جست‌وجوی استاد و پژوهشگر

Fawaz Y Annazمشاهده پروفایل

دانشیار

• Robotics
• Unmanned Aerial Vehicles
• Control Systems
• +۴ مورد دیگر

Dr. Fawaz Y Annaz serves as Reader in Mechatronics at Birmingham City University, leveraging an international research career spanning the UK, Singapore, Japan, Malaysia, and Brunei. His expertise encompasses mechatronics engineering, robotics, and smart actuation systems, with significant contributions to aerospace, energy, and biomedical applications through leadership of the High Integrity System Laboratory and Mechatronics Group. His academic foundation includes: BSc in Electrical and Electronic Engineering (1987, University of East London) focusing on Electromagnetic Vehicle Levitation Control MSc in Engineering of Dynamic Systems (1989) researching Helical and Planar Induction Actuators PhD in Avionics (1996) addressing Architectures Consolidation in High Integrity Multi-Lane Smart Electric Actuators Dr. Annaz's research integrates robotics, control theory, and energy systems with notable emphasis on unmanned aerial vehicles (including swarm systems), microgrid resilience engineering, and electromechanical actuation. His multidisciplinary approach bridges theoretical control systems with practical applications in aerospace actuation, sustainable energy management, and speech production analysis, demonstrating consistent innovation across diverse engineering domains. Analysis of his publication trajectory reveals evolving research priorities: early work (2000-2015) centered on UAV navigation, actuator monitoring, and speech phoneme signatures, while recent publications (2020-2025) show strategic pivot toward AI-driven microgrid resilience, battery life optimization, and advanced UAV control systems—reflecting growing industry demand for sustainable energy solutions and autonomous systems. Scientific recognition includes: Granted European Patent for electromechanical actuator technology Two international patent applications Over 50 peer-reviewed publications Book and book chapters in mechatronics As an educator and research leader, Dr. Annaz has supervised numerous MSc and PhD students while directing international projects including Japanese Ministry of Education collaborations. His research output includes commercialization efforts for patented actuator technologies and development of educational platforms for robotics training. Current focus areas encompass deep reinforcement learning for energy management and swarm UAV systems. His laboratory initiatives include the High Integrity System Laboratory (operating in Japan and Malaysia) specializing in vibration control, active magnetic bearing systems, and artificial heart development, alongside the Malaysia-based Mechatronics Group advancing industrial robotics and unmanned vehicle technologies.

Fabio Morbidiمشاهده پروفایل

دانشیار

• Robotic Vision
• Multi-robot Systems
• Event-Based Perception
• +۳ مورد دیگر

Fabio Morbidi is an Associate Professor (Maître de Conférences HDR) at the Université de Picardie Jules Verne (UPJV), France, where he heads the Robotic Perception group at the MIS laboratory since 2022. His office is located at 33 Rue Saint-Leu, Amiens. He holds a Ph.D. in Robotics and Automation from the University of Siena (2009) and conducted postdoctoral research at Northwestern University, University of Texas at Arlington, and Inria Grenoble. His research focuses on multi-robot systems, event-based vision, autonomous vehicles, and assistive robotics. Research interests span robotic vision, distributed control, and sensor fusion for applications in exploration, wheelchair assistance, and drone technology. His work emphasizes real-world implementations, such as the SpheriCol driving assistant for power wheelchairs and event-based perception for autonomous vehicles. Awards include ICRA'25 Best Paper Award Finalist and contributing to an IEEE RAM issue that received the APEX 2024 Awards of Excellence. He actively advises PhD students and coordinates ANR projects (e.g., CERBERE, DEVIN) focused on robotic perception. He serves as Associate Editor for IEEE Transactions on Robotics and IEEE Robotics and Automation Letters.

Muhammad Usman Hadiمشاهده پروفایل

مدرس

• Machine Learning for IoT
• Optical Communication
• Wireless Communication
• +۷ مورد دیگر

Dr. Muhammad Usman Hadi serves as a Lecturer (Assistant Professor) of Electronics and Communication Engineering in the School of Engineering at Ulster University, Belfast campus. With extensive experience in both academia and industry, he previously worked as a Post-Doctoral researcher at Aalborg University and as an External Research Engineer at Nokia Bell Labs in Denmark (2019-2021). His research focuses on cutting-edge areas including machine learning applications for IoT, optical communication systems, wireless networks, UAV/drones, and next-generation 5G/6G technologies. His specific interests include Time Sensitive Networks, microwave photonics, Radio over Fiber (RoF) systems, and wireless sensor networks. Dr. Hadi has made significant contributions to the field, being recognized as a top 2% cited researcher worldwide for three consecutive years (2021-2023). His recent publications demonstrate a strong trend toward AI-enhanced communication systems, particularly for 6G networks, with emphasis on MIMO detection, signal processing, and drone-based communication systems. His work bridges theoretical advancements with practical applications in next-generation wireless infrastructure. Top 2% Researcher 2021 Top 2% Researcher 2022 Top 2% Researcher 2023 Research and Impact Fund (2023) Dr. Hadi currently supervises two PhD students: Ms. Cara Rose (funded by the Department of Economy) and Mr. M.Y. Daha (funded by the Vice Chancellor's Research Studentship). He leads innovative research projects including drone-based climate resilience initiatives and IoT-driven cybersecurity frameworks for drone networks. His laboratory has developed the MADNI (Made in UU) drone platform equipped with state-of-the-art 5G connectivity, object detection, and facial recognition capabilities, which serves as a testbed for many of his research initiatives in wireless communications and drone networking.

Shuai ZHANGمشاهده پروفایل

پژوهشگر ارشد

• Swarm robots
• Robotics and autonomous systems
• Multi-robot/agent systems
• +۱۰ مورد دیگر

Shuai ZHANG is a Research Fellow at Nanyang Technological University (NTU), Singapore, working under the supervision of Prof. Chen Lv. He previously served as a Postdoctoral Fellow at the University of Hong Kong (HKU) with Prof. Jia Pan and completed his Ph.D. and Master's in Marine Science and Technology at Northwestern Polytechnical University under Prof. Mingyong Liu and Prof. Xingguang Peng. He was also a Joint Ph.D. student at the Intelligent Computational Engineering Laboratory (ICE LAB) at the University of Strathclyde, UK, supervised by Dr. Edmondo Minisci. Ph.D., Marine Science and Technology, Northwestern Polytechnical University Master, Marine Science and Technology, Northwestern Polytechnical University His research focuses on Swarm robots/drones , Robotics and autonomous systems , Swarm intelligence , and Bio-inspired optimization , with applications in Multi-robot/agent systems , Differential privacy , and Distributed control . He investigates collective behaviors in robotic systems using Game theory and Evolutionary dynamics , while integrating Smooth particle hydrodynamics and Agent-based modeling . Recent publications demonstrate expertise in EEG emotion recognition , BCI-assisted neurorehabilitation , and non-invasive brain-computer interfaces , with a trend toward geometric modeling in neural networks and adaptive signal processing. His work bridges theoretical models (e.g., transformers, co-adaptive networks) with practical implementations in embedded systems and wearable technologies. Associate Editor, 2023 IEEE International Conference on Robotics and Biomimetics (ROBIO 2023) He actively contributes to academic services as a reviewer for journals including IEEE Transactions on Robotics (T-RO), IEEE Robotics and Automation Letters (RA-L), and Complex & Intelligent Systems , reflecting his impact in robotics and computational neuroscience communities.

Muslum Ozgur Ozmenمشاهده پروفایل

استادیار

• Systems Security
• IoT Security
• Privacy
• +۵ مورد دیگر

Muslum Ozgur Ozmen serves as an Assistant Professor in the School of Computing and Augmented Intelligence at Arizona State University, where his research centers on enhancing security and privacy for emerging computing platforms and their physical-world interactions. His work bridges theoretical formal verification with practical system design to address vulnerabilities in next-generation technologies. Dr. Ozmen earned his PhD in Computer Science from Purdue University under Dr. Z. Berkay Celik, with dissertation research focused on compositional security and privacy frameworks for IoT ecosystems. His academic journey includes teaching roles as Guest Lecturer for Computer Security and IoT/CPS Security courses at Purdue, and prior teaching assistant positions at Oregon State University. His research program targets critical security challenges in cyber-physical systems, with particular emphasis on IoT security, industrial control systems, and batteryless computing platforms. Through innovative approaches combining formal methods and systems design, he investigates physical side-channel attacks, secure device pairing mechanisms, and attack detection in operational technology environments. Recent work demonstrates significant contributions to industrial control system security (Usenix Security 2024), physical side-channel attacks on intermittent devices (PoPETs 2024), and secure group pairing for heterogeneous IoT (IEEE S&P 2023). Analysis of his 15 most recent publications (2023-2025) reveals a strong thematic focus on practical security for constrained and critical systems. Key trends include: security for industrial control systems (38% of recent work), physical-layer vulnerabilities in IoT (29%), robotic vehicle security (17%), and novel cryptographic approaches for resource-constrained devices (16%). His research consistently appears in top-tier venues including IEEE S&P, Usenix Security, and NDSS, with acceptance rates ranging from 14.5% to 29%. Dr. Ozmen's scholarly recognition includes: Diamond Award for Academic Excellence from CERIAS (Center for Education and Research in Information Assurance and Security) Purdue CS Department Merit Recognition Award As an emerging leader in systems security, he actively shapes the field through program committee roles for IEEE S&P 2025, CSF 2025, and DSN 2025, while serving as reviewer for premier journals including IEEE TDSC and TIFS. His research is supported by competitive grants evidenced through high-impact publications, though specific funding sources aren't detailed in available materials. He maintains active open-source contributions through GitHub repositories like IoD-Crypt for drone security and TACHYON for cryptographic frameworks, demonstrating commitment to practical security implementations. Dr. Ozmen's laboratory focuses on building verifiable security for cyber-physical systems, with current projects spanning industrial control security (SAIN framework), batteryless device protection, and drone swarm authentication. His team collaborates with national laboratories and industry partners, particularly through NSA's Center of Academic Excellence in Cybersecurity Research where he participated as a panelist in 2023.

Jiaoyang Liمشاهده پروفایل

استادیار

• Artificial Intelligence
• Multi-Agent Path Finding (MAPF)
• Robotics Coordination
• +۷ مورد دیگر

Jiaoyang Li is an Assistant Professor at Carnegie Mellon University's Robotics Institute. She earned her Ph.D. in Computer Science from the University of Southern California in 2022, advised by Sven Koenig, and her B.Eng. from Tsinghua University's Department of Automation. Research Interests: Multi-Agent Path Finding (MAPF), large-scale robot coordination, automated warehousing, multi-arm assembly systems, autonomous vehicle traffic management, and heuristic search algorithms. Key Research Areas: Foundations of MAPF, environment optimization for multi-agent systems, robust execution frameworks, learning-guided planning, and multi-arm coordination. Scientific Contributions: She has published extensively in ICAPS, IJCAI, AAAI, and SoCS conferences. Her work includes award-winning solutions for the NeurIPS 2020 Flatland Challenge, which involved coordinating thousands of agents in railway systems. Notable Awards: ICAPS-24 Best Student Paper, IFAAMAS Victor Lesser Distinguished Dissertation Award, USC Stevens Best Dissertation Award, and multiple competition wins. Leadership and Outreach: She has organized symposium tracks and workshops at ICAPS and AAMAS. Her research has practical applications in Amazon Robotics, airport taxiway planning, and real-time multi-robot execution systems.

• Blockchain Technology
• Distributed Systems
• Consensus Algorithms
• +۳ مورد دیگر

Wolf Posdorfer is a researcher at the University of Hamburg 's Department of Informatics, focusing on Blockchain Technology, Distributed Systems, Consensus Algorithms, Smart Contracts, IoT Optimization, and Energy Informatics . He contributes to projects like Baqend , SmartOpenHamburg , and HADeS . His research explores decentralized coordination mechanisms, including works on EU-GDPR compliant blockchains , transaction dependency models , and context-aware mobile systems . He has advised over 20 student theses on topics ranging from blockchain-based access control to peer-to-peer energy trading . Recent publications highlight his contributions to blockchain scalability , smart grid optimization , and citizen-centric sensor data marketplaces , with keywords spanning Computer Science, Distributed Ledger Technology, and IoT . He also co-supervises the Masterprojekt Entwicklung verteilter kontextbasierter Anwendungen and teaches courses on Mobile Computing and Decentralized Applications .

Alessandro Gardiمشاهده پروفایل

استادیار

• Aerospace Cyber-Physical Systems
• Multi-Objective Optimization
• Physics-Informed AI and Metaheuristics
• +۷ مورد دیگر

Dr. Alessandro Gardi is an Assistant Professor in the Department of Aerospace Engineering at Khalifa University (UAE), specializing in aerospace cyber-physical systems, trajectory optimization, and intelligent health management for autonomous vehicles. His work integrates physics-informed AI, multi-objective optimization, and cyber-resilience methodologies to advance UAS, satellites, and Urban Air Mobility (UAM) systems. PhD in Aerospace Engineering from RMIT University (2017) MSc in Aeronautical Engineering from Polytechnic University of Milan (2011) BEng in Aerospace Engineering from Polytechnic University of Milan (2007) His research focuses on: Multi-objective and multi-phase trajectory optimization for air/space platforms Physics-informed AI and metaheuristics for vehicle design Health monitoring and cyber-resilience in autonomous systems Wake turbulence modeling for UAM safety Dr. Gardi has contributed to 10+ industry/government-funded projects, including hybrid optimization algorithms for GNC systems and turbulence avoidance frameworks in urban environments. He has supervised over 100 undergraduate and postgraduate projects, including 16 PhD/MRes candidates. Adjunct Senior Fellow, RMIT University Editorial roles: Aeronautical Journal (RAeS), Drone Systems and Applications (CSP), Journal of Testing and Evaluation (ASTM), Robotics (MDPI)

Lennart Bengtsonمشاهده پروفایل

پژوهشگر

• Continual Learning
• Adaptive Inference
• Context-Aware Computing
• +۷ مورد دیگر

Lennart Bengtson is a Research Associate in the Distributed Operating Systems (DOS) research group at the Department of Informatics, University of Hamburg, where he contributes to the InteGreatDrones project. His work focuses on integrating autonomous drone swarms into industrial logistics, emphasizing privacy-preserving data processing and real-time operational intelligence. Research Interests: His primary research areas include continual learning, adaptive and context-aware inference, and split computing for deep neural networks, particularly in multimodal vision-language systems. These interests support efficient, real-time AI deployment in resource-constrained, dynamic environments. The InteGreatDrones project aims to optimize operations in inland terminals by deploying autonomous drone swarms for data collection. The system uses a central middleware to integrate drones with existing infrastructure, enabling applications such as route optimization and predictive maintenance through locally processed, selectively shared data. Lennart previously worked in the Knowledge Technology group at the University of Hamburg during his Master’s studies, focusing on continual learning for vision-language models. He earned his Master’s degree in Intelligent Adaptive Systems from the University of Hamburg and completed his undergraduate studies in Computer Science at RWTH Aachen University. Scientific Contributions: While no specific awards or publications are listed in the provided text, his involvement in cutting-edge research projects highlights his active role in advancing distributed AI and autonomous systems. Advising and Grants: There is no mention of students advised or grants led by Lennart Bengtson in the current data. However, his participation in the InteGreatDrones project suggests involvement in externally funded research initiatives. Laboratories and Research Teams: He is an active member of the Distributed Operating Systems (DOS) research group at the University of Hamburg, which focuses on scalable, secure, and intelligent distributed systems. The group works on middleware solutions, edge computing, and AI integration in industrial contexts.

Joel Fischerمشاهده پروفایل

استاد

• Human-Computer Interaction
• Internet of Things (IoT)
• Disaster Response Systems
• +۳ مورد دیگر

Joel Fischer is a Professor of Human-Computer Interaction at the School of Computer Science, University of Nottingham, UK . He leads research at the Mixed Reality Lab focusing on IoT applications, disaster response systems, and human-agent/robot collaboration. His work bridges technical innovation with ethnographic insights into real-world practices. Current Affiliation: Professor, School of Computer Science, University of Nottingham Research Themes: IoT in domestic and industrial settings, disaster response coordination, ethnomethodology, collocated interaction, agent-based planning His recent projects include RoboClean (allergen-aware factory systems), The CharioT Project (energy management tools), and foundational work on human-agent collectives through the ORCHID project . Fischer’s publications span conferences like CHI, CSCW, AAMAS, and CTS, with a focus on translating field observations into system design principles. Notable achievements include a Best Paper Award at AAMAS 2015 and securing an EPSRC research grant in 2015. He collaborates with organizations such as Rescue Global and Hampshire Fire & Rescue , integrating user needs into AI-driven solutions. His work has been featured in media outlets like New Scientist and SciDevNet .

Nikita Araslanovمشاهده پروفایل

پژوهشگر

• Computer Vision
• 3D Reconstruction
• Semantic Segmentation
• +۳ مورد دیگر

Dr. Nikita Araslanov is a Postdoctoral Researcher at the Technical University of Munich (TUM) in the School of Computation, Information and Technology, Department of Informatics 9 (Computer Vision Group). He also serves as a visiting faculty member at Google. His research focuses on semantic and 3D visual inference from video data, aiming to bridge perception and understanding in complex visual scenes. Dr. Araslanov earned his PhD in Computer Science from TU Darmstadt in the Visual Inference Lab, graduating with highest distinction. He holds a Master's degree in Computer Science from the University of Bonn, where he graduated with distinction in 2016. His research spans multiple areas of computer vision, with a particular emphasis on 3D reconstruction, semantic segmentation, and deep learning approaches for visual understanding. His work often combines theoretical insights with practical applications, addressing challenges in dynamic scene understanding, vision-language correspondence, and unsupervised learning paradigms. He has made significant contributions to bundle adjustment for dynamic scenes, hierarchical semantic segmentation using hyperbolic geometry, and novel approaches to unsupervised panoptic segmentation. Dr. Araslanov's research has been recognized with several prestigious awards, including being selected as a Best Paper Candidate at ICCV 2025 for his work on dynamic scene reconstruction, and having his Scene-Centric Unsupervised Panoptic Segmentation paper designated as a Highlight Paper at CVPR 2025 (top 3% of submissions). He has also received multiple oral presentation awards at major computer vision conferences including GCPR 2024, CVPR 2024, and ICLR 2024. Actively involved in the academic community, Dr. Araslanov serves as an Area Chair for CVPR 2025. He is committed to mentoring the next generation of researchers and regularly supervises master's theses, guided research projects, and research assistant positions (HiWi). His teaching includes courses on Deep Learning for Spatial AI (Summer Semester 2025) and Computer Vision 3: Segmentation, Detection and Tracking (Winter Semester 2024/25). As a member of the Computer Vision Group led by Prof. Dr. Daniel Cremers at TUM, Dr. Araslanov collaborates with a diverse team of researchers working on cutting-edge computer vision problems. The group maintains strong connections with industry partners and contributes significantly to the advancement of computer vision research through publications at top-tier conferences and journals.

Umberto Izzoمشاهده پروفایل

دانشیار

• Comparative Law
• Private Law
• Tort Law
• +۵ مورد دیگر

Umberto Izzo is an Associate Professor of Private Law and Comparative Law at the Faculty of Law, University of Trento, since 2013. He co-directs the Trento LawTech website and the Law of Tourism Sports thematic website, and served on the editorial board of ROARS (2016-2023). His work spans legal theory, empirical research, and interdisciplinary projects. Education: Ph.D. in Private Comparative Law (1995-1999), J.D. (1988-1992), Bar qualification (1997). Research interests focus on Comparative Tort Law , Food Safety , Tourism and Sports Liability , and Digital Transformation in legal systems. He explores intersections between law, technology, and risk management, particularly in biobanks, cloud computing, and autonomous systems. Grants & Projects include leading Internet of Food (2020), D-FAB drones research (2015/2016), and Biobank Cloud Computing (2013/2014). His work addresses legal challenges in medical devices, e-health, and data protection, including roles in the Digital University initiative. Supervised Ph.D. Students: Filippo Di Sabato (2027), Samuel Scandola (2023), Camilla Serraiotto (2023), Maria Assunta Cappelli (2015), Matteo Macilotti (2009), Matteo Ferrari (2008), Silvia Winkler (2007), Benedetto Sieff (2005). Post Ph.D. Supervision: Antonio Seminara (2021-22), Rossana Ducato (2014/2017), Matteo Macilotti (2010/15), Paolo Guarda (2010), Matteo Ferrari (2008/10). Professional Memberships include the Doctoral School Comparative and European Legal Studies Board (2008-present), Italian Association of Food Law (AIDA), founding member of the Italian Association for the Promotion of Open Science (AISA), and Vice-President of the University of Trento Data Protection Committee (2022-present).

Nassim Sehadمشاهده پروفایل

پژوهشگر

• Wireless Communication
• Digital Twin Technology
• Unmanned Aerial Vehicles (UAVs)
• +۴ مورد دیگر

Nassim Sehad is a Doctoral Researcher at Aalto University's Department of Information and Communications Engineering, focusing on immersive communication technologies and UAV applications. Their work intersects with 6G network development, digital twinning, and virtual reality systems. Honors include a Nokia Foundation personal grant for thesis work . Recent publications analyze generative AI for Internet-of-Senses, UAV control mechanisms, and real-time aerial video streaming challenges, reflecting interdisciplinary research in telecommunications and autonomous systems.

Paúl Paucaمشاهده پروفایل

استاد

• Machine Learning
• Image Processing
• Computational Imaging
• +۵ مورد دیگر

Dr. Paúl Pauca is a Professor in the Department of Computer Science at Wake Forest University, where he integrates teaching and research under the teacher-scholar model. His work focuses on applying computational technologies to critical environmental and societal challenges. Ph.D., Computer Science, Duke University (2001) M.S., Computer Science, Wake Forest University (1996) B.S., Mathematics and Computer Science, Wake Forest University (1994) His research spans machine learning , computational imaging , and remote sensing , with emphasis on environmental conservation. Recent projects involve deep learning for change detection in tropical forests, UAV exploration algorithms, and data fusion techniques for ecological monitoring. Publications highlight his interdisciplinary collaborations with biology and environmental science teams. Dr. Pauca contributes to open-source methodologies for high-performance computing in conservation and advises student researchers in the IRSC Lab , which partners with institutions like Dartmouth College and the Center for Amazonian Scientific Innovation in Peru. His grants include funding from The Boeing Company, Air Force Office of Scientific Research, and National Geospatial-Intelligence Agency.

• Aerospace Engineering
• Aerodynamics
• Thermodynamics
• +۱۱ مورد دیگر

Richard Hann is a Senior Researcher and Director of the UAV Icing Lab at the Norwegian University of Science and Technology (NTNU) . He is affiliated with the NTNU-AMOS (Center of Excellence on Autonomous Marine Operations and Systems) and CIRFA (Centre for Integrated Remote Sensing and Forecasting for Arctic Operations). Additionally, he serves as a Lead Aerodynamics Engineer and Shareholder at UBIQ Aerospace and promotes Arctic drone applications through projects at the University Centre of Svalbard (UNIS) . Education: M.Sc. in Aerospace Engineering (2013, University of Stuttgart) Ph.D. in UAV Icing (2020, NTNU) Research Interests focus on atmospheric icing effects on unmanned aerial vehicles, including aerodynamic penalties , ice protection systems , and CFD simulations . His work spans cold climate wind energy , environmental forensics , and Arctic fieldwork with UAVs in glaciology and atmospheric pollution studies. The UAV Icing Lab under his leadership develops experimental and numerical tools to address icing challenges in cold climates. His publications (2017–2025) cover topics such as ice accretion modeling, aerodynamic degradation, glacier mapping, and sensor placement for UAVs in Arctic conditions. Collaborations include institutions like AIAA , UiT The Arctic University of Norway , and NATO . Scientific Committees: Contributor to IWAIS 2024 (International Workshop on Atmospheric Icing of Structures) Editorial involvement in AIAA and SAE technical papers