جست‌وجوی استاد و پژوهشگر

Roland Büchiمشاهده پروفایل

استاد

• Control Systems Engineering
• Robotics
• Artificial Intelligence
• +۴ مورد دیگر

Prof. Dr. Roland Büchi is a Professor at the School of Engineering, Zurich University of Applied Sciences (ZHAW), specializing in control systems engineering and applied AI. His affiliation includes leadership roles in research projects such as the ongoing 'Digital Bridge to Computer Science' initiative. With a career spanning decades, he maintains active research output and industrial collaborations. Research Interests: Büchi focuses on control systems optimization , particularly PID controller tuning using AI methods, system identification, and applications in robotics and drone technology. His work bridges theoretical control theory with practical implementations in mechatronics. Recent efforts explore machine learning for hysteresis modeling and swarm optimization for control systems. Publication Trends: His 15 most recent works (2018-2024) emphasize AI-driven control optimization , drone technology advancements, and engineering education. Dominant themes include PID parameter tuning for time-delayed systems, drone telemetry, and adaptive learning algorithms. A notable shift toward AI/ML applications in control engineering emerged post-2020. Labs and Teams: Büchi collaborates with researchers like Lukas Gruber and has historical ties to ETH Zurich’s robotics projects. His work involves experimental validation at ZHAW’s engineering facilities, with patents in turbocharger magnetic bearing systems.

Raffaello D'Andreaمشاهده پروفایل

استاد

• Robotics
• Control Systems
• Aerospace Engineering
• +۵ 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.

Cesar Dario Cadena Lermaمشاهده پروفایل

مدرس

• Robotics
• Computer Vision
• SLAM (Simultaneous Localization and Mapping)
• +۳ مورد دیگر

Dr. Cesar Dario Cadena Lerma is a Lecturer at the Department of Mechanical and Process Engineering and a tenured Senior Scientist at the Institute of Robotics and Intelligent Systems (IRIS) at ETH Zurich. He leads the Perception, Mapping and Navigation team within the Robotics Systems Lab (RSL), co-founded and directs the ETH RobotX initiative focusing on educational robotics, and previously held roles at ETH Zurich's Autonomous Systems Lab, University of Adelaide, and George Mason University. His research focuses on robotics perception, particularly in SLAM (Simultaneous Localization and Mapping), semantic scene understanding, and robust perception systems for dynamic environments. Education: PhD in Computer Science and System Engineering from the University of Zaragoza, followed by postdoctoral research at George Mason University and The University of Adelaide. Professional roles include managing director of ETH RobotX and leadership in multi-modal mapping frameworks like maplab 2.0. Research interests emphasize integrating perception and learning in robotics, with a focus on semantic mapping, data association, place recognition, and navigation in unstructured environments. His work bridges traditional SLAM techniques with modern deep learning approaches to create robust, modular systems. Key contributions include the PHASER registration algorithm, SCIM obstacle avoidance framework, and C-Blox dense mapping system. Awards include the Best Paper Award at the 2017 IEEE International Symposium on Safety, Security, and Rescue Robotics. His articles span topics like semantic pointcloud filtering, volumetric mapping, and embodied domain adaptation. He collaborates widely, with over 50 peer-reviewed publications in top venues such as IEEE Robotics and Automation Letters and International Journal of Robotics Research.

• Satellite positioning
• Inertial navigation
• Integrated navigation systems
• +۹ مورد دیگر

Jan Skaloud serves as an Adjunct Professor at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Architecture, Civil and Environmental Engineering (ENAC). He holds positions across multiple departments including SSIE (Institute of Earth Surface Dynamics), EDCE (Doctoral Program in Environmental Sciences and Engineering), and leads the Earth Sensing and Observation (ESO) Lab. His office is located at GC C2 397 in the EPFL campus in Lausanne, Switzerland. Dr. Skaloud's research expertise spans satellite positioning, inertial and integrated navigation systems, sensor orientation and calibration, attitude determination, mobile mapping, airborne laser scanning, and Kalman filtering techniques. His work bridges theoretical development with practical applications in UAV navigation, photogrammetry, and remote sensing. He teaches across three EPFL sections and two faculties, demonstrating his interdisciplinary approach to education. His publication record shows consistent contributions to the field, with recent work (2023-2025) focusing on vehicle dynamic model-based navigation for various UAV platforms, including delta-wing and fixed-wing drones. His research demonstrates a clear trajectory toward increasingly sophisticated navigation systems that integrate aerodynamic modeling with traditional sensor fusion approaches. This trend reflects the growing importance of model-based navigation in achieving higher precision and autonomy in UAV operations. 2021: Samuel Gamble Award for career contribution in photogrammetry & sensing (ISPRS) 2020: U.V. Helava Award for best paper in ISPRS Journal (2016-2019) 2017: Best Demo Award at IEEE International Workshop on Metrology & Aerospace 2014: Hansa Luftbild Award for best paper in PFG journal 2012: Karl Kraus Medal for best textbook in Photogrammetry 2009: GNSS Leader to Watch Innovation Award (GPS World) Dr. Skaloud has supervised numerous PhD students whose work focuses on advanced navigation systems, sensor calibration, and UAV applications. His research has received funding for projects involving direct georeferencing, mobile mapping systems, and UAV-based search and rescue operations. The ESO lab he directs serves as a hub for cutting-edge research in Earth observation technologies. The Earth Sensing and Observation Lab under Dr. Skaloud's direction brings together researchers working on navigation systems, sensor integration, and data processing techniques for geospatial applications. The lab maintains strong connections with industry partners and international research organizations, facilitating technology transfer and collaborative research projects.

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).

Karen Mullenersمشاهده پروفایل

دانشیار

• Fluid Dynamics
• Unsteady Flow Phenomena
• Bio-inspired Robotics
• +۴ مورد دیگر

Karen Mulleners is an Associate Professor at the École polytechnique fédérale de Lausanne (EPFL), affiliated with the School of Engineering (STI), the Institute of Mechanical Engineering (IGM), and the UNFOLD Laboratory (Laboratoire de diagnostic des écoulements instationnaires). She also serves in the SGM-ENS teaching department and is a member of the EDEY-GE doctoral program commission. Her research focuses on experimental fluid dynamics, particularly unsteady flow phenomena and vortex dynamics. Professor Mulleners specializes in the intersection of fluid dynamics and bio-inspired engineering, with research interests including: Unsteady vortex-dominated flow phenomena Fluid-structure interaction in flexible systems Experimental methods for flow visualization and measurement Application of fluid dynamics principles to bio-inspired robotics Aerodynamic performance optimization of wind turbine systems Vortex dynamics in flapping and rotating wing systems Her recent publications (2022-2025) demonstrate a strong experimental focus on understanding complex fluid phenomena, particularly in bio-inspired robotics and renewable energy applications. Mulleners' work consistently addresses fundamental questions about vortex formation, flow control, and fluid-structure interactions, with significant contributions to understanding dynamic stall in wind turbines and undulatory swimming mechanics. Her research group employs advanced diagnostic techniques to study unsteady flows, often bridging engineering and biological principles. Professor Mulleners actively supervises PhD students and has directed multiple EPFL theses. Her teaching responsibilities include courses on Measurement Techniques and Aerodynamics, where she imparts knowledge on experimental methods for observing and measuring physical variables such as force, resistance, temperature, flow velocity, and structural deformation. The UNFOLD Laboratory, which Professor Mulleners leads, focuses on diagnostic techniques for unsteady flow phenomena, employing advanced experimental methods including flow visualization, particle image velocimetry, and force measurement systems to study complex fluid dynamics problems with applications in renewable energy and bio-inspired engineering.

Christopher Onderمشاهده پروفایل

مدرس

• Control Engineering
• Mechanical Engineering
• Energy Systems
• +۳ مورد دیگر

Christopher Onder is a Lecturer at the Department of Mechanical and Process Engineering at ETH Zürich, where he serves as Deputy Head of the Institute for Dynamic Systems and Control. His research focuses on control engineering, energy systems, and sustainable transportation solutions. Role : Lecturer, Deputy Head of Institute Department : Mechanical and Process Engineering Institute : Dynamic Systems and Control University : ETH Zürich His research interests include: Control systems for hybrid and electric vehicles Energy management optimization Thermal comfort in public transport Co-design of mechanical and racing strategies Nonlinear control in aerospace applications Model-based calibration for diesel engines Contact: onder@idsc.mavt.ethz.ch

Giorgia Ramponiمشاهده پروفایل

استادیار

• Machine Learning
• Mathematical Modelling
• Reinforcement Learning
• +۳ مورد دیگر

Giorgia Ramponi is an Assistant Professor with Tenure Track at the Faculty of Business, Economics and Informatics at the University of Zurich. She is also an affiliated professor at the ETH AI Center and the Data Science and AI, Computer Science and Engineering department at Chalmers University of Technology. Her educational background includes a Ph.D. in Information Technology from Politecnico di Milano (completed June 2021 with honors), advised by Marcello Restelli, and a Master of Science in Computer Science with Honours Programme (110/110 cum laude) from la Sapienza (July 2017), advised by Flavio Chierichetti and Alessandro Panconesi. Dr. Ramponi's research focuses on machine learning and mathematical modeling, with particular emphasis on reinforcement learning and multiagent learning. Her work bridges theoretical foundations with practical applications, exploring how learning algorithms can make optimal decisions in complex environments. She has made significant contributions to areas including inverse reinforcement learning, multi-agent systems, constrained Markov decision processes, and human-AI interaction through preference learning. Her recent publications demonstrate a strong trend toward addressing fundamental challenges in reinforcement learning, particularly in multi-agent settings, constrained optimization, and learning from human feedback. Her work combines theoretical rigor with practical applications across robotics, economics, and decision-making systems. Hassler Research Grant for "Unified Feedback Integration Framework for Reinforcement Learning" Dr. Ramponi actively contributes to the academic community through conference participation, invited lectures (including at the Mediterranean Machine Learning Summer School), and teaching. She designed and taught the "Data Science and Machine Learning" course for the ETH-Ashesi Master program. She is also a member of the ELLIS community, which connects excellence in AI research across Europe. Her research group focuses on developing frameworks for reinforcement learning with various feedback types, including preferences, rewards, and demonstrations. The group aims to advance the theoretical understanding of learning algorithms while addressing practical challenges in real-world applications.

Helen Oleynikovaمشاهده پروفایل

مدرس

• Robotics
• Autonomous Systems
• Micro-Aerial Vehicles (MAVs)
• +۱۲ مورد دیگر

Helen Oleynikova is a Lecturer at the Department of Mechanical and Process Engineering at ETH Zürich, where she is part of the Autonomous Systems Lab. She works on the intersection of perception and planning, particularly for micro-aerial vehicles. Her research focuses on real-time onboard mapping, planning, and localization using visual-inertial systems and signed distance fields. Research Interests: Helen's work spans robotics, autonomous systems, and computer vision, with a focus on enabling safe and efficient navigation in complex environments. She specializes in visual-inertial odometry, SLAM, 3D mapping using signed distance fields, and real-time path planning for MAVs. Her projects often involve embedded systems and FPGA-based high-speed vision for obstacle avoidance. Publication Trends: Her recent publications (2023–2019) show a consistent focus on real-time, onboard algorithms for autonomous navigation. Key themes include signed distance function maps, collision-free motion generation, global localization, and efficient exploration. She frequently publishes in top-tier robotics conferences such as ICRA and IROS, and journals like IEEE RA-L and Journal of Field Robotics. Professional Experience: Senior Researcher, Autonomous Systems Lab, ETH Zürich Senior Software Engineer, Isaac 3D Perception, Nvidia Senior Scientist, Microsoft Mixed Reality and AI Lab, Zürich Software Engineer, Google (StreetView) Contributor, Willow Garage (ROS, TurtleBot Arm) Education: PhD in Robotics, ETH Zürich (2019) MSc in Robotics, ETH Zürich BSc in Robotics, Olin College of Engineering (2011) Advising and Grants: While no formal students are listed, she has collaborated extensively with researchers at ETH Zürich and industry labs. Her work has been supported through institutional affiliations and industry research roles. She has contributed to open-source robotics software, particularly in ROS-based systems for manipulation and navigation. Labs and Teams: Helen is a key member of the Mobile Manipulation team at the Autonomous Systems Lab at ETH Zürich. She has also been involved in projects at Nvidia, Microsoft, Google, and Willow Garage, focusing on real-world deployment of autonomous systems.

Won Dong Shinمشاهده پروفایل

پژوهشگر

• Robotics
• Unmanned Aerial Vehicles (Drones)
• Vision-Based Control
• +۵ مورد دیگر

Won Dong Shin is a Postdoctoral Researcher at the Laboratory of Intelligent Systems (LIS) within the School of Engineering (STI) at EPFL. His research focuses on bio-inspired robotics, particularly in the design and control of drones and multi-modal robots. He explores topics such as avian-inspired flight mechanisms, morphological control systems, and autonomous navigation strategies. His work integrates vision-based control, biomimetic principles, and reinforcement learning to enhance the agility and accuracy of winged drones in urban environments. He has contributed to developing robots capable of transitioning between ground and air, perching, and adapting to complex terrains through energy-efficient designs. Selected projects include studies on elastic actuation for repetitive hopping, multi-modal locomotion systems, and bio-inspired claws for perching. His research often emphasizes practical applications in robotics for civilian tasks, such as urban exploration and environmental monitoring. Shin collaborates with the LIS group, which is part of EPFL’s Institute of Microengineering (IGM). His contact information includes the email won.shin@epfl.ch and a physical office at MED 1 1612 in Lausanne.

Martin Raubalمشاهده پروفایل

استاد

• Spatial Decision-Making
• Mobile Geographic Information Systems (GIS)
• Location-Based Services (LBS)
• +۷ مورد دیگر

Prof. Dr. Martin Raubal is a Full Professor at the Institute for Cartography and Geoinformation, Department of Civil, Environmental and Geomatic Engineering, ETH Zurich. He leads research on spatial decision-making, mobile GIS, and location-based services, with applications in transportation, energy, and aviation. His work integrates cognitive engineering and eye-tracking to analyze human mobility and interaction with geospatial systems. Doctorate in Geoinformation (with distinction), Vienna University of Technology (2001) MS in Spatial Information Science and Engineering, University of Maine (1997) Dipl.-Ing. in Surveying Engineering and Geoinformation, Vienna University of Technology (1998) His research focuses on spatiotemporal human mobility, cognitive models for GIS, and sustainable urban systems. Key projects include the Digital Underground initiative at the Singapore-ETH Centre and the Empirical Use and Impact Analysis of Mobility-as-a-Service (EIM). Awards include the UV-Helava Prize and multiple best paper recognitions. Recent publications emphasize 3D spatial analysis, AI-driven geospatial tools, and causal inference in mobility modeling. Collaborations span institutions like Lufthansa Systems, SBB, and ETH-IVT. His lab investigates applications such as electric vehicle charging networks, bikeability indexes, and augmented reality in transportation planning.

• Robotics
• Artificial Intelligence
• Computer Vision
• +۳ مورد دیگر

Björn Jensen is a Professor and Co-Head of the AI Robotics Research Lab at Lucerne University of Applied Sciences and Arts (HSLU), specifically within the Lucerne School of Computer Science and Information Technology. He also teaches medical robotics at the University of Bern's Biomedical Engineering Program. His professional background includes roles at the Autonomous Systems Lab at EPFL, Switzerland, and founding the startup Singleton 3D focusing on 3D laser measurement technology. Educational background: MSc in Electrical Engineering (Automation & Image Processing) from TU Darmstadt (1998), followed by a Master's in Industrial Management from the same institution. PhD in human-robot interaction from EPFL (2005), with research stints at Tokyo University (2005) and involvement in projects like Robox@Expo.02 and Smarter-Elrob. Research interests span robotics, human-robot interaction, autonomous systems, medical robotics, and sensor-based navigation. Notable projects include the 'Smart Ennoblement Factory', 'NaviMow' autonomous lawnmower, and 'Bagger Assistenzsysteme'. His work emphasizes real-world applications of robotics in dynamic environments and human-centric systems. Lab leadership includes co-directing the AI Robotics Research Lab, focusing on advancing robotics technologies for practical scenarios. No scientific awards explicitly listed, but contributions to industry-academia collaborations are highlighted through startup ventures and applied research projects.

Mauro Prevostiniمشاهده پروفایل

مدرس

• Wireless Sensor Networks
• Precision Agriculture
• Embedded Systems
• +۴ مورد دیگر

Mauro Prevostini is the Program Manager of the Faculty of Informatics at the Università della Svizzera italiana (USI) since 2004 and holds the academic rank of Lecturer. He previously managed the creation of the Faculty of Informatics from 2001 to 2004 and has been a staff member of the ALaRI institute until 2018. His roles include coordinating academic-industry collaborations and promoting computer science education in local schools. Education: MSc in Electrical Engineering (ETH Zürich, 1994), Thesis: "On-Line Recognition of Masticatory Muscles Activity with Long-Time EMG Recorder" Secondary Education: Liceo Cantonale Lugano 1 (1984–1988) Research Interests: Focuses on Wireless Sensor Networks applied to Precision Agriculture, particularly in pest monitoring systems like PreDiVine DSS. His work integrates UML-based design methodologies for embedded systems and cyber-physical systems. Collaborations include ALaRI and Agroscope research center. Academic Contributions: Over 15 key publications from 2003–2022 emphasize system-level design, hardware/software co-design, and sensor network optimization. Recent articles address deep learning strategies for pest detection and adaptive decision support systems. Professional Activities: Co-founder of Dolphin Engineering Sagl (2012–present), a Precision Agriculture startup Member of the academic senate (2017–2019; 2023–present) Former coordinator of the Ticino branch for the informatica08 initiative (2008) Labs & Projects: Leads projects on wireless sensor networks for agricultural monitoring and collaborates with ALaRI on embedded system design tools and methodologies.

• Swarm Engineering
• Robotics
• Swarm Robotics
• +۱۴ مورد دیگر

Sabine Hauert is Associate Professor (Reader) of Swarm Engineering at the University of Bristol, UK, affiliated with the Faculty of Engineering and the Department of Engineering Mathematics. She leads the Hauert Lab, focusing on swarm systems across scales—from nanorobots in cancer therapy to environmental and logistics robots. She is also based at the Bristol Robotics Laboratory and the Life Sciences Building. Education: PhD in Computer Science, EPFL, Switzerland (2006–2011) MSc in Computer Science, EPFL, Switzerland (2005–2006) Exchange Student in Computer Science, Carnegie Mellon University, USA (2004–2005) BSc in Computer Science, EPFL, Switzerland (2001–2004) Her research centers on swarm engineering, leveraging bio-inspired algorithms, machine learning, and distributed control to design intelligent collective systems. She explores applications in nanomedicine, environmental robotics, and public-facing AI. Her work integrates computational modeling, experimental validation (e.g., tissue-on-a-chip), and real-world deployment of robotic swarms. Sabine is a prominent science communicator and thought leader in robotics and AI. As co-founder and President of Robohub.org and executive trustee of AIhub.org, she bridges research and public discourse. Her insights have been featured in Nature, Science, BBC, CNN, The Guardian, The Economist, and TEDx. She has delivered over 40 invited talks, including three TEDx appearances, and contributed to policy discussions at the Royal Society and European Parliament. Scientific Awards and Recognitions: Society for Experimental Biology President’s Medal (2016) Lindau Nobel Laureate Meeting Selectee (2013) European Podcast Award – Swiss Non-Profit Category (2012) Human Frontiers in Science Program Cross-Disciplinary Fellowship (2011–2014) Botsker Award for Bio-inspired Flying Robots (2011) Best Video Award in Artificial Intelligence (2008) Robocup US Open Champion (2005) Sabine has supervised 6 postdoctoral researchers, 14 PhD students (3 completed), and over 50 undergraduate/MSc projects. She has taught more than 2,000 students in robotics, bio-inspired AI, engineering mathematics, and programming. She has secured major grants including EPSRC TAS, Innovate UK Future Flight, HFSP Project Award, H2020 EVONANO, and multiple EPSRC PhD studentships. She serves on influential committees such as the Royal Society Data Policy Committee, BEIS Robotics Growth Partnership, and IEEE RAS Industrial Advisory Board. She actively organizes major robotics events, including roles as Publicity Chair for IEEE ICRA 2022 and co-chair for IEEE IROS 2019. Her leadership in conference organization and program committees (GECCO, ICRA, IROS, AAAI) underscores her standing in the global robotics community.

• Multiprocessor Systems
• Real-Time Embedded Computing
• Distributed Signal Processing
• +۳ مورد دیگر

Prof. Dr. Matthias Rosenthal is a Professor of Multiprocessor and Real-Time Systems at the ZHAW School of Engineering, Zurich University of Applied Sciences (ZHAW), where he also serves as Head of the Research/Focus Area Realtime Platforms. He holds a PhD and MSc in Electrical Engineering from ETH Zurich (1993–1997). His research focuses on multiprocessor systems, hybrid multicore architectures, distributed signal processing, embedded GPU computing, and real-time embedded systems. Key projects include In-Flight GNSS Interference Detection, dAIrector (automated multi-camera live production), and novel AFM techniques for industrial quality control. He has led over 15 industry-focused projects, including collaborations with Innosuisse and companies like Harman International. His work emphasizes real-time systems, FPGA-GPU co-design, and embedded AI solutions. Education: PhD (ETH Zurich, 1997), MSc (ETH Zurich, 1993) Awards: CTI Startup Label (2005) Teaching: Lectures on digital systems, real-time computing, and information theory Notable contributions include advancements in embedded machine learning for food waste management, secure boot concepts for Zynq MPSoC, and low-latency wireless video systems. His research bridges theoretical computer engineering with practical industrial applications.