جست‌وجوی استاد و پژوهشگر

Mohammad A. Khanمشاهده پروفایل

استادیار

• Environmental Monitoring
• Photonics
• Sensor Technology
• +۵ مورد دیگر

Mohammad A. Khan, PhD, is an Assistant Professor and Interim Director of Imaging at Delaware State University (DSU), affiliated with the Division of Physics, Engineering, Mathematics, and Computer Science within the College of Agriculture, Science, and Technology (CAST). He holds a Ph.D. in Electrical and Computer Engineering from Old Dominion University and an M.S. in Physics from the Indian Institute of Technology, New Delhi. His research focuses on low-power laser-based sensors, mid-infrared (mid-IR) spectroscopy using quantum cascade lasers, and environmental monitoring. Key areas include developing compact greenhouse gas sensors for unmanned aerial vehicles (UAVs) and sensor networks, enabling applications in atmospheric research and industrial emissions tracking. His work emphasizes cost-effective, non-intrusive measurement systems for trace gas detection in environments such as the planetary boundary layer. Dr. Khan teaches courses such as ENGR 212 (Signals and Systems), ENGR 211 (Introduction to Sequential Circuits), and ENGR 310 (Optical Electronics). He is part of the Advanced Quantum Sensing Center at DSU, contributing to cutting-edge photonic sensor technologies for environmental and health applications. No scientific awards, grants, or advising records are explicitly listed in his profile. His research priorities include advancing mid-IR sensor systems for hazardous chemical detection and improving sensor autonomy for field and airborne applications.

Lantao Liuمشاهده پروفایل

دانشیار

• Robotics
• Artificial Intelligence
• Autonomous Vehicles
• +۲ مورد دیگر

Lantao Liu is Associate Professor of Intelligent Systems Engineering at Indiana University's Luddy School, directing the Vehicle Autonomy and Intelligence Lab (VAIL). His research enhances autonomy capabilities for unmanned ground, aerial and aquatic vehicles. Research develops planning, learning and coordination algorithms for single/multi-robot systems applied to autonomous navigation, environmental monitoring, search and rescue operations, and intelligent transportation systems. Current projects focus on adaptive control strategies for heterogeneous robot teams in dynamic environments. Prior to joining IU, Dr. Liu held postdoctoral positions at University of Southern California and Carnegie Mellon University. He holds a PhD in Computer Science from Texas A&M University (2013) and BS from Beijing Institute of Technology (2007).

Stephan Olariuمشاهده پروفایل

استاد

• Vehicular Ad Hoc Networks (VANETs)
• Cybersecurity
• Telemedicine
• +۴ مورد دیگر

Stephan Olariu is a Professor of Computer Science at Old Dominion University (ODU), affiliated with the College of Sciences. He holds a Ph.D., M.Sc., and B.S. in Computer Science from McGill University (1982–1986). His research focuses on vehicular ad hoc networks (VANETs), cybersecurity, telemedicine, and vehicular cloud computing. He has led projects like TRENDS, a cyber-physical system for traffic event detection, funded by ODU (2011). Dr. Olariu's work emphasizes vehicular networks' security and efficiency, including solutions for VANETs, UAV-based medical supply delivery, and blockchain-driven decentralized marketplaces. He explores smart city technologies, such as traffic optimization and environmental impact reduction. His recent publications address topics like drone coordination for surveillance, trust frameworks in blockchain systems, and UAV applications in counterterrorism. Grants: TRENDS (2011) and others focused on vehicular systems and telemedicine. Key Themes: Vehicular cloud computing, cybersecurity, UAV systems, and smart infrastructure. His contributions span academic leadership in computer science, with a focus on translating theoretical research into real-world applications like emergency response systems and resilient decentralized platforms.

Xiang Changمشاهده پروفایل

مدرس

• Robotics
• Control Systems
• Neural Networks
• +۳ مورد دیگر

Xiang Chang is a Lecturer in the Engineering Unit at Aberystwyth University, within the Faculty of Business and Physical Sciences. His research focuses on robotics, control systems, and neural networks. He holds a Doctor of Philosophy (PhD) from Aberystwyth University, completing his thesis titled 'Robotic Imitation Learning from Videos: Boosting Autonomy and Transferability' in 2024. Research Interests: Robotics and Aerial Manipulation Control Systems and Nonlinear Dynamics Neural Networks and Deep Learning Image Processing and Computer Vision Reinforcement Learning and Optimization His recent work emphasizes advancements in unmanned aerial systems, neural network compression, and improving training efficiency in diffusion models. Key contributions include studies on convergence time control for aerial manipulators and techniques for long-tailed recognition in deep learning. Grants & Supervision: While no grants are explicitly listed, his thesis supervision indicates involvement in guiding research in robotic imitation learning and autonomous systems. He collaborates internationally, with research outputs often involving interdisciplinary teams. Labs/Teams: Active in the Engineering Unit's robotics and control systems research groups at Aberystwyth University.

Lilian Lieberمشاهده پروفایل

پژوهشگر ارشد

• Marine Ecology
• Ocean Technology
• Biological Oceanography
• +۳ مورد دیگر

Lilian Lieber is a Senior Research Fellow at the University of Plymouth's School of Biological and Marine Sciences. Previously, she held positions at Queen’s University Belfast, Bangor University, and the Marine Biological Association. She earned her Doctorate from the University of Aberdeen in 2016, focusing on basking shark ecology. Her research integrates ocean observation technologies like aerial drones and bioacoustics to study marine predator behavior in changing environments, particularly addressing anthropogenic impacts such as ocean energy development. She teaches courses including Marine Environmental Monitoring and Biological Oceanography. Her work emphasizes interdisciplinary approaches, linking bio-physical dynamics to predator foraging strategies. She has contributed to understanding environmental impacts of tidal turbines and coral reef ecosystems. Lieber is a member of the Challenger Society for Marine Science and serves on the Executive Board of the National Centre for Coastal Autonomy.

Ningshi Yaoمشاهده پروفایل

استادیار

• Control Systems
• Human-Robot Interaction
• Cyber-Physical Systems
• +۵ مورد دیگر

Ningshi Yao is an Assistant Professor in the Department of Electrical and Computer Engineering at George Mason University. Her research focuses on control systems, human-robot interaction, and bio-inspired robotics. She holds a PhD from Georgia Institute of Technology (2020) and a BS in Automatic Control from Zhejiang University (2014). Prior to her current role, she was a postdoctoral research fellow at Georgia Tech (2020-2021). Her work emphasizes real-time scheduling, cyber-physical systems, and machine learning applications. Notable projects include developing contention-resolving control methods for resource-constrained systems and creating lighter-than-air autonomous blimps for efficient navigation. Recent achievements include dual awards for groundbreaking robotics research (2025). Dr. Yao collaborates with faculty and students on cutting-edge robotics systems, such as blimps for rapid environmental response and medical robotics for ocular imaging. Her lab, part of George Mason's MARC initiative, explores autonomy, robotics, and ethical AI integration.

• Autonomous Systems
• Control Systems
• Robotics
• +۷ مورد دیگر

Professor Antonios Tsourdos is a leading academic in autonomous systems and control engineering at Cranfield University, where he serves as Professor of Autonomous Systems and Control and Director of the Centre for Autonomous and Cyber-physical Systems. His career spans over two decades with significant contributions to guidance, navigation, and control systems for unmanned vehicles. He has held leadership positions including Head of the Autonomous Systems Group (2007), Head of the Centre of Autonomous and Cyber-Physical Systems (2012), and Director of Research for Aerospace, Transport and Manufacturing (2015). Professor Tsourdos earned his academic qualifications from prestigious UK institutions: MEng in Electronic, Control and Systems Engineering from the University of Sheffield (1995), MSc in Systems Engineering from Cardiff University (1996), and PhD in Nonlinear Robust Flight Control Design and Analysis from Cranfield University (1999). His research focuses on autonomy for single and multiple unmanned vehicles, with particular expertise in guidance and control systems, mission planning, multi-agent coordination, and UAS traffic management. Professor Tsourdos has published extensively in top-tier journals, with over 100 publications in the last five years alone, demonstrating his active research program and leadership in the field. His work bridges theoretical control systems with practical aerospace applications. His research portfolio includes significant projects such as CHEDDAR (Communications Hub for Empowering Distributed ClouD Computing), Air Mobility Ecosystem Consortium, Project BLUEPRINT for UTM-enabled drone operations, and the UKRI Trustworthy Autonomous Systems Node in Security. These projects are funded by UKRI, ESA, Horizon Europe, and major industry partners including BAE Systems, Lockheed Martin, Boeing, Airbus, and Thales. Professor Tsourdos has received notable recognition including Fellowship in the Royal Aeronautical Society, membership in the winning team for the UK MoD Grand Challenge (2008), and the IET Innovation Award (2009). He served as chair of the IFAC Technical Committee on Aerospace Control (2017-2023) and has been involved with the BSI Future Flight Standards Hub and AIAA Advanced Aerial Mobility Certification Task Force. He serves on the editorial boards of numerous prestigious journals including Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering; Aerospace Science and Technology; and IEEE Transactions on Aerospace and Electronic Systems. His work has significant industrial impact through collaborations with major aerospace and defense companies.

• Integrated intelligent and energy systems
• Urban mobility solutions
• Unmanned aerial vehicle (UAV) systems
• +۳ مورد دیگر

Professor Mircea BOȘCOIANU is affiliated with the University of Technical Education in Brașov (UNITBV), serving in the Department of Engineering and Industrial Management under the Faculty of Technological Engineering and Industrial Management. His research focuses on integrated intelligent systems, UAV innovation for defense, sustainable development frameworks, and autonomous vehicle methodologies. Education & Background: Details about formal education not explicitly provided in text. Research Interests: Specializes in designing enterprise systems for sustainability using dynamic capabilities and option pricing models. Explores unmanned systems (UAV/UUV/UGV) for defense applications, urban mobility solutions, and extreme risk assessment in aviation. Utilizes advanced AI techniques for system autonomy and remote control. Publications: Recent work includes studies on muscle performance analysis in strength training and risk assessment methodologies for aviation systems, reflecting interdisciplinary approaches between engineering and applied sciences. Awards & Grants: No specific honors or grants mentioned in the provided text. Advising & Labs: No student advisees listed. May be involved in research teams focused on UAV systems and enterprise engineering through UNITBV's research infrastructure.

Zachary Sunbergمشاهده پروفایل

استادیار

• Aerospace autonomy
• Partially observable Markov decision processes (POMDPs)
• Game theory
• +۵ مورد دیگر

Zachary Sunberg is an Assistant Professor in the Ann and H.J. Smead Aerospace Engineering Sciences Department at the University of Colorado Boulder. He is affiliated with the Research and Engineering Center for Unmanned Vehicles (RECUV) and leads the Autonomous Decision and Control Lab (ADCL). His research focuses on artificial intelligence for autonomous systems, particularly in aerospace autonomy, decision-making under uncertainty (via POMDPs), and human-AI interaction. Sunberg holds a PhD from Stanford University (2018), an MS and BS from Texas A&M University (2013, 2011). His work spans algorithm development for autonomous vehicles, including safe and efficient driving, rotorcraft control, and game-theoretic planning. Notable contributions include the POMCP and POMCPOW algorithms for continuous POMDPs, and open-source frameworks like POMDPs.jl. He has received a NSF CAREER Award (2024) and a NSF Graduate Fellowship (2012). Academic roles include mentoring the AI4ALL program, teaching courses on decision-making under uncertainty, and advising projects at the intersection of robotics and AI. His lab collaborates on applications ranging from weather observation to human-centered autonomy in unmanned systems.

Yvan Petillotمشاهده پروفایل

استاد

• Marine Robotics
• Autonomous Systems
• Sensor Processing
• +۴ مورد دیگر

Yvan Petillot is a Professor of Robotics and Autonomous Systems at Heriot-Watt University, co-academic lead of the National Robotarium, and chair of Robotics at the Scottish Research Partnership in Engineering. His expertise spans marine robotics, autonomous systems, sensor fusion, and subsea domain control. He leads a £3M grant portfolio focused on marine robotics innovations, emphasizing multi-vehicle collaboration and AI-driven autonomy. Petillot co-founded SeeByte Ltd to translate academic research into commercial solutions and pioneered EU robotics competitions fostering talent. His research emphasizes underwater robotics, including navigation, perception, and intervention in hazardous environments. Notable achievements include developing advanced underwater imaging techniques, reinforcement learning platforms (e.g., MarineGym), and frameworks for digital twins in teleoperation. He has received the Royal Society Industry Fellowship (2013) and was part of the 2022 Research Team of the Year award. Key technical contributions include synthetic aperture sonar systems, underwater SLAM (Simultaneous Localization and Mapping), and control strategies for vehicle-manipulator systems. His work addresses challenges in autonomous exploration, environmental monitoring, and safe human-robot collaboration in marine and industrial settings.

Juan Sandinoمشاهده پروفایل

پژوهشگر ارشد

• Autonomous Systems
• Reinforcement Learning
• Remote Sensing
• +۶ مورد دیگر

Dr. Juan Sandino is a Research Fellow at the QUT Centre for Robotics, affiliated with the School of Electrical Engineering and Robotics at Queensland University of Technology (QUT). He holds a BEng (Mechatronics) from Nueva Granada Military University and a PhD in Robotics and Autonomous Systems from QUT (2022). His research focuses on autonomous UAV decision-making, machine learning, and remote sensing for environmental monitoring, biosecurity, and search and rescue operations. Education : PhD in Robotics and Autonomous Systems (2018–2022), QUT Bachelor of Engineering (Mechatronics, 2010–2015), Nueva Granada Military University Diploma in Project Management (2017–2018), Australian Pacific College Research Interests : Dr. Sandino specializes in developing drone-based solutions for environmental challenges. His work integrates autonomous systems, reinforcement learning, and hyperspectral imaging to address issues such as biosecurity threats, Antarctica's fragile ecosystems, and search and rescue missions in GPS-denied environments. His projects include UAV frameworks for planetary exploration (UAV4PE), detection of invasive species like Bitou Bush and Parthenium Weed, and real-time vegetation monitoring in polar regions. Awards & Recognition : CSIRO Data61 PhD and Top-Up Scholarships (2018–2021) Best Team Award, QUT Centre for Robotics (2021) Phase 1 Finalist, OpenCV AI Competition (2021) Projects & Grants : He leads projects funded by the Australian Research Council (SAEF initiative) and industry partners, including aerial mapping of forests affected by pathogens, UAV-based monitoring in Antarctica, and pest risk modeling for Buffel Grass. His work emphasizes collaboration with organizations like CSIRO Data61 and Charles Sturt University. Labs & Teams : Dr. Sandino contributes to the Securing Antarctica’s Environmental Future (SAEF) initiative and collaborates with interdisciplinary teams at QUT’s Centre for Robotics. His research integrates robotics software (ROS, PX4), sensor instrumentation, and AI for real-world applications.

Troy Bruggemannمشاهده پروفایل

مدرس ارشد

• UAV
• Aerospace Engineering
• Control Systems
• +۷ مورد دیگر

Dr. Troy Bruggemann is a Senior Lecturer at Queensland University of Technology (QUT), specializing in aerospace engineering and robotics. He holds a PhD and Master of Engineering from QUT, with over 15 years of research experience in aerospace automation, precision navigation, and sensor systems. His work focuses on UAV autonomy, swarm systems, and infrastructure inspection technologies. Notable contributions include developing the Fugro ROAMES system for global infrastructure monitoring and advancing bushfire response strategies through simulation and uncertainty quantification. Education : PhD in Aerospace Engineering, QUT (2005-2009) Master of Engineering, QUT (2003-2004) Research Interests : Dr. Bruggemann’s research spans UAV autonomy, air traffic management, sensor fusion, and disaster response systems. His work integrates robotics, control systems, and computational modeling to address challenges in aerospace automation and infrastructure monitoring. Key areas include: Unmanned aircraft systems (UAS) for remote inspection Swarm intelligence and multi-UAV coordination Autonomous decision-making frameworks Air traffic management for uncrewed systems Uncertainty quantification in complex systems Publications : His recent work emphasizes airspace management, emergency response systems, and UAS reliability. Notable trends include: Advancements in UAV swarm coordination and safety Applications of simulation for disaster resilience Development of robust decision frameworks for autonomous systems Awards : 2015 Vice Chancellors Performance Award 2014 Queensland Government Accelerate Fellowship 2013 Vice Chancellors Performance Award 2011 Vice Chancellor’s Team Award for Excellence Advising & Grants : He has supervised at least one doctoral student and secured a QLD State Government grant for multi-UAV control research. His work with Fugro ROAMES and CASA demonstrates industry collaboration in advancing UAS technologies. Labs & Teams : Prominent affiliations include the QUT Centre for Robotics and the Australian Research Centre for Aerospace Automation, where he contributes to cutting-edge robotics and aerospace projects.

Jasmin Martinمشاهده پروفایل

مدرس

• Artificial Intelligence
• Electrical Engineering
• Aerospace Autonomy
• +۳ مورد دیگر

Dr. Jasmin Martin is a Lecturer and Research Fellow at Queensland University of Technology's School of Electrical Engineering & Robotics. She completed her Doctor of Philosophy at QUT and specializes in artificial intelligence applications for aerospace systems. Her primary affiliations include the QUT Centre for Robotics where she conducts research on autonomous systems. Martin's research focuses on artificial intelligence, electrical engineering, and aerospace autonomy, with particular emphasis on computer vision and deep learning solutions for aircraft detection and collision avoidance in unmanned systems. Her work bridges theoretical AI concepts with practical aerospace applications. Her publications demonstrate consistent focus on vision-based detection systems for aircraft, utilizing deep learning techniques and synthetic data generation. Recent work explores collision avoidance algorithms and dataset development for autonomous aerial systems.

Felipe Gonzalezمشاهده پروفایل

استاد

• Aerial Robotics
• Automation
• Unmanned Aerial Systems (UAVs)
• +۶ مورد دیگر

Professor Felipe Gonzalez is a Professor at the School of Electrical Engineering and Robotics (EER) within the Engineering Faculty at Queensland University of Technology (QUT). He leads the Airborne Sensing Lab and is a Chief Investigator (CI) in the QUT Centre for Robotics (QCR). His research focuses on aerial robotics, UAV automation, and remote sensing, with applications in environmental monitoring, biosecurity, and wildlife conservation. He holds a PhD in Aeronautical Engineering from the University of Sydney. Dr. Gonzalez has secured over $47.1M in grants, including ARC DP, ARC Linkages, CRC projects, and industry partnerships. His work emphasizes translating scientific outcomes into practical solutions for autonomy, sensor design, and UAV-based data analysis. Notable achievements include the Green Falcon solar-powered UAV, which won the iENA 2011 Gold Medal and EDN Innovation Award. His research spans UAV navigation in GPS-denied environments, precision agriculture, and AI-driven environmental monitoring. He has authored/co-authored nearly 130 refereed papers and several books on UAV design and optimization. Professional affiliations include Engineers Australia, AIAA, and the Royal Aeronautical Society. Awards include the Engineers Australia Excellence Award (2010), Vice-Chancellor’s Award (2011), and Chartered Professional Engineer (CPENG) certification. His teaching spans systems engineering, aerospace design, and UAV technologies, with consistently high student evaluations. Current projects include Antarctic vegetation monitoring, multi-UAV path planning, and AI-driven pest surveillance. The Airborne Sensing Lab collaborates with industry and international partners to advance UAV applications in environmental and industrial domains.

Tamás Molnárمشاهده پروفایل

استادیار

• Nonlinear Dynamics and Control
• Safety-Critical Control
• Time Delay Systems
• +۳ مورد دیگر

Dr. Tamás Molnár is an Assistant Professor of Mechanical Engineering at Wichita State University (since Fall 2023), leading the SANDy (Safe Autonomy & Nonlinear Dynamics) Lab. His expertise spans nonlinear dynamics and control, safety-critical systems, and time delay systems, with applications in connected automated vehicles, robotic systems, and autonomous systems. His research emphasizes ensuring safety while optimizing performance through theoretical analysis, simulations, and experiments. Dr. Molnár holds a Ph.D. (2018) and M.Sc. (2015) in Mechanical Engineering, and a B.Sc. (2013) in Mechatronics Engineering from Budapest University of Technology and Economics. He completed postdoctoral work at Caltech (2020–2023) and the University of Michigan, Ann Arbor (2018–2020). His lab focuses on advancing autonomy and safety in dynamic systems, including robotic inspection, autonomous vehicle coordination, and safe human-robot collaboration. Current advisees include PhD students Laszlo Gacsi (2024) and Shaibal Das (2025). Prospective students are encouraged to submit interest via a dedicated form. His work has been supported by initiatives like the Kansas NASA EPSCoR Partnership Development Grant, involving collaborations with NASA JPL. Key research themes include control barrier functions, traffic control via connected vehicles, and experimental validation of safety-critical systems.