting her commitment to robust, real-time, and brain-inspired solutions for healthcare. Elisa’s contributions to neuromorphic computing are evident in her exploration of heterogeneous population encoding , event-driven processing , and ultra-low-power microcontrollers . Her projects often integrate wearable systems with neuroscience, aiming to improve prosthetic control and rehabilitation technologies .

• 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)

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.

• Exercise Physiology
• Sports Medicine
• Diabetes Management
• +۳ مورد دیگر

Prof. Oliver Faude is a Professor and Researcher at the Department of Motor Performance & Biomechanics within the University of Basel's Department of Sport, Exercise and Health (DSBG). His research focuses on exercise physiology, sports medicine, and the application of physical activity in managing chronic conditions like type 2 diabetes. He supervises doctoral students, including Vivien Hohberg, whose work on telephone-based health coaching for diabetes patients was published in the Journal of Science and Medicine in Sport. Faude collaborates on projects such as the dbcoach intervention, funded by Innosuisse and health insurers, demonstrating how personalized coaching increases physical activity in diabetic populations. His work also extends to musculoskeletal imaging innovations, such as the UMUD web application for ultrasonography data access, and the PrepAir study addressing chemotherapy-induced sensory dysfunction in children. Faude's interdisciplinary approach integrates clinical research, biomechanics, and public health, with a particular emphasis on aging populations and pediatric oncology. He contributes to injury prevention strategies in sports like badminton and soccer, while advancing methodologies for muscle volume assessment via 3D ultrasound and MRI comparisons. Key Projects: dbcoach program, PrepAir study, musculoskeletal imaging tools, agility training for frailty prevention. Grants: Innosuisse, SwissLife Foundation, Voluntary Academic Society of Basel. Students: Vivien Hohberg (PhD). Labs/Teams: Motor Performance & Biomechanics lab, collaborations with Prof. Bart Roelands (Vrije Universiteit Brussel) on overtraining syndrome research.

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.

• Neuroscience
• Metabolism
• Behavioral Neuroscience
• +۳ مورد دیگر

Dr. Paulius Viskaitis is a Researcher affiliated with the Rehabilitation Engineering Lab at ETH Zürich's Department of Health Sciences and Technology. His work focuses on the neurophysiological mechanisms underlying metabolic regulation, motor behavior, and neurological disorders. Key research areas include orexin neuron dynamics, hypothalamic circuitry, and their roles in movement, energy homeostasis, and epilepsy mitigation. His studies integrate experimental neuroscience with engineering approaches, exploring how neural networks encode metabolic states and behavioral outputs. Notable contributions include identifying orexin neurons' roles in blood glucose tracking and seizure suppression. Current research emphasizes translational applications in rehabilitation engineering and neurotherapeutic strategies. Dr. Viskaitis collaborates across disciplines, leveraging mouse models to investigate neural circuits governing feeding, locomotion, and decision-making. His findings bridge basic neuroscience with clinical applications, particularly in metabolic and motor disorders.

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.

Alexander Breussمشاهده پروفایل

پژوهشگر

• Biomedical Engineering
• Robotics in Healthcare
• Sleep Disorders
• +۳ مورد دیگر

Dr. Alexander Breuss is part of the Sensory-Motor Systems Professorship at ETH Zürich, focusing on developing innovative robotic and sensor technologies for medical applications, particularly in sleep disorder treatment and home healthcare. His work integrates biomedical engineering, robotics, and machine learning to address challenges in sleep medicine and cardiovascular diagnostics. Key projects include the Somnomat Care robotic bed for vestibular stimulation and the Somnomat Casa system for nocturnal interventions. His research spans sensorized devices for sleep monitoring, clinical trials for rhythmic movement disorders, and cardiovascular disease prognosis using imaging and hemodynamic analysis. Dr. Breuss collaborates on interdisciplinary projects, combining engineering and clinical insights to advance healthcare technologies. His research interests include the design of medical devices for home environments, non-invasive monitoring systems, and closed-loop robotic systems for therapeutic applications. Notable contributions include lightweight wearable sensors for movement disorders and automated sleep position classification using neural networks. He has published extensively on topics such as pleural effusion in aortic stenosis and ECG-based cardiac prognosis, highlighting his cross-disciplinary approach to biomedical challenges. No scientific awards are explicitly mentioned for Dr. Breuss. His work is centered at the Sensory-Motor Systems Lab, where he contributes to advancing technologies that improve patient care and sleep quality through robotics and sensor innovation.

Kathryn Hess Bellwaldمشاهده پروفایل

استاد

• Algebraic Topology
• Homotopy Theory
• Neuroscience
• +۴ مورد دیگر

Kathryn Hess Bellwald is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL) in both the School of Life Sciences and School of Basic Sciences . She leads the Laboratory for Topology and Neuroscience and serves as Academic Director for the Euler Programme . Her work bridges pure mathematics and interdisciplinary applications in neuroscience, materials science, and data analysis. Education : PhD in Mathematics (MIT, 1989), preceded by positions at Stockholm, Nice, and Toronto universities. Her research spans algebraic topology , homotopy theory , operad theory , and algebraic K-theory , with applications in neuroscience and materials science . She has pioneered topological data analysis methods for classifying neuronal morphologies , microglia phenotypes , and nanoporous materials , creating a parameter-free framework linking neural network structure to activity. The 15 most recent publications highlight her work on topological inverse problems , neuroinflammation , and equivariant homotopy . These studies often involve collaborations with the Blue Brain Project and EPFL teams in neuroscience , machine learning , and materials science . Scientific Awards : Fellow, American Mathematical Society (2017); Distinguished Speaker, European Mathematical Society (2017); Crédit Suisse Teaching Prize (2012); Polysphère d'Or (2013); Full Member, Swiss Academy of Engineering Sciences (2016); Chaire de la Vallée Poussin (2023); Fellow, Association for Women in Mathematics (2024). She has mentored numerous PhD students in mathematics and neuroscience, including Adélie Eliane Garin , Varvara Karpova , and Dimitri Zaganidis . Her EPFL Mathematics affiliations include the DIVISION MATH , while her Neuroscience lab operates under the Brain Mind Institute (BMI) in the School of Life Sciences (SV). Grants and collaborations are evident in her work on neurodegenerative diseases , synthetic materials , and machine learning frameworks .

• Educational Psychology
• Self-Determination Theory
• Motivation
• +۳ مورد دیگر

Julien Chanal is a researcher at the Faculty of Psychology and Educational Sciences, University of Geneva, specializing in Methodology and Data Analysis (MAD group). His work bridges educational psychology, motivation theory, and neuropsychology through empirical studies on self-determination, physical activity, and cognitive function. Primary affiliation: University of Geneva Research focus: Motivation and executive function assessment Key areas: Physical education, materialism effects, neuropsychological testing His research spans two decades, producing 38 publications with over 19,000 views. Recent projects examine motivation multidimensionality (2025), aerobic fitness-cognition links (2024), and neural correlates of materialism (2018). Despite extensive publication history, specific student names remain unspecified. Methodological innovations include epoch-length analysis in physical education (2015), self-concept modeling (2009), and neuropsychological norm establishment in Cameroon (2009). His work remains actively cited across disciplines, though no scientific awards are explicitly documented in available sources.

Elisa Pellegrinoمشاهده پروفایل

پژوهشگر ارشد

• Phonetics
• Computational Linguistics
• Prosody
• +۷ مورد دیگر

Dr. Elisa Pellegrino is a senior Post-Doc in Phonetics at the Department of Computational Linguistics , affiliated with Zeppelin University and the Digital Society Initiative of the University of Zurich . Her research focuses on voice individualization, vocal accommodation, and the role of speaker-specific information in speech temporal variability. Role: Senior Post-Doc in Phonetics University: Zeppelin University School: Faculty of Arts and Social Sciences Department: Department of Computational Linguistics Email: elisa.pellegrino@uzh.ch Research Interests: Prosody and speech rhythm in native and second language acquisition Vocal accommodation in cross-dialectal interactions Speaker individuality and forensic phonetics Age-related speech temporal variability Speech disorders and Parkinson’s disease Applications of speech technology in linguistics and education

Sarah Dégallier Rochatمشاهده پروفایل

استاد

• Human-Computer Interaction
• Robotics
• Cobotics
• +۶ مورد دیگر

Prof. Dr. Sarah Dégallier Rochat is Head of the strategic thematic field 'Humane Digital Transformation' at Bern University of Applied Sciences (BFH). She holds a joint appointment as Professor at the School of Engineering and Computer Science and serves as co-leader of the Computer Perception and Virtual Reality Lab (cpvrLab) within the Institute for Human-Centered Engineering. Her educational background includes: Ph.D. in Robotics from École Polytechnique Fédérale de Lausanne (EPFL) Master's in Mathematics from EPFL Teaching Diploma in Mathematics from Haute École Pédagogique de Lausanne Psychology studies at University of Lausanne Her research focuses on human-centered technological development with emphasis on: Designing inclusive human-machine interfaces through participatory approaches Developing upskilling strategies for industrial workforce adaptation Examining how techno-narratives shape societal perceptions of technology Creating collaborative robotic systems for agile manufacturing (Cobotics) Exploring mixed reality interfaces for worker augmentation Her publications demonstrate strong interdisciplinary focus on robotics and human-centered AI, with recent works exploring human augmentation in industry, ethical AI implementation, and participatory robot programming. The trajectory shows increasing emphasis on socio-technical systems and workforce empowerment. Significant awards include: Industry 4.0 Shapers Award (2019) CHIRA Best Paper Award (2023) She leads multiple research projects funded by Innosuisse, SNF, and EU programs, including: CODIMAN (Cobotics and workplace humanization) Agile Robotics for High-Mix Low-Volume Production Upskill at Work (digital literacy initiatives) Augmented workers with mixed reality interfaces As founder of Auto-Mate Robotics, she develops flexible robotic cells for industrial applications. She co-leads the Computer Perception and VR Lab and serves on advisory boards including the Swiss Cobotics Competence Center and EUA Task Force on AI.