جستجوی استاد راهنمای دانشگاهی

Prof. Christian Holz is an Associate Professor at the Department of Computer Science and Deputy Head of the Institute of Intelligent Interactive Systems at ETH Zürich. His work focuses on advancing human-computer interaction through innovations in wearable technologies, mixed reality systems, and sensor-driven applications. Key research areas include motion capture, physiological signal processing, and adaptive user interfaces. Holz leads the SIPLab (siplab.ethz.ch), producing influential work at the intersection of computer science and biomedical engineering. His research explores cutting-edge topics such as egocentric vision systems, wearable health monitoring devices, and VR/AR applications. Recent studies investigate cybersickness detection via EEG, heart rate estimation from eye-tracking cameras, and scalable motion capture using inertial/UWB sensors. Holz's work emphasizes practical applications in healthcare, education, and human-centered computing. Publications reflect a strong focus on interdisciplinary solutions, combining machine learning with sensor data analysis. Notable contributions include the EgoSim multi-view simulator, WildPPG biomedical dataset, and MiBOT cardiovascular modulation device. His research bridges theoretical advancements with real-world usability in domains like emergency response training, chronic disease monitoring, and immersive education.

• Human-Computer Interaction
• Wearable Technologies
• Mixed Reality
• +۴ مورد دیگر

Prof. Hedan Bai is an Assistant Professor at the Department of Materials, ETH Zürich, specializing in robotics materials, bio-inspired systems, and soft robotics. Their research focuses on developing advanced materials for sensing, energy-efficient systems, and biomedical applications. Notable projects include the SmartSuit architecture for space exploration and self-healing optical sensors for soft robots. Research interests span bioelectronics, stretchable sensors, haptic interfaces, and biomimetic materials. Bai's work integrates material science with robotics to create adaptive, sustainable, and intelligent systems. Key areas include wireless implants for neuromodulation, environmental-responsive textiles, and energy-harvesting devices. Publications highlight innovations in optical waveguides, self-healing materials, and wearable technologies. Their interdisciplinary approach bridges robotics, biomedical engineering, and aerospace applications. No formal awards are listed, but contributions to next-gen materials for robotics are prominent. Advising and grants are not detailed in the text, but Bai's lab focuses on projects like SmartSuit for extravehicular activities and synthetic afferent neural networks. Collaborations likely involve aerospace and biomedical sectors.

• Robotics Materials
• Bioelectronics
• Sensors Technology
• +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.

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

Dr. Michael Mühlebach is a Lecturer at the Department of Information Technology and Electrical Engineering, ETH Zurich, and affiliated with the Max Planck Institute for Intelligent Systems in Tübingen, Germany. He holds a Bachelor's (2010) and Master's (2013) from ETH Zurich, recognized with awards for academic excellence in Robotics, Systems, and Control. His research focuses on multibody dynamics, nonlinear system control, and model predictive control, with applications in robotics and aerospace systems. His work spans theoretical advancements in variational integrators and practical implementations in systems like the Cubli (a reaction wheel-based 3D inverted pendulum) and flying platforms for ducted fan actuation. Publications highlight contributions to model predictive control schemes with stability guarantees, nonlinear analysis, and distributed event-based state estimation. Key awards include the Outstanding D-MAVT Bachelor Award and Willi-Studer Prize. His research integrates control theory with real-world applications, emphasizing both foundational mathematics and engineering implementations. No grants or lab affiliations are explicitly listed in the provided text.

• Multibody Dynamics
• Control of Nonlinear Systems
• Model Predictive Control
• +۳ مورد دیگر

Prof. Raffaello D'Andrea is a Full Professor at ETH Zürich's Department of Mechanical and Process Engineering, affiliated with the Institute for Dynamic Systems and Control. His research focuses on bridging digital and physical worlds through robotics, control systems, and autonomous systems. He has pioneered work in aerial robotics, swarm systems, tactile sensing, and soft robotics. His philosophy emphasizes solving 'easy' problems with scalable, robust solutions, prioritizing simplicity and replicability. Key research areas include UAV navigation, distributed control, tactile sensor design, and fault-tolerant systems. He has founded multiple organizations and led roles as CTO/CEO, emphasizing cross-disciplinary innovation. His work has commercial applications in logistics, healthcare, and automation, driven by a belief in technology's role in improving human life. Notable projects include the Cubli robotic cube, aerial vehicle swarms, and optical tactile sensors for robotics. His lab emphasizes collaboration and team leadership, aiming to translate theoretical insights into practical, scalable technologies. Scientific awards: None explicitly listed in the provided texts. Advising and grants: No students listed in the provided texts; grants information not detailed. Labs/Teams: Leads research at ETH Zurich's Institute for Dynamic Systems and Control, collaborating with industry and academic partners globally.

• Robotics
• Control Systems
• Aerospace Engineering
• +۵ مورد دیگر

Prof. Michael Moor is a tenure-track Assistant Professor for Medical AI at ETH Zurich's Department of Biosystems Science and Engineering in Basel. Previously, he conducted postdoctoral research at Stanford University under Prof. Jure Leskovec, focusing on medical foundation models. His work spans causal learning, multimodal AI, and sepsis prediction. Moor holds an MD from the University of Basel and a PhD from ETH Zurich's Machine Learning and Computational Biology Lab under Prof. Karsten Borgwardt. Research Interests: Generalist medical AI models Multimodal medical reasoning Zero-shot and few-shot learning Clinical causal inference Retrieval-augmented language models Sepsis prediction systems Key Achievements: Published foundational work in Nature (2023) on generalist medical AI Developed Med-Flamingo multimodal model (2023) Zero-shot causal learning framework accepted to NeurIPS 2023 (Spotlight) International sepsis prediction study with 156k ICU patients (2023) Lab Activities: Leads ETH's Medical Foundation Models group, collaborating with Stanford HAI and NASA Ames. Active in creating medical AI benchmarks like AgentClinic and developing retrieval-augmented systems like Almanac.

• Medical AI
• Machine Learning in Healthcare
• Causal Learning
• +۳ 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 .

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

Prof. Dr. Melanie Zeilinger is an Associate Professor at the Department of Mechanical and Process Engineering at ETH Zurich, leading the Intelligent Control Systems group at the Institute for Dynamic Systems and Control. She holds a diploma in Engineering Cybernetics from the University of Stuttgart (2006) and a Ph.D. in Electrical Engineering from ETH Zurich (2011). Her postdoctoral research included stints at EPFL (2011–2012), a Marie Curie fellowship at UC Berkeley and the Max Planck Institute (2012–2015), and a professorship at the University of Freiburg (2018–2019). Her research focuses on learning-based control, distributed control systems, and robotics , with applications to medical devices (e.g., hydrocephalus shunts) and human-in-the-loop systems. She organizes the Conference on Learning for Dynamics and Control (L4DC) and contributes to initiatives like the "Algorithm on My Team" project. Her awards include the ETH Medal for her PhD thesis, a Marie-Curie IO Fellowship , and an SNF Assistant Professorship grant . She serves as an Associate Editor for IEEE Control Systems Letters and actively reviews for top journals/conferences like IEEE TAC, Automatica, and NeurIPS. Key projects include: VIEshunt: A smart ventricular shunt for hydrocephalus treatment, combining control systems and medical engineering. Autonomous Racing: Contextual tuning and safety-certified learning-based MPC for real-time obstacle avoidance. Data-Driven Control: Integrating Gaussian processes and state-space models into MPC frameworks for uncertain systems. Her work bridges control theory, machine learning, and robotics, addressing societal challenges such as healthcare and energy efficiency.

• Learning-based Control
• Distributed Control and Optimization
• Robotics
• +۴ مورد دیگر

Bradley Nelson is a Full Professor of Robotics and Intelligent Systems at ETH Zürich since 2002, leading the Institute for Robotics and Intelligent Systems. He holds a Ph.D. in Robotics from Carnegie Mellon University (1995), with prior roles as Assistant Professor at the University of Illinois at Chicago (1995-1998) and Associate Professor at the University of Minnesota (1998-2002). His research focuses on microrobotics and nanorobotics for biomedical applications, including targeted drug delivery and medical robotics. He leads the Microrobotics Lab (MSRL) and chairs international workshops/conferences. Awards include IEEE and ASME Fellowships, and Best Paper accolades at major robotics venues. Research interests emphasize magnetic microrobot navigation, smart materials, and clinical translation of robotic systems. His work bridges engineering and medicine, addressing challenges like cerebral vasculature navigation for drug delivery. He has developed electromagnetically controllable catheters and telesurgery frameworks. Leadership roles include Head of the ETH Department of Mechanical and Process Engineering and Chairman of the ETH Electron Microscopy Center (EMEZ). Notable contributions include magnetically guided microcatheters, variable-stiffness catheters, and clinical-ready navigation systems. Ongoing projects explore magnetoelectric effects and biodegradable micromotors for environmental and biomedical uses. His lab collaborates with industry and academic partners globally to advance robotic solutions for healthcare challenges.

• Microrobotics
• Nanorobotics
• Medical Robotics
• +۳ مورد دیگر

Devis Tuia serves as Associate Professor at the Swiss Federal Institute of Technology Lausanne (EPFL), holding appointments in the Institute of Environmental Engineering (IIE) within the School of Architecture, Civil and Environmental Engineering (ENAC). He leads the Environmental Computational Science and Earth Observation Laboratory (ECEO) since 2020 and contributes to EPFL's Doctoral Program in Civil and Environmental Engineering. His academic journey began in Lausanne with studies at UNIL and EPFL, culminating in a PhD in remote sensing from UNIL. Postdoctoral research followed at institutions in Valencia, Boulder, and EPFL, focusing on machine learning model adaptation. He progressed from Research Assistant Professor at University of Zurich to Associate and Full Professor at Wageningen University before joining EPFL. Tuia's research bridges Earth observation with artificial intelligence, specializing in interpretable deep learning for environmental applications. His lab develops algorithms for making remote sensing accessible, with particular emphasis on digital wildlife conservation through automated censuses using drone and satellite imagery. Current projects tackle the 'black box' problem in environmental modeling while advancing spatial intelligence for sustainable urban development. His 2023-2025 publication portfolio reveals three dominant trends: (1) species distribution modeling using incomplete observations, (2) multimodal fusion of satellite/drone data with textual descriptions, and (3) interpretable AI frameworks for environmental decision-making. This work consistently addresses real-world challenges like wildfire forecasting and biodiversity monitoring. As an educator, Tuia supervises 12 current PhD students and has graduated 4 former EPFL doctoral candidates. His teaching portfolio includes Frontiers of Deep Learning for Engineers , Sensing and Spatial Modeling for Earth Observation , and Image Processing for Earth Observation courses. The ECEO laboratory maintains active collaborations with ESA-NASA initiatives and conservation organizations globally.

• Earth Observation
• Remote Sensing
• Machine Learning
• +۵ مورد دیگر

Manuel Kaufmann is a Lecturer in the Department of Computer Science at ETH Zürich. His work focuses on advanced 3D human motion capture, sensor-based systems, and computer vision applications. He is affiliated with the Institute of Informatics (inf.ethz.ch) and contributes to research in real-time motion tracking, dataset development, and machine learning integration for human-robot interaction. Research interests include holistic human-scene reconstruction from monocular videos, gaze estimation using EEG signals, and expressive avatar creation. His projects emphasize practical applications in robotics, sports analytics, and biomedical engineering, often leveraging electromagnetic and inertial sensors for high-precision data acquisition. His publications reflect a trend toward multi-modal data fusion, real-world dataset creation (e.g., WorldPose, ARCTIC), and addressing challenges in loose garment modeling (Reloo). These efforts aim to improve markerless motion capture, crowd analysis, and human-robot collaboration. No scientific awards or grants are explicitly listed. He has no documented advisees, though his research may involve collaborations with students or teams. His office is located at OAT X 23, Andreasstrasse 5, Zürich, Switzerland, and contact details include a phone number and professional email.

• 3D Human Motion Capture
• Computer Vision
• Sensor Data Processing
• +۳ مورد دیگر

Stéphanie P. Lacour is a Full Professor at the School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), where she holds the Foundation Bertarelli Chair in Neuroprosthetic Technology. She leads the Laboratory of Soft Bioelectronic Interfaces (LSBI) and is affiliated with multiple departments including INX-STI, STI-SMT, SV-SSV, and AVP-DLE-EDOC. Since 2025, she has served as EPFL’s Vice-President for Support to Strategic Initiatives, overseeing institutional research strategy. Her research is centered at Campus Biotech in Geneva, where she was the founding director of the Neuro-X Institute. PhD in Electrical Engineering, INSA Lyon, France (1998–2001) Postdoctoral Research, Princeton University and University of Cambridge Joined EPFL in 2011 Her research focuses on soft bioelectronic interfaces that seamlessly integrate with biological tissues. She pioneers the development of stretchable, compliant electronics for implantable and wearable applications, using techniques from MEMS and microelectronics adapted to elastomeric substrates. Her work enables long-term, minimally invasive neural interfacing for applications in neuroprosthetics, rehabilitation, and health monitoring. Key innovations include soft electrocorticography arrays, liquid metal sensors, and encapsulation methods for chronic implants. Her recent publications span high-impact journals such as Nature , Science Robotics , Advanced Materials , and Nature Nanotechnology , covering topics like neural stimulation, soft robotics, wireless implants, and hydrogel-based interfaces . The work demonstrates a strong trend toward multimodal, closed-loop, and translational neurotechnologies with real-world clinical potential. Scientific Awards: No scientific awards explicitly mentioned in the provided text. She advises a large cohort of PhD students and postdoctoral researchers, many of whom have completed their theses under her supervision. Her team has received funding for projects in neural interfacing, bioelectronics, and soft robotics. She is actively involved in teaching courses such as Soft Microsystems Processing and Devices and Neural Interfaces . Lacour leads the Laboratory of Soft Bioelectronic Interfaces (LSBI) , a multidisciplinary research team focused on the fabrication, characterization, and in vivo evaluation of soft bioelectronic systems. The lab collaborates extensively across EPFL and with clinical partners to translate technologies from bench to bedside.

• Bioelectronics
• Neuroprosthetics
• Soft Electronics
• +۹ مورد دیگر

Prof. Dr. Raphael Sznitman serves as Director of the ARTORG Center for Biomedical Engineering Research and Head of the Artificial Intelligence in Medical Imaging group at the University of Bern, Switzerland, holding a Full Professor position in AI for Medical Imaging since 2015. Education: PhD in Computer Science, Johns Hopkins University (2011) MSc in Computer Science, Johns Hopkins University (2009) BSc in Cognitive Systems, University of British Columbia (2007) Research Interests: Sznitman's work centers on computational vision , probabilistic methods , and statistical learning applied to medical imaging challenges. His group develops AI algorithms for ophthalmic diagnostics, surgical robotics, and medical image analysis, with emphasis on OCT, surgical phase recognition, and domain adaptation techniques. Key application areas include retinal disease detection and cataract surgery automation. Publication Trends: His 2021-2025 publications reveal concentrated efforts in deep learning for medical imaging , particularly in ophthalmology (OCT analysis) and surgical video understanding. Emerging themes include LLM applications for clinical monitoring, unsupervised out-of-distribution detection for surgical safety, and physics-informed AI for multimodal medical data fusion. Research Leadership: As ARTORG Center Director, Sznitman oversees interdisciplinary research bridging computer science and clinical medicine. His group collaborates extensively with Bern University Hospital clinicians on translational projects, securing funding for AI-driven diagnostic tools and surgical assistance systems. Current initiatives focus on real-time intraoperative guidance and spaceflight ophthalmology applications. Laboratory: The Artificial Intelligence in Medical Imaging group operates within ARTORG's dedicated facilities, maintaining partnerships with surgical robotics labs and ophthalmology departments for clinical validation of AI systems. Their work integrates multimodal data streams including OCT, VR perimetry, and surgical video feeds.

• Computer Vision
• Probabilistic Methods
• Statistical Learning
• +۲ مورد دیگر

Daniel Razansky is a Full Professor at the Department of Information Technology and Electrical Engineering, ETH Zurich, leading the Professorship for Biomedical Imaging. His research spans engineering, physics, biology, and medicine, focusing on developing advanced in vivo imaging tools like optoacoustic tomography and ultrasound neuromodulation. His recent work emphasizes multi-scale functional and molecular imaging , with applications in neuroscience , Alzheimer’s disease , and stroke diagnostics . Collaborations include National Tsing Hua University and the EU Horizon consortium SWEEPICS. Current projects target hybrid imaging systems (e.g., MRI-MSOT) and image-guided neuromodulation. Scientific awards include the IPPA James Smith Prize for his contributions. His lab has secured significant grants, including a $2.5M NIH award and SNSF funding. He mentors PhD students like Quanyu Zhou and Eva Remlova, who have received accolades for their research. The Razansky Lab at ETH Zurich’s Preclinical Imaging Center explores medical microrobotics , dynamic fluid flow imaging , and neuroimaging techniques , aiming to bridge engineering with clinical applications.

• Biomedical Imaging
• Functional Imaging
• Molecular Imaging
• +۷ مورد دیگر

Prof. Dr. Mirko Meboldt serves as a Full Professor at ETH Zurich's Department of Mechanical and Process Engineering, where he holds dual leadership roles as Head of Lecturers' Conference and Deputy Head of the Institute of Machine Tools and Manufacturing. His office is located at Leonhardstrasse 21 in Zürich, Switzerland. Professor Meboldt's research spans multiple engineering domains with particular emphasis on: User-oriented product innovations New production technologies Mechanical engineering applications Biomedical device development CAD/PDM systems standardization Engineering education methodologies His recent publication portfolio reveals a distinctive interdisciplinary approach that bridges traditional mechanical engineering with cutting-edge medical applications. Key research trends include human-robot collaboration systems, intelligent medical devices for neurosurgery, augmented reality training platforms for medical procedures, advanced manufacturing processes, and AI-assisted healthcare communication analysis. This diverse research portfolio demonstrates his commitment to solving complex real-world engineering challenges through cross-disciplinary innovation. Professor Meboldt places significant emphasis on the educational impact of his work, explicitly stating that he 'regards the impact on the education of young engineers and its relevance for industry as a key motivation and benchmark for his research.' His industrial background at Hilti AG informs his practical approach to academic research, ensuring strong industry relevance across all his projects.

• Product Development
• Engineering Design
• Mechanical Engineering
• +۴ مورد دیگر