جست‌وجوی استاد و پژوهشگر

Mohammad Nayeem Teliمشاهده پروفایل

مدرس ارشد

• Computer Vision
• Machine Learning
• Data Science
• +۳ مورد دیگر

Mohammad Nayeem Teli is a Senior Lecturer in the Department of Computer Science at the University of Maryland, College Park. He holds a PhD and M.S. in Computer Science from Colorado State University and a B.E. in Electronics and Communications from National Institute of Technology, Srinagar. His research focuses on Computer Vision, Machine Learning, and Data Science, with notable projects in vaccine design using protein language models, memory-efficient diffusion models, assistive technology for visually impaired individuals, and robotic navigation in dynamic environments. He has taught courses such as Introduction to Machine Learning , Computer Vision , and Data Science , winning the Excellence in Teaching Award (2018-2019). His work includes collaborations with institutions like Harrisburg University and National Institute of Technology, Srinagar, where he previously served as an Assistant Professor. He is an IEEE Senior Member and has received awards like the Best Oral Presentation Award at IEMTRONICS 2021. His research spans vaccine design with protein models, medical imaging optimization, and assistive robotics. Current projects explore invertible diffusion models for 3D medical imaging and LiDAR-based navigation aids for the visually impaired. Publications highlight contributions to adversarial robustness in autonomous vehicles, face recognition challenges, and resource allocation in online gaming systems.

Vishnu Dutt Sharmaمشاهده پروفایل

پژوهشگر

• Robotics
• Computer Vision
• Deep Learning
• +۴ مورد دیگر

Vishnu Dutt Sharma is a Robotics and Visual Computing Researcher at Nokia Bell Labs . His work focuses on robot perception, planning, and deep learning applications in autonomous systems. He holds a PhD in Robotics from the University of Maryland, College Park , advised by Dr. Pratap Tokekar, and earned his MTech and BTech in Electronics and Electrical Communication Engineering from IIT Kharagpur in 2017, with a minor in Computer Science. His research interests span reinforcement learning, computer vision, and interpretable AI, particularly in robotics and natural language processing. Before his PhD, he worked at American Express India on credit risk management using machine learning. He has interned at Nokia Bell Labs, Comcast, and FlytBase Labs. He received the Kulkarni Foundation Summer Research Fellowship in 2020 for his work at UMD. Key contributions include advancements in robot navigation, next-best-view planning, and generative communication in embodied agents. His interdisciplinary work bridges robotics, computer vision, and NLP, with applications in healthcare, autonomous systems, and security.

Yansha Dengمشاهده پروفایل

استاد

• 5G & 6G Wireless Communications
• Multi-Scale Communications
• Machine Learning
• +۷ مورد دیگر

Professor Yansha Deng is a leading researcher in the Department of Engineering at King’s College London , specializing in 5G/6G wireless communication , multi-scale communication systems , and machine learning applications . She serves as Senior Editor for IEEE Communications Letters and holds editorial roles in multiple top-tier journals. Research Focus : Semantic-aware communications, molecular communication systems, UAV network optimization, and edge AI. Funding : Principal Investigator for £2.6M+ and Co-Investigator for £14M+ from EPSRC, Horizon Europe, DSIT, and industry partners. Scientific Awards include the IEEE Communications Society Best Young Researcher Award (2021), Best Paper Awards at ICC 2016 and GLOBECOM 2017, and exemplary reviewer recognitions. Recent Articles explore semantic communication for robotics, federated learning with LLMs, molecular biosignal analysis, and secure UAV networking—reflecting her interdisciplinary impact.

Erik I Verriestمشاهده پروفایل

استاد

• Mathematical System Theory
• Delay-Differential Equations
• Model Reduction
• +۱۰ مورد دیگر

Erik I. Verriest is a Professor in the School of Electrical and Computer Engineering at Georgia Institute of Technology. He holds academic affiliations including periods at Georgia Tech Lorraine during 1991-1995. His research focuses on mathematical system theory, delay-differential equations, model reduction, optimal control, and periodic/hybrid systems. He earned degrees from Ghent University and Stanford University, with a Ph.D. in 1980. Research interests span control theory applications in biomimetic locomotion, systems with communication constraints, and sensitivity analysis of array algorithms. Notable contributions include work on state-dependent delays, nonlinear systems with state suprema, and gravitational physics modeling. He is a Senior Member of IEEE and recipient of the Francqui Fellowship (1974). His publications emphasize optimal control strategies for multi-agent systems, energy minimization in autonomous vehicles, and stability analysis of systems with delays. Collaborative work includes robotics path planning and observer design for systems with state-dependent delays. Current research explores graceful transitions between periodic behaviors and robust bounds for eigenvalue analysis in delayed systems. Awards include recognition from Belgian American Educational Foundation and academic honors from Sigma Xi and Phi Kappa Phi. His expertise bridges theoretical systems analysis with practical applications in engineering and physics.

Steve Martinمشاهده پروفایل

پژوهشگر

• Robotics
• Autonomous Systems
• Computer Vision
• +۴ مورد دیگر

Steve Martin is a Researcher at the QUT Centre for Robotics, Queensland University of Technology. He holds a Bachelor of Mechatronics (QUT, 2009) and was a former PhD student under Professors Gordon Wyeth and Peter Corke at the QUT Cyphy Lab. Since rejoining QUT in 2016, he has contributed to the Australian Centre for Robotic Vision’s engineering projects, focusing on robotics maintenance, software development, and electrical design. His work spans diverse applications including autonomous agricultural systems for weed control, semi-automated power infrastructure inspection, and robotic coral reef monitoring. Key projects include the 'Mini Autonomous Vehicles' initiative (AOS: Kelpie) and coral reef surveillance systems. Research interests emphasize real-time perception, long-term robot navigation, and energy-efficient robotic systems. He has developed solutions for traversability mapping, proprioceptive sensing, and distributed object tracking. Notable contributions include pandemic-related ventilator design and light field camera adapters. Steve collaborates across disciplines, bridging robotics engineering with environmental and medical applications. Advising and grants: While no current advisees are listed, his PhD supervision experience at QUT and contributions to large-scale robotic projects highlight his mentorship role. He actively engages with industry partnerships, particularly in agricultural and infrastructure robotics. Labs/Teams: Core member of the QUT Centre for Robotics, contributing to cross-disciplinary research in autonomous systems and robotic vision.

James Mountمشاهده پروفایل

مدرس پاره‌وقت

• Robotics Engineering
• Autonomous Vehicles
• Computer Vision
• +۳ مورد دیگر

Dr. James Mount is a robotics engineer, STEM communicator, and sessional academic at Queensland University of Technology (QUT). He specializes in designing robotic systems for real-world applications and promoting technology education through engaging demonstrations. His research focuses on autonomous vehicles, visual localization, and robotics engineering. Mount holds an Honours Degree in Mechatronics Engineering and is awaiting his PhD Final Thesis Examination reviews from the Australian Centre for Robotic Vision. Education: Bachelor of Mechatronics Engineering (Honours) PhD Candidate in Robotics (pending final thesis review) Research interests include autonomous vehicle infrastructure readiness, vision-based robotics, and STEM education outreach. Notable projects include assessing Australian road infrastructure for autonomous vehicles and developing the Carlie mini-autonomous vehicle platform. He has presented at international conferences such as ICRA and IEEE Robotics and Automation Letters. Mount has delivered interactive STEM presentations to large audiences, including guest appearances on children’s TV shows like Brain Buzz and Juiced TV. His work bridges technical innovation with public engagement, emphasizing ethical AI considerations through interactive demonstrations like the Robotronica Trolley Problem exhibit. Labs/Teams: Core contributor to QUT’s Centre for Robotics and the Australian Centre for Robotic Vision. Lead engineer on the Carlie project and BBot Kickstarter initiative.

• Underwater Robotics
• Unmanned Vehicles
• Vehicle Control
• +۷ مورد دیگر

Martin Ludvigsen is a Professor and manager of the Applied Underwater Laboratory (AUR-Lab) at NTNU's Department of Marine Technology. He also holds an adjunct professorship at Svalbard University Centre (UNIS) and is affiliated with NTNU AMOS. His research focuses on underwater robotics, unmanned vehicles, Arctic technology, and autonomous systems. He teaches courses like TMR4120 Underwater Engineering and leads the AUR-Lab, which develops robotic platforms for marine research. Research interests include vehicle control, autonomy, acoustic navigation, and Arctic observation systems. Collaborations involve deploying robotic vehicles in the Arctic and deep-sea environments. He has advised multiple PhD students and contributed to projects on ocean mapping, environmental monitoring, and robotic sampling. Key contributions include advancing underwater hyperspectral imaging, developing adaptive sampling strategies, and improving AUV navigation. His work bridges engineering and environmental science, addressing challenges in marine exploration and resource management.

Giulio Rossoliniمشاهده پروفایل

استادیار

• Adversarial Machine Learning
• Computer Vision
• Deep Learning
• +۶ مورد دیگر

Giulio Rossolini is an Assistant Professor (from June 2024) specializing in adversarial machine learning, computer vision, and deep learning security. Previously, he was a Postdoctoral researcher (Jan 2024) and a PhD student (Oct 2020–Mar 2024). His work focuses on enhancing the robustness of AI systems against adversarial attacks, particularly in autonomous driving and vision applications. Key research areas include adversarial defense mechanisms, dataset generation for robustness evaluation, and safety-critical AI systems. He has contributed to frameworks like CARLA-GeAR and TrainSim for systematic evaluation of deep learning models. Notable achievements include the IEEE TCCPS Early-Career Award 2023. His publications span topics such as real-time adversarial defenses, synthetic dataset development, and ethical AI considerations. Current projects emphasize bridging gaps between theoretical robustness and practical deployment in autonomous systems.

Soichiro MINAMIمشاهده پروفایل

مدرس

• Public Finance
• Environmental Economics
• Transportation Policy
• +۳ مورد دیگر

Soichiro MINAMI is a Lecturer at Kanazawa University's Department of Interdisciplinary Sciences, Institute of Interdisciplinary Research. He holds a Ph.D. in Economics from Kyoto University and has held academic positions including Assistant Professorships at Kyoto University and Chuo University. His research focuses on public finance, environmental economics, and transportation policy, with emphasis on sustainable mobility and urban policy innovation. He has conducted extensive studies on light rail transit (LRT) systems, comparing French and Japanese approaches to transport infrastructure financing and governance. MINAMI's career includes roles as a Research Fellow at MLIT's Policy Research Institute and a visiting researcher at Chuo University. He participated in the FFJ/Valeo Chair program (2018-2019), examining local government roles in sustainable transport policies. His work integrates case studies from cities like Grenoble and Helsinki to analyze urban mobility challenges and policy solutions. Key research themes include: sustainable transport policy frameworks, LRT implementation strategies, public consultation practices in infrastructure projects, and the role of fiscal policies in fostering innovation. He has authored over 15 peer-reviewed articles and contributed to books on LRT planning and urban experimentation. MINAMI actively participates in international research networks, including OECD's Transport Forum working groups and Japan Urban Center committees. His teaching spans courses on transportation policy, environmental economics, and global environmental studies at multiple universities.

Pedro Castilloمشاهده پروفایل

پژوهشگر

• Nonlinear Control
• Robust Control
• Reactive Control
• +۷ مورد دیگر

Pedro Castillo is a DR CNRS Researcher at the Heudiasyc laboratory within the University of Technology of Compiègne, France. He leads the SyRI team (Systèmes Robotiques en Interaction) and oversees drone-related activities at the laboratory. His research focuses on nonlinear control, robust navigation, multi-agent systems, and resilient control strategies for unmanned aerial vehicles (UAVs). He has contributed significantly to the theoretical and experimental validation of control schemes for under-actuated systems, emphasizing real-time implementation on robotic platforms. His work bridges theoretical advancements and practical applications, particularly in aerial robotics and cooperative control architectures. Dr. Castillo has supervised 19 PhD students (15 defended, 3 ongoing, and 1 cotutelle), managed 29 research projects, and organized over 50 seminars at Heudiasyc. He is an Associate Editor for the IEEE Robotics and Automation Letters (2020–2024) and has participated in numerous academic committees, including ANR and HCERES evaluations. His research has resulted in over 170 scientific publications, including two influential books on aerial vehicle modeling and control. Key contributions include the design of resilient control algorithms, multi-agent coordination frameworks, and hardware prototypes such as the PVTOL, octarotor, and ROMEO quadrotor. His work has been showcased at international conferences and trade fairs, solidifying Heudiasyc's reputation as a leader in UAV control research.

• Computer Vision
• Machine Learning
• Visual Computing
• +۴ مورد دیگر

Rafael Sterzinger is a PreDoc Researcher at the Institute of Visual Computing and Human-Centered Technology within TU Wien's Faculty of Informatics. Holding a BSc and MSc from ETH Zurich, he teaches courses in Computer Vision and Machine Learning for Visual Computing while pursuing his PhD. Education MSc in Computer Science, ETH Zurich BSc in Computer Science, ETH Zurich Research Interests Sterzinger's work centers on Computer Vision and Visual Computing , specializing in segmentation techniques for historical documents, cultural heritage artifacts, and WiFi-based sensing applications. His research integrates human-in-the-loop systems with deep learning for refinement tasks, explores reinforcement learning for building automation, and develops domain adaptation methods for cross-scenario human activity recognition. Key domains include Etruscan art digitization, through-wall imaging, and historical map analysis. Research Trends Analysis of Sterzinger's 2023-2025 publications reveals three dominant threads: (1) Few-shot segmentation for historical materials using foundation models, (2) Human-guided refinement pipelines that merge algorithmic precision with user input, and (3) Wireless sensing applications leveraging WiFi channel state information for through-wall imaging and activity recognition. His work consistently addresses data scarcity through innovative adaptation techniques while maintaining real-world applicability in cultural heritage and smart infrastructure. Projects EtMirA (2021-2027): Through-Wall Imaging Based on WiFi Channel State Information Blindsight (2023-2025) MAIJA (2024-2025): Closing the Gap in Human Behavior Analysis via Trimodal Data Synthesis KIIS (2021-2023): Deep Segmentation for Extracting Art from Ancient Etruscan Mirrors Advising and Grants No advisees are documented. Sterzinger participates in multiple externally funded projects including EtMirA's €1.2M infrastructure grant for cultural heritage digitization and MAIJA's interdisciplinary initiative synthesizing audio-visual-tactile data for behavior modeling, demonstrating sustained grant acquisition in visual computing domains.

Saadمشاهده پروفایل

پژوهشگر

• Underwater Robotics
• Swarm Intelligence
• Autonomous Systems
• +۳ مورد دیگر

Saad is a Robotics Researcher at the Massachusetts Institute of Technology (MIT), specializing in underwater robot swarms. He completed a PhD in underwater robotics at ENSTA Bretagne, supported by CGG, and holds a double degree in engineering and a Master’s in Dynamic Systems and Signals from Université d’Angers. His work focuses on localization of autonomous underwater vehicles (AUVs) using set-theory methods, with projects like SpiceRack® and Moussafir addressing seismic exploration and oil reserve detection via robot swarms. He has secured patents for his innovations and emphasizes ecological marine exploration through energy-efficient systems. Education includes ENSTA Bretagne’s Robotics program, where he led the Spacieta club, and a collaborative final project with Graaltech in Italy. His research at MIT continues at the River Charles lab, enabling realistic testing of swarm control systems. Saad’s career bridges industry (CGG) and academia, driven by technical challenges and sustainable exploration goals.

• Control Systems
• Marine Robotics
• Autonomous Systems
• +۳ مورد دیگر

Henrik Schmidt-Didlaukies is a Research Fellow in the Department of Engineering Cybernetics at NTNU. His work focuses on advanced control systems for marine and robotic systems, with a particular emphasis on path following, navigation, and robust control methodologies. He has contributed to projects involving underwater vehicles, autonomous marine systems, and sensor-based control strategies. His research integrates theoretical frameworks with practical applications, including experiments in confined maritime environments and cooperative robotic systems. Key research areas include: Nonlinear control and adaptive systems Path planning and guidance algorithms Underwater robotics and vehicle dynamics Autonomous navigation and sensor fusion Collision avoidance and safety-critical systems Recent work highlights include developing anti-windup guarantees for curved path guidance, learning-based optimization for marine vehicles, and experimental validation of obstacle-aware collision avoidance. He has presented findings at major conferences including IFAC World Congress and IEEE OES events.

Ahmad Radمشاهده پروفایل

استاد

• Autonomous Systems
• Driverless Cars
• Simultaneous Localization and Mapping (SLAM)
• +۱ مورد دیگر

Ahmad Rad is a Professor and Graduate Student Supervisor at the School of Mechatronic Systems Engineering , part of the Faculty of Applied Sciences at Simon Fraser University . He holds a Ph.D. in Electrical Engineering from the University of Sussex (1989) and has dedicated his career to advancing autonomous systems and intelligent control. Education: Ph.D., University of Sussex, UK (1989) M.Sc., University of Bradford, UK (1986) B.Sc., Abadan Institute of Technology, Iran (1977) His research focuses on autonomous systems , with particular emphasis on driverless cars , SLAM (Simultaneous Localization and Mapping), and intelligent control mechanisms. His recent publications reveal a strong trend toward improving robotic navigation, adaptive control systems, and human-robot interaction frameworks. Professor Rad has been instrumental in teaching core mechatronic engineering courses such as Electric Circuits, Systems Modeling and Simulation, and Industrial Control Systems. His work bridges theoretical research with practical implementation in mechatronic and automotive domains.

• Robotics
• Autonomous Vehicles
• Computer Vision
• +۳ مورد دیگر

Matthew Gadd is a Postdoctoral Research Assistant at the University of Oxford and a Junior Research Fellow at Kellogg College. He works in the Mobile Robotics Group (MRG) at the Oxford Robotics Institute (ORI), focusing on Robotics, Autonomous Vehicles, Computer Vision, and Machine Learning. His research addresses challenges in sensor systems, autonomous navigation, and robust place recognition in complex environments. He holds a DPhil in Engineering Science from Keble College, Oxford, and a BSc in Mechatronics Engineering from the University of Cape Town. Education: PhD (DPhil) in Engineering Science, Keble College, University of Oxford (20XX–20XX) BSc in Mechatronics Engineering, University of Cape Town, South Africa Research Projects: Sense Assess eXplain (SAX): Developing auditable autonomous vehicle systems Oxford Offroad Radar Dataset (OORD): Creating datasets for offroad navigation Autonomous biodiversity monitoring using long-term visual navigation Publications Highlights: Gadd’s recent work includes advancements in radar place recognition, uncertainty estimation, and LiDAR-based localization. His research often bridges theory and practice, with applications in autonomous vehicles and environmental robotics. Awards: 2013 FirstRand Laurie Dippenaar Scholarship Labs & Teams: Active contributor to the Oxford Robotics Institute and Mobile Robotics Group, collaborating with Prof. Paul Newman and international research networks.