جست‌وجوی استاد و پژوهشگر

• Wireless Communication
• Machine Learning
• Internet of Things (IoT)
• +۳ مورد دیگر

Aderemi Aaron-Anthony Atayero is an academic affiliated with the Department of Electrical Engineering and Information Engineering at Covenant University, Nigeria. His research focuses on telecommunications, wireless communication systems, IoT applications, and machine learning, with a strong emphasis on path loss modeling, signal processing, and smart city technologies. He has contributed to over 30 publications since 2005, collaborating extensively with researchers like Segun I. Popoola, Sanjay Misra, and Simon K. Hinga. His work spans theoretical and applied domains, including 5G mmWave models, botnet detection in IoT networks, and smart city infrastructure. Notable projects include the development of a low-intensity light imaging probe for medical applications and a cellular RSS dataset for roaming analysis. His research has practical implications for urban communication systems, healthcare technology, and cybersecurity.

• Artificial Intelligence
• Internet of Things
• Computer Vision
• +۴ مورد دیگر

Miloš Dobrojević serves as a Professor at Singidunum University's Faculty of Informatics and Computing in Belgrade, Serbia. His academic foundation includes doctoral, postgraduate, and bachelor studies at the University of Belgrade's Faculty of Mechanical Engineering. His research spans Artificial Intelligence , Internet of Things , and Computer Vision with emphasis on practical applications. Key focus areas include metaheuristic optimization of neural networks for tasks like crop yield prediction, medical diagnostics, and cybersecurity. Recent work demonstrates strong industry relevance in precision agriculture, drone detection systems, and sustainable homestead automation. Analysis of his 15 most recent publications reveals a consistent pattern of applying modified metaheuristics to enhance deep learning models across diverse domains. His work bridges theoretical AI advancements with real-world implementations in agriculture, healthcare, and energy systems. Scientific Contributions: Author of 3 textbooks including 'Veb informacioni sistemi' (2024) and 'Veb programiranje' (2021) Published 40+ journal/conference papers between 2003-2025 Active contributor to Springer book chapters on AI applications Dobrojević's work demonstrates strong practical orientation with projects in Serbian renewable energy transition, flood prevention systems, and municipal e-government solutions. His recent collaborations with researchers like N. Bacanin and M. Zivkovic show consistent output in high-impact journals. Current projects focus on generative AI for medical data and computer vision for agricultural optimization. His laboratory work centers on IoT-based monitoring systems for environmental applications, particularly water management in mountainous regions. Ongoing research explores drone detection networks and waste classification systems using advanced computer vision techniques.

Robert Davisمشاهده پروفایل

استاد

• Real-Time Embedded Systems
• Real-Time Scheduling
• Real-Time Networks (CAN)
• +۵ مورد دیگر

Roles & Affiliations: Dr. Robert Davis is a Reader in the Real-Time Systems Research Group at the University of York, UK. He has held an Inria International Chair (2014-2018) and currently works part-time. He has contributed to major initiatives like the Mixed Criticality Embedded Systems on Many-Core Platforms (MCC) project and the HI-CLASS project. University of York, Department of Computer Science Member of the IEEE Technical Community on Real-Time Systems (TCRTS) Education: Completed a DPhil (PhD) in Computer Science at the University of York in 1995. Research Interests: Focuses on Real-Time Systems, including scheduling analysis, mixed criticality systems, probabilistic real-time systems, and IDK classifiers. His work spans theoretical advancements and industrial applications, such as automotive networks and embedded systems. Key Contributions: Developed the Volcano CAN software library (used in automotive industries), Real-Time Architect RTOS, and co-founded Rapita Systems for WCET analysis tools. His research has led to three REF2014 Impact Case Studies. Awards & Recognition: Recipient of multiple best paper awards, including outstanding papers at RTNS and ECRTS conferences. His work has been recognized for influencing industry practices and safety-critical systems. Community Leadership: Organized events like RTSS, RTAS, and Dagstuhl seminars. Served as chair of the IEEE TCRTS and editor of the Real-Time Systems journal.

António Casimiroمشاهده پروفایل

دانشیار

• Dependable adaptive systems
• Middleware for distributed embedded real-time systems
• Cyber-Physical Systems
• +۴ مورد دیگر

António Casimiro is an Associate Professor at the Department of Informatics of the Faculty of Sciences, University of Lisbon. He holds a PhD in Computer Science (2003) from the same institution. His research focuses on dependable adaptive systems, middleware for distributed real-time applications, and cyber-physical systems. He leads the Cyber-Physical Systems research line at the LASIGE research unit and coordinates EU projects like ADMORPH and VEDLIoT, as well as the national AQUAMON project for water monitoring. Education: PhD in Computer Science, University of Lisbon (2003) Research Interests: Middleware for embedded real-time systems Fault-tolerant distributed systems IoT and environmental monitoring Cybersecurity in autonomous systems Key Projects: KARYON (FP7): Safe cooperative automotive/avionics systems VEDLIoT (H2020): Accelerated AIoT systems AQUAMON: Wireless sensor networks for water monitoring Awards: None explicitly listed, but active in editorial roles like Editor-in-Chief of the Ada User Journal. Teaching & Leadership: Coordinates the Master in Information Security program Former Vice-Director of LASIGE and member of Faculty Scientific Council Labs/Teams: LASIGE research unit, Navigators group, involvement in GULLIVER testbed for vehicular systems.

Günter Alceمشاهده پروفایل

مدرس ارشد

• Internet of Things (IoT)
• Human-Computer Interaction
• Augmented Reality
• +۵ مورد دیگر

Günter Alce is a Senior Lecturer at Lund University's Department of Ergonomics and Aerosol Technology, part of the Lund Institute of Technology (LTH). His research focuses on human-technology interaction in smart environments, including IoT systems, augmented/virtual reality (AR/VR), and user interface design. Key projects include the 6G-FOX initiative (6G network research) and MAGICIAN (immersive learning via VR). He contributes to UN Sustainable Development Goals through work on embedded systems and health technology. Alce leads the LTH Profile Area: Engineering Health, emphasizing cross-disciplinary collaboration. His recent studies explore VR applications in workplace safety, telepresence systems for regulatory oversight, and user interface optimization for fitness tracking. He actively supervises master’s theses in AR/VR domains and participates in the Centre for Healthy Indoor Environment (CHIE). Research outputs span 24 peer-reviewed works, including conference proceedings on IoT interaction models, drone detection systems, and VR-based phobia treatment. His work bridges technical innovation with ergonomic and social factors, addressing both system design and user experience challenges.

• Health Informatics
• Social Media Analytics
• Public Health Surveillance
• +۴ مورد دیگر

Xiao Liu is an Assistant Professor in the Department of Information Systems at Arizona State University (ASU), Tempe campus. She holds a Ph.D. in Management Information Systems from the Eller College of Management at the University of Arizona. Her research focuses on leveraging data science and predictive analytics in healthcare, education, and fintech, with a particular emphasis on health informatics, social media analytics, and machine learning applications. Liu's work bridges computational methods with real-world healthcare challenges, analyzing social media data to understand medication nonadherence, opioid treatment barriers, and adverse drug events. Education Ph.D. in Management Information Systems, University of Arizona Research Interests Health Informatics Social Media Analytics Public Health Surveillance Machine Learning Natural Language Processing Grants NIH Grant: $984k (ASU Share: $262K) for 'Leveraging YouTube Video Analytics for Patient Education on Health Management: A Digital Therapy Tool for Clinicians' (2021–2024). Labs/Teams Not explicitly mentioned, but her research aligns with ASU's healthcare data science initiatives.

• Performance Analysis
• Network Systems
• Industrial Real-Time Communications
• +۴ مورد دیگر

Federico Tramarin is an Associate Professor at the Enzo Ferrari Engineering Department of the University of Modena and Reggio Emilia , Italy. He holds a Dr. Eng. in Electronic Engineering and a Ph.D. in Information Engineering from the University of Padova (2008 and 2012, respectively). Previously, he served as an Assistant Professor at the University of Padova's Department of Management and Engineering and held a post-doctoral position at the National Research Council of Italy (CNR) from 2013 to 2018. His research focuses on performance analysis and measurements of network systems , with emphasis on industrial real-time wired/wireless communications, cyber-physical systems, real-time embedded systems, Time Sensitive Networks (TSN), and IoT. He actively contributes to standards and protocols for industrial communication through memberships in IEEE committees (e.g., IEEE Industrial Electronics Society and Instrumentation and Measurement Society). Prof. Tramarin has authored/co-authored over 60 peer-reviewed publications in top conferences and journals, emphasizing real-time wireless LANs, industrial IoT, and networked control systems . His work spans topics like 5G-enabled PMU systems, TSN integration with SDN, and reliability in industrial wireless networks. He serves on editorial and program committees of major international journals and conferences, furthering the advancement of networked measurement systems. He is a member of the IEEE and the Italian Group of Electrical and Electronic Measurements (GMEE), reflecting his commitment to metrology and industrial automation. His interdisciplinary research bridges theoretical foundations with practical applications in smart manufacturing, automotive systems, and healthcare monitoring.

• Formal Methods
• Cyber-Physical Systems
• Probabilistic Programming
• +۴ مورد دیگر

Ezio Bartocci is a Full Professor in Formal Methods for Cyber-Physical Systems Engineering at TU Wien's Faculty of Computer Science. He leads the Trustworthy Cyber-Physical Systems (TrustCPS) Group within the Cyber-Physical System Research Unit. His research focuses on formal verification, probabilistic systems, and runtime monitoring, with applications in autonomous systems, safety-critical software, and embedded systems. Roles & Affiliations: Full Professor, TU Wien (100% research focus) Principal Investigator in projects funded by EU, WWTF, FFG, and industry partners Chair of the Curriculum Commission for Computer Engineering Editor-in-Chief of the Formal Methods in Outer Space series Research Interests: Formal methods for CPS: verification, synthesis, and runtime monitoring Probabilistic programming and loop analysis Temporal logic specifications and mining Automated tools for safety-critical systems (e.g., Polar, MoonLight) Applications in healthcare, robotics, and autonomous vehicles Key Projects: ProbInG (2020–2025): Analyzing probabilistic loops ARTIST (2021–2026): AI and robotics safety EdgeAI (2022–2025): Optimizing embedded processing TAIGER (2023–2027): Trustworthy AI and CPS Grants & Funding: €10M+ secured from EU Horizon 2020, WWTF, FFG, and industry partners like TTTech Auto AG. Academic Leadership: Teaches courses on logical methods, CPS engineering, and scientific research at TU Wien. Supervises PhD students in formal methods and CPS domains. Tools Developed: Polar (probabilistic loop analyzer), MoonLight (spatio-temporal monitoring), and FIM (fault injection tool).

• System-on-Chip (SoC) Design
• FPGA-Based High-Level Synthesis
• Real-Time Embedded Systems
• +۵ مورد دیگر

Timo Hämäläinen is a Professor of Computer Engineering at Tampere University, leading the Unit of Computing Sciences within the Faculty of Information Technology and Communication Sciences. He is a core member of the System-on-Chip research group and the Computer Engineering Team, actively contributing to the System-on-Chip Hub initiative. His research focuses on System-on-Chip (SoC) design methodologies, FPGA-based high-level synthesis, real-time embedded systems, and open-source hardware-software co-design frameworks like RISC-V and HEVC encoding. He has pioneered work on agile SoC development processes and validation techniques for large-scale hardware systems. Key research areas include: High-level synthesis (HLS) optimization for FPGAs Real-time processor architectures and context-switching latency reduction Formal verification of IP-XACT-compliant SoC designs Resilient RISC-V MPSoC implementations Hardware-accelerated algorithms for signal processing and networking His recent publications (2023-2025) emphasize agile SoC development frameworks, hardware-software co-design for real-time systems, and validation methodologies for large-scale embedded systems. He has contributed to open-source projects like Kvazaar HEVC encoder and the Kactus2 IP-XACT toolchain. Academic advising includes students such as Santéri Mäki-Äijö (formal verification), Arto Oinonen (RISC-V tooling), and Sakari Lahti (processor modeling). His work integrates academic research with industrial collaboration through frameworks like the Fault-slip-Through quality assessment methodology.

Tuna Balkanمشاهده پروفایل

استاد

• Control Systems
• Robotics
• System Dynamics
• +۵ مورد دیگر

Prof. Tuna Balkan is a Professor in the Mechanical Engineering Department at Middle East Technical University (METU), Ankara, Turkey. He holds a B.Sc. (1979), M.Sc. (1983), and Ph.D. (1988) from METU. His research focuses on control systems, robotics, fluid power control, and dynamic modeling. He leads the Control Systems Laboratory at METU and teaches courses such as Control Systems (ME 304), Fluid Power Control (ME 516), and Mechanical Engineering Systems Laboratory (ME 410). His work spans hydraulic actuator design, platform stabilization, and industrial robotic applications like spray painting and arc welding. Research interests include real-time control, Kalman filtering, and energy-efficient hydraulic systems. He has supervised numerous theses, including studies on hydraulic load simulators, energy-efficient actuators, and vibration-based energy harvesting. His publications cover topics like instability analysis in hydraulic systems, friction compensation in motion platforms, and microelectromechanical systems (MEMS) for energy harvesting. Prof. Balkan’s lab, Control Systems Lab (Room G-130), develops advanced control algorithms and experimental setups. His contributions to automotive safety, agricultural machinery design, and robotic spray painting have been widely recognized. He has collaborated on projects involving durability test rigs, unmanned aerial vehicles, and sensor integration for industrial applications.

Margaret Lechمشاهده پروفایل

استاد

• Machine Learning
• Signal Processing
• Speech Processing
• +۳ مورد دیگر

Professor Margaret Lech holds a position as Discipline Leader in the Department of Electrical & Electronic Engineering at RMIT University's School of Engineering. She has been at RMIT since 1998, progressing from a Research Fellow to her current role as Professor. Her expertise spans machine learning, signal processing, speech and image processing, and biomedical applications. Education: MSc in Physics from the University of Maria Curie-Sklodowska (Poland), PhD in Electrical Engineering from the University of Melbourne. Research highlights include groundbreaking emotion detection from speech signals, clinical depression analysis, and conversational trust modeling. She has co-authored over 160 papers and holds an international patent for her work on emotion detection. Awards: Telstra Innovation Challenge 2010, Vice-Chancellor's Research Supervision Excellence Award (2013), RMIT Award for Excellence in Graduate Research (2019). Grants: VPAC, ARC Linkage, DSI, AOARD, DSTG, and current co-investigator on Office of National Intelligence and ARC Discovery grants. Her research focuses on applications of AI and machine learning in healthcare, cybersecurity (e.g., Smart Grids), robotics (multi-agent systems), and fine art analysis. She has supervised over 30 PhD students and pioneered techniques in real-time speech emotion recognition and sleep stage classification. Labs/Teams: Leads interdisciplinary teams working on neuromorphic sensing, neural network systems, and computational inference of social signals. Active in collaborative projects involving industry and international partners.

• Applied Artificial Intelligence (AI)
• Computer Vision
• Disaster Management
• +۴ مورد دیگر

Dr. Umair Iqbal is a Researcher in the School of Engineering at the University of Newcastle, specializing in Applied Artificial Intelligence (AI) with a focus on Computer Vision and Edge-Computing solutions for real-world challenges like disaster management and water resource optimization. He holds a PhD from the University of Wollongong and is an NVIDIA DLI Ambassador, delivering workshops on deep learning and AIoT technologies. His research emphasizes AI-driven video analytics for infrastructure monitoring (e.g., culvert blockage detection), public safety (e.g., violence detection in transit systems), and environmental applications (e.g., flood risk mitigation). His work combines interdisciplinary approaches, leveraging tools like TensorFlow, NVIDIA frameworks, and edge devices (Jetson platforms). Key contributions include developing an AIoT solution for pipeline protection, a real-time edge-computing system for public transport safety, and bibliometric reviews on drones and computer vision in flood management. Dr. Iqbal has secured $114,814 in grants, including a 2023 project on floodborne debris identification and a 2025 initiative for kerbside waste management. He actively supervises graduate students and leads projects like StopBlock (culvert blockage detection) and iMOVE (transport safety analytics). Research interests span AIoT frameworks, generative AI, and geotechnical applications. His publications (23+ journal articles, 3 conference papers, 2 book chapters) address hydraulic infrastructure resilience, machine learning in civil engineering, and disaster response technologies. He collaborates with industry partners like Remondis and fosters innovation through workshops and course coordination at undergraduate/postgraduate levels.

Jeremy Singerمشاهده پروفایل

دانشیار

• Systems Software
• Garbage Collection
• Compilers
• +۴ مورد دیگر

Jeremy Singer is a Reader in Programming Language Implementation at the School of Computing Science, University of Glasgow. He specializes in systems software, compilers, garbage collection, and secure runtime environments. His research focuses on advancing memory management techniques, many-core parallelism, and edge computing. Singer holds a PhD from the University of Cambridge (2006) in Static Program Analysis based on Virtual Register Renaming. He is a Senior Member of the ACM and a Fellow of the BCS. His academic roles include supervising PhD students in areas such as quantum memory management, federated graph neural networks, and secure memory systems. He has led multiple EPSRC-funded projects, including M4Secure (2023-2026), Capable VMs (2020-2024), and FRuIT (2017-2019). He teaches courses like COMPSCI1016 (Computational Thinking) and COMPSCI4021 (Functional Programming in Haskell). Singer’s research spans compiler design, runtime systems, and security. Notable contributions include work on SSA-based compiler techniques, Raspberry Pi cluster systems, and secure microPython implementations. He has authored over 80 publications and co-developed MOOCs on functional programming and data science. His awards include Fellow of the BCS and Senior ACM Membership. Current research interests include secure memory management, compiler optimizations for heterogeneous architectures, and edge computing security.

Saddek Bensalemمشاهده پروفایل

استاد

• Formal Methods
• Verification
• Embedded Systems
• +۷ مورد دیگر

Saddek Bensalem is a Professor at Université Grenoble Alpes (UGA), affiliated with the Laboratoire Verimag within the Grenoble Institute of Technology. His research focuses on rigorous system design, formal methods for verification, and the integration of learning-enabled components into safety-critical systems. He leads projects like FETLAS (Engineering Trustworthy Learning-enabled Autonomous Systems) and has contributed to frameworks such as BIP for component-based system design. Research Interests: Formal verification of real-time systems, model-based design, cyber-physical systems, autonomous robotics, and security in IoT. His work emphasizes scalable verification techniques and correctness-by-construction approaches. Recent Projects: FOCETA (H2020): Foundations for continuous engineering of trustworthy learning-enabled systems. BRAIN-IoT: Framework for smart IoT-CPS integration and security. CPS4EU: Strengthening European capabilities in cyber-physical systems. Labs & Teams: Laboratoire Verimag, leading the Rigorous System Design team (2008-2020) and currently advancing autonomous systems research. Active in collaborations with institutions like NASA/JPL and SRI International.

Björn Annighöferمشاهده پروفایل

استاد

• Avionics Systems
• Self-Adaptive Systems
• Cybersecurity
• +۵ مورد دیگر

Björn Annighöfer is a Professor at the Institute of Aviation Systems (ILS) at the University of Stuttgart, where he serves as Managing Director. His work focuses on complex, digital, and safety-critical avionics systems, including self-adaptive platforms, cybersecurity, and AI-supported aerospace systems. Research interests include: Self-adaptive avionics platforms Model-based cybersecurity frameworks Integrated Modular Avionics (IMA) development Virtualization and middleware for safety-critical systems AI applications in aerospace Automated development and certification processes Recent publications highlight advancements in PLUG-AND-FLY avionics, security assessment using large language models, and domain-specific modeling tools. He leads a team of ~25 scientists at ILS, which operates modern labs, flight simulators, and research aircraft for testing.