جستجوی استاد راهنمای دانشگاهی

• Robotics
• Autonomous Vehicles
• Data Fusion
• +۳ مورد دیگر

Philippe BONNIFAIT is a Professor at the University of Technology of Compiègne (UTC) and Director of the Heudiasyc Research Lab (UMR UTC-CNRS 7253) since 2018. He specializes in robotics, autonomous vehicles, and data fusion, with a focus on localization systems and sensor integration. His research addresses challenges in intelligent transportation, fault detection, and cooperative robotics. He holds leadership roles including Head of the Autonomous Land Robotics axis in the TIRREX EQUIPEX+ project, and serves on the steering committee of the SIVALab joint lab with UTC, CNRS, and Renault. His international collaborations include Coimbra University (Portugal). Research Interests: Autonomous Vehicle Navigation Multi-Sensor Fusion GNSS-Based Positioning Decentralized Cooperative Systems Intelligent Transportation Systems Publications highlight advancements in vehicle localization, error mitigation, and sensor integration for autonomous systems. Notable work includes fault detection methodologies and HD map-aided navigation. No scientific awards listed. Active in lab administration and industry partnerships, contributing to experimental vehicles and robotics infrastructure.

• Aerodynamics
• Animal Flight Mechanics
• Bio-inspired Robotics
• +۳ مورد دیگر

Florian Muijres is an Associate Professor and Chairholder at the Experimental Zoology Group, Wageningen University & Research, where he leads the Animal Flight Lab. His research focuses on the biomechanics, aerodynamics, and flight control of natural flyers such as insects, birds, and bats, with applications in bio-inspired robotics and ecological solutions like mosquito traps and flapping-wing drones. He holds a PhD from Lund University (Sweden) and conducted postdoctoral research at the Dickinson Lab, University of Washington (USA). Research Interests: Merging experimental and computational methods, his work explores primary research on flight mechanics (e.g., mosquito evasion, butterfly gliding) and applied studies (e.g., drone design, pollinator behavior in greenhouses). His lab uses advanced videography and robotic models to study flight dynamics under real-world conditions. Labs & Teams: The Animal Flight Lab collaborates with biologists, physicists, and engineers to investigate flight adaptations in mosquitoes, bumblebees, and pied flycatchers. Projects include developing high-efficiency traps and analyzing flight performance in complex environments.

Joseph Mooreمشاهده پروفایل

استادیار

• Aerial Robotics
• Computational Control
• Learning-based Control
• +۳ مورد دیگر

Dr. Joseph Moore is an Assistant Professor in the Department of Mechanical Engineering at Johns Hopkins University (JHU), serving as Director of the Agile and Intelligent Robotics (AIRO) Laboratory. He is affiliated with the Laboratory for Computational Sensing and Robotics (LCSR), the Institute for Assured Autonomy (IAA), and holds a Bridging Faculty appointment in the Research and Exploratory Development Department (REDD) at JHU/APL. His research focuses on computational control, machine learning, and robotics to enable agile systems operating in complex environments. Dr. Moore previously served as Robotics Group Chief Scientist at JHU/APL, leading projects on hybrid unmanned aerial-aquatic vehicles and aerobatic fixed-wing systems. He has secured funding as Principal Investigator (PI) for ONR, DARPA, and ARL programs, particularly in post-stall maneuvering control and multi-robot coordination. His work emphasizes robust control strategies for autonomous systems in constrained environments. Research interests include aerial robotics, optimization, and learning-based control. Notable contributions involve NMPC-based systems, UAV navigation, and adaptive control for uncertain environments. His recent articles highlight advancements in swarm coordination, morphing-wing UAVs, and PAC-NMPC frameworks. Dr. Moore advises students such as Mark Gonzales and Adam Polevoy. Key grants include ONR/DARPA-funded projects on post-stall flight control and Army-funded multi-robot coordination efforts. His lab (AIRO) and collaborations (LCSR, IAA) drive applied and theoretical robotics research.

Kyle DeMarsمشاهده پروفایل

دانشیار

• Space situational awareness
• Navigation, guidance, and control
• Bayesian filtering
• +۶ مورد دیگر

Kyle DeMars is an Associate Professor and Associate Department Head for Theoretical and Computational Research in the Department of Aerospace Engineering at Texas A&M University. He holds a Ph.D. from The University of Texas at Austin (2010) and has expertise in space situational awareness, navigation systems, Bayesian filtering, and information theory. His work focuses on advanced estimation techniques for spacecraft autonomy and space surveillance. Dr. DeMars' research emphasizes robust nonlinear filtering, multitarget tracking, and information-theoretic approaches to orbital dynamics. He has developed innovative methods for spacecraft navigation, including terrain-relative systems and anonymous feature processing. His contributions address challenges in uncertainty quantification, sensor fusion, and cislunar space domain awareness. Education: Ph.D./M.S.E./B.S. in Aerospace Engineering (UT Austin, 2004–2010) Awards: AIAA Young Professional Award (2017), NASA Innovation Award (2014), and multiple teaching/research recognitions Labs/Teams: Active in space situational awareness, guidance & control, and probabilistic navigation systems Key trends in his publications include: Advances in particle flow and Gaussian mixture methods for nonlinear estimation Cislunar trajectory analysis and resonance-based surveillance strategies Development of fault-resistant and anonymous navigation frameworks Integration of information theory into sensor tasking and uncertainty management His work bridges theoretical developments with practical applications in planetary landing navigation, space traffic management, and autonomous spacecraft systems.

• Hydrography
• Geodesy
• Navigation Systems
• +۷ مورد دیگر

Prof. Harald Sternberg is a distinguished academic at HafenCity University Hamburg, holding the position of University Professor for Hydrography and Geodesy. His affiliations include the Department of Geodesy and Geoinformatics, where he leads research in hydrographic education and advanced geomatics technologies. He previously served as Vice President for Teaching and Studies (2009-2022) and Acting President (2010) of HCU. Education: Ph.D. in Geodesy from University of the Bundeswehr Munich (1999), specializing in trajectory determination of land vehicles using hybrid systems. Early career included roles as scientist at Bundeswehr University (1991-2001) and academic leadership at HAW Hamburg (2005-2009). Research focuses on underwater mapping, navigation systems, and sensor integration. Key projects include: Level 5 Indoor Navigation (5G-based positioning), hydrothermal vent exploration using deep-towed multibeam systems, and low-cost mobile mapping solutions. He also investigates smartphone-based inertial navigation and autonomous underwater vehicles for infrastructure monitoring. Publications span underwater vision systems, satellite-derived bathymetry, and 3D point cloud analysis. Over 200 peer-reviewed articles and book chapters reflect expertise in geomatics applications. Current research emphasizes 5G-enabled indoor navigation and environmental sensor networks. Grants include BMWK-funded autonomous deep-sea monitoring and BGR exploration projects in the Indian Ocean. His lab develops innovative tools like the HOMESIDE sled for seafloor surveys. Supervises Ph.D. research on hydrothermal vent analysis and data-driven inertial localization.

• Robotics
• Unmanned Aerial Vehicles (UAVs)
• Mechatronics
• +۷ مورد دیگر

Alexis Lussier Desbiens is an Associate Professor at the Université de Sherbrooke in the Department of Mechanical Engineering , Faculty of Engineering. He co-founded several research labs and initiatives including NSERC CREATE CoRoM (Collaborative Robotics in Manufacturing) and NSERC CREATE UTILI (Uninhabited Aircraft Systems Training). His work bridges robotics, mechanical design, and sports equipment innovation. PhD in Mechanical Engineering (Stanford University, 2012) BEng in Mechanical Engineering (Université de Sherbrooke, 2005) Postdoctoral Research (Harvard University, 2013) His research focuses on robotics and automation , particularly unmanned aerial vehicles (UAVs) with bioinspired design principles for mechanical intelligence. Key areas include: Autonomous UAV perching and climbing Hybrid locomotion systems Sports equipment dynamics (skis, hockey sticks) Magnetorheological actuator applications Conservation biology tools via aerial sampling Recent publications highlight interdisciplinary work in robotics , sports engineering , and ecological monitoring . His projects often integrate mechanical design with environmental or human-centric applications. Scientific recognition includes: Best Student Paper (IEEE SMC, 2021) Best Poster (ISEA, 2020) National Geographic Explorer (2020) CSME Gold Medal (2005) Current grants (2020-2023) include: $339,000 - High-performance UAV for power line interactions $1.65M - NSERC CREATE UTILI training program $120,000 - Intelligent hockey stick development He also leads the CREATEK Research Lab and maintains global collaborations with institutions like Harvard University, Stanford University, MIT, and EPFL.

John Valasekمشاهده پروفایل

استاد

• Autonomous Systems
• Nonlinear Control
• Cyber-Physical Systems
• +۵ مورد دیگر

John Valasek is a Professor in the Department of Aerospace Engineering at Texas A&M University, holding the Drs. L. Diane '88 and John E. Hurtado '91 Professorship. He directs the Vehicle Systems & Control Laboratory (VSCL) and serves as Site Director for the NSF Center for Autonomous Air Mobility and Sensing (CAAMS) and the FAA Center for General Aviation Research (PEGASAS). His research focuses on autonomous control systems, UAV navigation, and cybersecurity for aerospace vehicles. Valasek earned his Ph.D., M.S., and B.S. in Aerospace Engineering from the University of Kansas (1995) and California State Polytechnic University (1986). Education: Ph.D., Aerospace Engineering, University of Kansas - 1995 M.S., Aerospace Engineering, University of Kansas - 1990 B.S., Aerospace Engineering, California State Polytechnic University - 1986 Research Interests: Autonomous systems, nonlinear control, vision-based navigation, UAV control, bio-nano materials control, and aerospace systems engineering. Key Contributions: Over 100 invited lectures/seminars, leadership in NSF-funded research centers, and development of advanced control algorithms for aerospace systems. Notable publications include work on reinforcement learning for autonomous systems and real-time system identification for UAS. Awards: John Leland Atwood Award (2015) McElmurry Outstanding Teaching Award (2001, 2004, 2014) Engineering Hall of Fame inductee (2019) Advising & Grants: Advised over 60 graduate students, including recent NSF GRFP winner Evelyn Madewell. PI on multi-million-dollar grants, including the NSF CAAMS project and Air Force-funded research on autonomous systems. Labs & Teams: Directs the Vehicle Systems & Control Laboratory (VSCL), focusing on low-cost attritable aircraft technology and autonomy. Collaborates with industry partners like Stratolaunch and VectorNav through CAAMS initiatives.

• Remote Sensing
• Bidirectional Reflectance
• Image Processing
• +۳ مورد دیگر

Craig Coburn is a Full Professor in the Department of Geography and Environment at the University of Lethbridge, where he has served since 2002 with promotions to Associate Professor in 2009 and Full Professor in 2019. His research centers on remote sensing physics, specializing in bidirectional reflectance properties and the development of low-cost remote sensing instrumentation for environmental monitoring and satellite calibration. Dr. Coburn's academic foundation includes: B.Sc. (Honours) in Geography from the University of Saskatchewan (1994) M.Sc. in Geography from the University of Alberta (1996) Ph.D. in Geography/Remote Sensing from Simon Fraser University (2002) His work spans instrument design to data processing algorithms, with emphasis on surface bidirectional reflectance. He pioneered world-leading goniometers and low-cost camera systems deployed via aircraft, UAVs, and high-altitude balloons for agricultural monitoring, biological system analysis, and global satellite validation. His research bridges theoretical physics with practical environmental applications. Analysis of his 2017-2021 publications reveals sustained focus on radiometric calibration, BRDF characterization, and sensor development. Key trends include interdisciplinary collaborations in atmospheric science (airborne metals), ecology (riparian systems), and soil science (erosion detection), alongside growing emphasis on UAV platforms and low-cost sensor validation for democratizing remote sensing. No scientific awards were specified in the source material. Dr. Coburn holds Principal Investigator status for the Prairie Farm Rehabilitation Administration-funded cattle wintering sites project ($45,000) and contributes as Co-Investigator to Alberta Ingenuity Centre for Water Research initiatives totaling $568,000. His grant portfolio spans riparian ecology, watershed analysis, and historical projects including National Land and Water Information System (Agriculture Canada) and Mountain Pine Beetle monitoring. His laboratory innovations include robotic goniometers for surface reflectance measurement and thermal imaging systems deployed globally for satellite calibration, supporting both research objectives and hands-on student training in remote sensing physics.

Guoquan Huangمشاهده پروفایل

استادیار

• Robotics
• Computer Vision
• Robot Learning
• +۵ مورد دیگر

Guoquan Huang is an Assistant Professor in the Department of Mechanical Engineering at the University of Delaware. He holds a B.Eng. in Automation from the University of Science and Technology, Beijing (2002), and M.Sc. and Ph.D. degrees in Robotics from the University of Minnesota (2009 and 2012). Prior to his current role, he was a Postdoctoral Associate at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL). His research focuses on robotics, computer vision, and autonomous systems, emphasizing probabilistic perception, estimation, and control for ground, aerial, and underwater vehicles. He leads the development of the OpenVINS platform for visual-inertial estimation and has contributed to advancements in SLAM (Simultaneous Localization and Mapping), sensor fusion, and multi-robot coordination. Education: B.Eng in Automation (Electrical Engineering), University of Science and Technology, Beijing, 2002 M.Sc. in Robotics, University of Minnesota, Twin Cities, 2009 Ph.D. in Robotics, University of Minnesota, Twin Cities, 2012 His research interests span robotics, computer vision, and autonomous systems , with a focus on: Visual-inertial navigation and SLAM Sensor fusion (LiDAR, IMU, camera) Autonomous vehicle control and safety Multi-robot cooperative localization His recent publications (2023–2025) emphasize robust algorithms for navigation in GPS-denied environments, real-time sensor calibration, and dataset development for aerial visual localization. He has pioneered techniques like decoupled error-state estimation and consistent parallel frameworks for SLAM. Labs/Teams: Leads the development of the OpenVINS research platform, focusing on visual-inertial state estimation. Collaborates on projects involving human-swarm interactions and resilient ground vehicle navigation.

• Robotics
• Machine Learning
• Reinforcement Learning
• +۳ مورد دیگر

Pawel Ladosz is a Lecturer in Engineering Systems for Robotics at the Department of Mechanical and Aerospace Engineering, The University of Manchester. His research focuses on applying machine learning and computer vision to mobile robots, particularly in extreme environments such as total darkness or cluttered spaces. He is actively involved in developing autonomous navigation systems, wireless signal mapping, and high-level decision-making for robotic swarms. He teaches courses including Robotic Systems Design Project and Autonomous Mobile Robots. Education: PhD in Establishing and Optimising Unmanned Airborne Relay Networks (Loughborough University, 2014–2019) MEng in Aerospace Engineering (The University of Manchester, 2010–2014) Research Interests: Ladosz’s work emphasizes reinforcement learning for robotics, vision-based autonomous systems, and exploration in challenging environments. His projects often intersect with UN Sustainable Development Goals, contributing to innovations in robotic autonomy and sensor networks. Awards: He received the 2nd Autonomous Flying Technology Competition award in 2021, recognizing his contributions to autonomous flight systems. His research has also led to the establishment of the Centre for Robotic Autonomy in Demanding and Long-Lasting Environments (CRADLE), fostering cross-disciplinary collaborations. Grants & Projects: As Principal Investigator in the Aerospace Engineering initiative (2010–2035), he explores UAV communication networks and trajectory planning. His work addresses urban environment challenges, including relay positioning and signal prediction. Labs/Teams: Ladosz contributes to CRADLE, advancing robotic autonomy in extreme scenarios. His lab focuses on integrating AI and robotics for real-world applications.

J. Ellersمشاهده پروفایل

استاد

• Evolutionary Biology
• Ecology
• Molecular Ecology
• +۶ مورد دیگر

Prof. Dr. J. Ellers is a Full Professor at the Faculty of Science, Vrije Universiteit Amsterdam , and a member of the Amsterdam Institute for Life and Environment . His research focuses on understanding how an individual’s phenotype is shaped by interactions between genes, genome, and environment , employing molecular, physiological, and experimental tools within an evolutionary framework. Ellers contributes to the Netherlands Society of Evolutionary Biology (NLSEB) as a co-founder and serves as Vice-Chair of the Dutch Biology Council , advocating for biology research and education in the Netherlands. Research Interests: Ellers explores the intersection of evolutionary biology, ecology, and environmental science , with key themes in phenotypic plasticity, urbanization effects on species, trait-based ecology, and adaptive signaling . His work spans soil fauna dynamics, invasive species impacts, and metabolic adaptations , emphasizing interdisciplinary approaches to link mechanisms with ecological and evolutionary outcomes. Recent Publications highlight trends in urban ecology, climate change impacts, and trait evolution . Notable studies examine how noise and light pollution alter animal communication , high-sugar diets affect microbiomes , and robot morphologies reflect biological systems . His research also addresses data interoperability through initiatives like ShareTrait and global soil arthropod assessments . Scientific Contributions: Ellers advocates for open-access publishing and interdisciplinary climate change experiments. His leadership in the Dutch Biology Council and co-founding of NLSEB reflect sustained commitment to scientific policy and community engagement. Supervised 23 PhD theses and teaching courses like Ecosystem Services and Scientific Advocacy underscore his mentorship and educational impact.

Kevin Lynchمشاهده پروفایل

استاد

• Robotic Manipulation
• Robot Locomotion
• Physical Human-Robot Interaction
• +۴ مورد دیگر

Kevin Lynch is a Professor of Mechanical Engineering and Director of the Center for Robotics and Biosystems at Northwestern University. He holds a Ph.D. in Robotics from Carnegie Mellon University and a B.S.E. in Electrical Engineering (with honors) from Princeton University. His research focuses on robotic manipulation, robot locomotion, physical human-robot interaction, and distributed control of robot swarms. He has pioneered advancements in exoskeleton control, swarm formation algorithms, and haptic interaction frameworks. Professor Lynch has received significant recognition, including the IEEE Fellow distinction (2010), the Harashima Award (2017), and the Charles Deering McCormick Professor of Teaching Excellence award (2007–2010). He serves as Editor-in-Chief of the IEEE Transactions on Robotics and has authored over 150 peer-reviewed publications. Key contributions include the development of safety-aware human-robot collaboration systems and self-healing swarm control algorithms. He created the ME 333 Introduction to Mechatronics course and the Mechatronics Design Laboratory, fostering interdisciplinary robotics education. His lab, the Center for Robotics and Biosystems, integrates biomechanics with advanced robotics to address challenges in rehabilitation and autonomous systems.

Jonathan Clarkمشاهده پروفایل

استاد

• Robotics
• Legged Locomotion
• Dynamic System Analysis
• +۴ مورد دیگر

Dr. Jonathan Clark is a Professor and Director of the CISCOR at the FAMU/FSU College of Engineering's Department of Mechanical Engineering. His research focuses on bioinspired robotics, legged locomotion, and mechanical design, emphasizing robots for unstructured environments. He holds a Ph.D. (2004), M.S. (2000), and B.S. (1998) in Mechanical Engineering from Stanford University and Brigham Young University, respectively. Key research areas include dynamic climbing robots, compliant leg design, and shape deposition manufacturing. Notable projects involve the Sprawl family of robots and the development of multimodal robots like STARQ and Aquaclimber. His work bridges biomechanics and robotics, with applications in rescue, exploration, and industrial automation. Publications emphasize gait optimization, material science for robotics, and energy-efficient locomotion. Recent trends include bioinspired swimming robots and terrain-adaptive systems. Clark collaborates with biologists and engineers to advance robotics in complex environments. He advises on grants relating to dynamic systems and robotics education, and leads CISCOR's initiatives in advanced manufacturing and robotics innovation. Labs and teams include the CISCOR facility, focusing on prototyping and testing next-generation robotic platforms.

Paul Cohenمشاهده پروفایل

استاد

• Artificial Intelligence
• Data Analysis
• Education Informatics
• +۴ مورد دیگر

Paul Cohen is a Professor of Computer Science at the University of Pittsburgh's School of Computing and Information (SCI), where he also directs the Modeling and Managing Complicated Systems Institute (MOMACS). Previously, he served as the founding Dean of SCI from 2017 to 2020. Before joining Pitt, he was a Program Manager at DARPA (2013–2017), leading initiatives like Big Mechanism and Communicating with Computers. Earlier roles include founding director of the University of Arizona’s School of Information: Science, Technology and Arts (SISTA), and professor at the University of Southern California’s Information Sciences Institute and the University of Massachusetts. Education: PhD in Computer Science and Psychology (Stanford University), MS in Psychology (UCLA), BS in Psychology (UC San Diego). Research Interests: Focuses on artificial intelligence, machine learning, natural language processing, and modeling complex systems like cell signaling pathways and socio-environmental interactions. His work emphasizes explainable AI, human-computer communication, and interdisciplinary problem-solving. Key Contributions: Authored Empirical Methods for Artificial Intelligence and over 200 peer-reviewed articles. His research spans robotics, education technology (e.g., the AnimalWatch tutoring system), and collaborative analysis tools like COLAB. He has won a Telly Award for his video on systemic challenges and a Best Paper award for spatial language learning frameworks. Awards & Recognition: Elected Fellow of the AAAI, recipient of the Telly Award, and winner of the Best Paper Award at the IEEE Conference on Development and Learning. Leadership & Outreach: Advocates for polymathy in education to address global challenges. His work includes developing curricula for complex systems thinking and promoting diversity in STEM through initiatives like AnimalWatch.

Andrea Del Preteمشاهده پروفایل

دانشیار

• Robot Control
• Reinforcement Learning
• Trajectory Optimization
• +۷ مورد دیگر

Andrea Del Prete is an Associate Professor in the Industrial Engineering Department at the University of Trento (Italy) since 2022. His research focuses on robot control, reinforcement learning, trajectory optimization, and numerical algorithms for dynamic systems. He leads the Interdepartmental Robotics Lab (IDRA) and has previously held roles as a tenure-track assistant professor at the University of Trento (2019-2021), a research scientist at the Max-Planck Institute for Intelligent Systems (2018), and an associated researcher at LAAS-CNRS (2014-2017) working with the HRP-2 humanoid robot. Earlier, he conducted PhD and post-doc research at the Italian Institute of Technology (2010-2013) on iCub robot control. PhD in Robotics (2013) - Italian Institute of Technology MEng in Computer Engineering (2009) - University of Bologna BSc in Computer Engineering (2006) - University of Bologna Dr. Del Prete specializes in merging learning and model-based techniques for safe robot control, particularly in legged systems. His work bridges trajectory optimization (TO) with reinforcement learning (RL) to overcome local minima challenges (CACTO/CACTO-SL algorithms) and develops robust controllers for humanoid and quadrupedal robots in unstructured environments. He explores viability kernels in MPC, safety certificates, and bi-level optimization for co-designing hardware/control policies. Key application areas include mountain rescue robotics (ALPINE platform), aerial maneuver recovery, and energy-efficient legged locomotion. His recent publications (2023-2025) emphasize numerical optimization algorithms, multi-contact locomotion, and hybrid control frameworks. Topics span from analytical integral optimization (2025) to climbing robots for mountain operations (2025), demonstrating a trajectory from theoretical algorithm development to real-world robotic applications. Research keywords include robotics, numerical optimization, and machine learning, with sub-fields like MPC for dynamic systems, humanoid control, and terrain adaptation. As an educator, he teaches advanced courses on: Optimization and Learning for Robot Control (48-hour master's course) Optimization-based Control of Legged Robots (12-hour PhD course) Task-Space Inverse Dynamics (3-hour PhD course) Current PhD advisees include Mohammad Hasan Yeganegi (generalization bounds for imitation learning), Pietro Noah Crestaz (numerically-efficient RL), Veronica Campana (ergodic control for defect detection), Elisa Alboni (data-efficient model-based RL), and Gianni Lunardi (MPC for legged locomotion).