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Bill ChuView profile

Professor

• Cybersecurity
• Cyber Threat Intelligence
• AI in Cybersecurity
• +2 more

Bill Chu is a Professor and Managing Director of CyberDNA at the University of North Carolina at Charlotte's College of Computing and Informatics. His research focuses on cybersecurity automation, cyber threat intelligence, application security, and AI-driven cybersecurity solutions. He has contributed to numerous publications on threat detection, vulnerability analysis, and secure software development practices. Chu's work emphasizes practical applications of cybersecurity, including static analysis tools, interactive code annotation for vulnerability detection, and educational tools for secure programming. His research spans collaborations with institutions and industry to bridge gaps in cybersecurity education and practice. Notable contributions include developing frameworks for extracting actionable threat intelligence from social media, automated unit testing for XSS vulnerabilities, and leveraging large language models for vulnerability detection. Chu actively participates in workshops and conferences on cybersecurity and software engineering, contributing to advancements in both theory and application.

• Computer Science
• Software Engineering
• Formal Methods
• +6 more

Thomas Henzinger is a Professor at the Institute of Science and Technology Austria (IST Austria) since 2009, serving as its President from 2009 to 2022. He holds honorary doctorates from Fourier University and Masaryk University. His research focuses on formal methods for improving software reliability in concurrent and embedded systems, with contributions to quantitative verification, quantum computing, and algorithmic fairness. He leads the Henzinger Group , which addresses challenges in software correctness, safety-critical systems, and AI ethics. Education: PhD from Stanford University (1991), followed by postdoctoral work at Université Joseph Fourier (1991). Research Interests: Concurrent and embedded systems, formal methods, quantum algorithms, fairness in AI, and runtime verification. His team develops mathematical foundations and tools to ensure software robustness in complex systems. Recent Trends in Publications: Focus on advancing formal verification techniques for neural networks, quantum computing, and ethical AI. Key contributions include fairness shields for decision systems and middleware for third-party monitoring (VAMOS). Awards: Royal Society Fellow (2024), US National Academy of Sciences Member (2020), Wittgenstein Award (2012), and numerous test-of-time awards. Advising & Grants: Advised over 20 PhD students. Secured ERC Advanced Grants (VAMOS, QUAREM) and FWF grants (Wittgenstein Award). Labs/Teams: Leads the Henzinger Group , collaborating on projects like SPyCoDe (semantic security) and VAMOS (third-party monitoring middleware).

• Control Systems
• Real-Time Systems
• Cloud Computing
• +3 more

Anton Cervin is a Senior Lecturer (on Leave of Absence) at the Department of Automatic Control, Lund University. He is affiliated with the LTH Profile Area: AI and Digitalization. His roles include Director of First and Second Cycle Studies, Deputy Head of the Department (2019–2022), and Director of the China Profile at LTH (2008–2012). Research focuses on real-time systems, control over cloud platforms, event-based control, and cyber-physical systems. Key projects include the Swedish Research Council-funded 'Event-Based Control of Stochastic Systems' and WASP-supported 'Event-Based Information Fusion for Self-Adaptive Cloud'. Developed software tools: TrueTime (real-time simulator), JitterTime, Jitterbug, and TinyRealTime. Recognized with multiple Best Paper Awards at ECRTS, RTNS, and RTCSA conferences. Supervised over 5 PhD students in real-time control and embedded systems. Teaching includes advanced courses on automatic control, systems engineering, and real-time systems. His work aligns with UN SDG 9 (Industry, Innovation, and Infrastructure) through contributions to smart infrastructure and cloud-based control systems.

Luca SchenatoView profile

Professor

• Control Systems
• Distributed Optimization
• Federated Learning
• +5 more

Luca Schenato is a Full Professor in the Department of Information Engineering at the University of Padova. His research focuses on distributed control systems, federated learning, multi-agent optimization, and wireless communication protocols. He has extensive experience in developing algorithms for cyber-physical systems, with applications in robotics, smart grids, and sensor networks. Education and Appointments section lists his academic journey but lacks explicit details. He has held positions related to control systems and information engineering throughout his career. Research interests include: Design of resilient wireless control systems Federated learning architectures for edge computing Distributed optimization under communication constraints Robotics and multi-agent coordination Smart energy management systems His recent publications (2021–2025) demonstrate a strong focus on: Over-the-air federated learning innovations High-speed wireless control systems (e.g., 1 kHz Wi-Fi control) Resilient distributed optimization algorithms Human-centric building automation He has contributed to numerous projects related to networked control systems and has organized conferences like ECC13. His work emphasizes bridging theoretical control principles with practical industrial applications.

Elena TroubitsynaView profile

Professor

• Autonomous Systems
• Software Engineering
• Formal Verification
• +3 more

Elena Troubitsyna is a Professor of Computer Science with specialization in Software Engineering at KTH Royal Institute of Technology. Her research focuses on developing dependable, autonomous systems that ensure safety and reliability, particularly in complex environments like self-driving cars and drones. She employs rigorous mathematical modeling and verification techniques to address system complexity and real-time adaptability challenges. Her work emphasizes the co-engineering of safety and security in cyber-physical systems, integrating formal methods such as Event-B modeling with AI-driven solutions. Key research areas include cybersecurity for embedded systems, formal analysis of safety-security interactions, and resilient multi-agent systems. Elena has contributed to advancing methods for autonomous system navigation, fault tolerance, and privacy-preserving microservices architectures. Elena has organized international workshops like SENSEI (Safety-Security Interaction) and published extensively on topics such as model-driven engineering, formal verification of critical systems, and optimizing scheduling for distributed computing. Her research bridges theoretical foundations with practical applications, aiming to enhance societal trust in autonomous technologies.

• Distributed/Parallel Computing
• Information Visualization
• Fault-Tolerant Communication Mechanisms
• +4 more

Philippas Tsigas is a Professor at the Department of Computer Science and Engineering at Chalmers University of Technology. He leads the Distributed Computing and Systems Research Group and has held roles as co-leader of research initiatives such as the PEPPHER project. His research spans distributed/parallel computing, information visualization, and fault-tolerant communication mechanisms. He has supervised numerous PhD students, including Yi Zhang, Håkan Sundell, and Farnaz Moradi. Research interests include lock-free data structures, multicore algorithms, secure network services, and visualization tools like Lydian and DataMeadow. Notable awards include Best Paper Awards at IPDPS 2003 and SNS 2012. His work has been published in top venues like IEEE Transactions on Parallel and Distributed Systems and ACM Journal of Experimental Algorithmics. Awards highlight contributions to lock-free algorithms and network modeling. Students have contributed to projects like NBmalloc (memory reclamation) and GPU Quicksort. Collaborations with institutions like SSF and VR have supported his research. Tsigas is also involved in teaching distributed systems and mentoring early-career researchers.

Andrew McPhersonView profile

Professor

• Music Computing
• New Interfaces for Musical Expression
• Digital Signal Processing
• +3 more

Andrew McPherson is a Professor of Musical Interaction at Queen Mary University of London, affiliated with the School of Electronic Engineering and Computer Science and the Centre for Multimodal AI. He leads the Augmented Instruments Laboratory, a research team focused on music technology and interdisciplinary collaboration. His work bridges electrical engineering, composition, and human-computer interaction, emphasizing the creation of new tools for musicians through hardware/software interfaces and expressive performance modeling. McPherson's research interests include augmented instruments, digital signal processing, and the design of intuitive musical interfaces. He has pioneered projects like the Bela embedded platform and the Magnetic Resonator Piano, emphasizing practical applications in traditional and experimental music venues. Collaborations with artists and industry inform his approach, ensuring research outputs are artistically relevant and accessible. Education & Expertise: Trained in electrical engineering and composition, McPherson combines technical proficiency with artistic sensibility. His lab’s projects, such as the TouchKeys and hackable instruments, highlight his focus on democratizing music technology. Grants & Awards: He holds a Royal Academy of Engineering Senior Research Fellowship (2021–2026) and an ERC Consolidator Grant (2023–2027). He co-leads the UKRI Centre for Doctoral Training in Artificial Intelligence and Music, fostering future researchers in AI-driven music innovation. Labs/Teams: The Augmented Instruments Lab collaborates across disciplines, with dual affiliation at Queen Mary and Imperial College London’s Dyson School of Design Engineering. The lab’s work spans from foundational research to industry partnerships, including spinout company Augmented Instruments Ltd, which supports maker communities and industry consultancy.

Sebastian MaierView profile

Researcher

• Distributed Systems
• Operating Systems
• Many-Core Architectures
• +3 more

Sebastian Maier is a Researcher at the Department of Computer Science 4 (Distributed Systems and Operating Systems) at Friedrich-Alexander-University Erlangen-Nuremberg, part of the Faculty of Engineering. His work focuses on invasive computing, many-core architectures, and distributed systems. He has contributed to projects like the iRTSS (Invasive Run-Time Support System) and the OctoPOS kernel, emphasizing system software for resource arbitration and latency-aware systems. Maier has taught courses such as System-level Programming in C and Operating Systems exercises from 2013 to 2019. His research interests include hardware-software co-design, embedded systems security, and runtime systems for future architectures. He has advised students on thesis topics like distributed TCP/IP stacks and asynchronous communication interfaces in many-core systems. His recent work explores dynamic hardware-managed queues (DySHARQ) and resource arbitration mechanisms for tile-based architectures. These efforts aim to optimize parallel processing and real-time performance in embedded systems. Maier has also collaborated on latency-aware operating systems (LAOS) and security in embedded systems (SESES). Key Projects: iRTSS, AAM (Asynchronous Abstract Machines), SHARQ, LAOS Lab/Teams: Part of the Invasive Computing SFB/TRR 89 project (Project C1) His publications span conferences like ROME, ROSS, and HiPEAC, addressing challenges in many-core kernel design, scalability, and hardware-accelerated systems. Current research trends focus on adapting system software to heterogeneous and dynamic many-core environments.

Martin HoffmannView profile

Researcher

• Embedded Systems
• Real-Time Systems
• Fault Tolerance
• +3 more

Dr. Martin Hoffmann is a former research staff member at the Department of Computer Science 4 (Distributed Systems and Operating Systems) at Friedrich-Alexander-University Erlangen-Nuremberg (FAU). He now works at Brose Fahrzeugteile in Bamberg. His research focuses on dependability, fault tolerance, and real-time systems, with emphasis on embedded systems and safety-critical applications. He taught courses such as Echtzeitsysteme (Real-Time Systems) and Verlässliche Echtzeitsysteme (Reliable Real-Time Systems) across multiple semesters. His work includes projects like dOSEK (a dependability-oriented RTOS), DanceOS (fault-tolerant OS design), and CoRed (software-based redundancy for mixed-criticality systems). He also contributed to the I4Copter interdisciplinary quadrocopter project. His research interests span fault-injection frameworks, static kernel analysis, and soft-error mitigation. Notable contributions include Fail* (a versatile fault-injection tool) and dOSEK (RTOS for automotive safety). He has advised multiple students on topics like fault-tolerant garbage collectors and modular OS service frameworks. No scientific awards are explicitly mentioned in the provided text. His work emphasizes interdisciplinary collaboration, with projects bridging embedded systems, robotics, and safety-critical applications.

• Communication Security
• Embedded Systems Security
• Design of Embedded Systems
• +4 more

Alberto Ferrante is a Lecturer and Researcher at the Faculty of Informatics of the Università della Svizzera italiana (USI), affiliated with the IDSIA (Dalle Molle Institute for Artificial Intelligence) USI/SUPSI. His work bridges cybersecurity, embedded systems, and AI applications, particularly in IoT and pest control. He holds a PhD from Università degli Studi di Milano (2006) and an MSc from Politecnico di Milano (2002). Research Interests: Ferrante focuses on Secure communication protocols and embedded systems security Malware detection and resource-optimized hardware solutions Machine learning applications for IoT, including agricultural pest monitoring and healthcare diagnostics Cyber-physical systems design and security-enhanced embedded systems His publications emphasize practical implementations, such as AI-driven UAVs for pest control and low-power drone systems for environmental monitoring. He actively contributes to tech transfer projects with industry partners and participates in major conferences like ICC and Globecom as a TPC member. He teaches the Master’s course Edge Computing in the IoT and collaborates on hardware-software co-design for security-critical systems. His work often integrates real-world constraints like energy efficiency and computational resource limitations. Key contributions include frameworks for dynamic security adaptation in wireless sensor networks and hardware-accelerated security for embedded systems.

Joseph SifakisView profile

Emeritus Professor

• Embedded Systems
• Formal Verification
• Component-Based Systems
• +3 more

Joseph Sifakis is an Emeritus Senior CNRS Researcher at the Verimag laboratory, University of Grenoble Alpes, and former Full Professor at the École Polytechnique Fédérale de Lausanne (EPFL) (2011-2016). He is renowned for his foundational contributions to formal verification, particularly in model checking and component-based system design. Sifakis is the founder of Verimag, a leading laboratory in embedded systems research, and the developer of the BIP framework for rigorous system design. His research focuses on system design methodologies, formal methods for embedded and cyber-physical systems, and the integration of correctness-by-construction principles. He pioneered the use of the Lustre language and SCADE tool for safety-critical systems, widely adopted in avionics and space applications. Key contributions include the BIP modeling language, the IF and Kronos verification tools, and advancements in system architecture modeling. His work bridges theoretical computer science with industrial applications, emphasizing safety, reliability, and scalability in complex systems. Awarded the Turing Award (2007) for model checking, Sifakis has held leadership roles in European research initiatives like the ARTIST Networks of Excellence. He served as President of the Greek Council for Research and Technology (2014-2016) and is a member of prestigious academies including the French Academy of Sciences and the National Academy of Engineering.

• Performance evaluation of networks
• Wireless networks
• Internet of Things (IoT)
• +12 more

Katia Jaffres-Runser is a full Professor at Institut National Polytechnique de Toulouse (Toulouse INP) , affiliated with the ENSEEIHT engineering school and the IRIT laboratory , where she leads the RMESS team. She holds a PhD from INSA Lyon and completed a prestigious Marie Curie postdoctoral fellowship at Stevens Institute of Technology and INSA Lyon. PhD : Institut des Sciences Appliquées de Lyon (INSA Lyon), 2005 M.Sc. : INSA Lyon, 2002 Diplôme d’Ingénieur en Télécommunications : INSA Lyon, 2002 Her research centers on performance evaluation and optimization of networks , particularly in wireless sensor networks, IoT, embedded systems, and complex networks. She applies advanced techniques like Google Matrix analysis, game theory, and deep reinforcement learning to improve network reliability, synchronization, and efficiency. Her work spans theoretical modeling and practical implementations in avionics, automotive, and industrial systems. Her recent publications highlight a strong trend in time-sensitive networking (TSN) , network synchronization , AI-driven optimization , and complex network analysis using Wikipedia and trade data. She has led major projects like MACACO, GOIA, and the Maison du Quantique Occitanie, focusing on real-time, reliable, and intelligent networking solutions. Scientific Awards: Best Paper Award on Propagation, IEE International Conference on Antennas and Propagation, 2003 STIC Innovation Prize, 2005 Marie Curie Outgoing International Fellowship, 2007–2010 Prime d'Excellence Scientifique (2013–2016) PEDR (2017–2021) RIPEC C3 (2022–2025) She has advised PhD students and contributed to national and international scientific service, including committee memberships in CoNRS , HCERES , and ACM N²Women . She has served on award juries and grant review panels. Her leadership extends to being Vice-President for Education at Toulouse INP (2021–2024) and Team Leader of RMESS at IRIT (since 2024) . She is actively involved in research labs and collaborative teams such as: RMESS Team , IRIT Laboratory – leading research on network modeling and embedded systems MACACO Project – international collaboration on adaptive communication networks GOIA and APPLIGOOGLE Projects – applying Google Matrix to AI and complex networks IRT EDEN – evaluating determinism in embedded networking

Peter DruschelView profile

Professor

• Distributed Systems
• Operating Systems
• Peer-to-Peer Systems
• +7 more

Peter Druschel is the founding director of the Max Planck Institute for Software Systems (MPI-SWS) and leads the Distributed Systems Group. He holds adjunct professorships at Saarland University and the University of Maryland, reflecting his strong academic affiliations in computer science. He has previously served as a Professor of Computer Science at Rice University and has held visiting positions at MIT, Microsoft Research Cambridge, and LIP6. Education: Ph.D. in Computer Science, University of Arizona, 1994 His research centers on building secure, compliant, and privacy-preserving distributed and mobile systems. Key interests include accountable systems, peer-to-peer networks, operating systems, and network security. He has led foundational work in systems like Pastry, Scribe, and Glacier, and currently focuses on privacy compliance in data processing through projects like Thoth and iPic. His work is supported by major grants from the ERC, Max Planck Society, DFG, BMBF, and Google. The recent publications highlight a consistent trend in secure and privacy-aware systems, with a focus on policy enforcement, isolation mechanisms, anonymity, and mobile security. These works span top venues such as USENIX Security, OSDI, MobiSys, and SIGCOMM, reflecting sustained impact in systems and security communities. Scientific Awards: NSF CAREER Award (1995) Alfred P. Sloan Fellowship (2000) SIGOPS Mark Weiser Award (2008) Microsoft Research Outstanding Collaborator Award (2016) EuroSys Lifetime Achievement Award (2017) Druschel has advised numerous PhD and master’s students and postdoctoral researchers at MPI-SWS. He has co-directed major collaborative programs including the Cornell-Maryland-Max Planck Pre-doctoral School and the Maryland Max Planck Ph.D. Program. His leadership extends to professional service, having chaired SOSP, OSDI, NSDI, and EuroSys, and served on editorial boards of CACM, TOCS, and Royal Society Open Science. He is a member of Academia Europaea and the German Academy of Sciences Leopoldina. Labs and Teams: Distributed Systems Group, MPI-SWS imPACT ERC Synergy Project Collaborators include Bobby Bhattacharjee, Deepak Garg, Miguel Castro, Ion Stoica, and others

• Signal Processing
• Image Processing
• Smart Environments
• +6 more

Manuel Reis is an Associate Professor with Agregação at the University of Trás-os-Montes e Alto Douro (UTAD), Portugal, in the Electrical Engineering Department. His research focuses on signal/image processing, smart environment systems, and multimedia education technologies. He is affiliated with the Institute of Electronics and Telematics Engineering of Aveiro (IEETA) and collaborates with Brazil's IFPA-Santarém in computing education research. Education: Bachelor's in Electrical Engineering (University of Trás-os-Montes e Alto Douro, 1991) Master's in Electronics and Telecommunications (University of Aveiro, 1996) PhD in Electrical Engineering (University of Aveiro, 2001) Research Interests: Signal & Image Processing Cybersecurity for IoT and Smart Environments Education Technology (e-learning, multimedia tools) 5G and Edge Computing Applications Artificial Intelligence in Agriculture and Healthcare Recent articles highlight his work on cybersecurity in connected vehicles, federated learning for IoT security, and IoT-based systems for drowsiness detection. He has contributed to projects involving smart city infrastructure, sustainable waste management, and low-cost biomedical devices. His educational research explores e-learning frameworks, student engagement metrics, and innovative teaching methodologies in engineering education. Lab/Affiliations: Institute of Electronics and Telematics Engineering of Aveiro (IEETA) Multidisciplinary Research Group IFPA-Santarém-Brazil (Computing in Education)

Zhiyi HuangView profile

Associate Professor

• Theoretical Computer Science
• Algorithmic Game Theory
• Online Algorithms
• +3 more

Zhiyi Huang is an Associate Professor of Computer Science at the University of Hong Kong, leading the Computer Science Division within the School of Computing and Data Science. He holds a PhD from the University of Pennsylvania (2013) and completed a postdoctoral fellowship at Stanford University (2013–2014). His research focuses on Theoretical Computer Science, Algorithmic Game Theory, Online Algorithms, and Differential Privacy, with notable contributions to Machine Learning and Computer Networks. Education: PhD in Computer and Information Science, University of Pennsylvania (2013) Postdoctoral Researcher, Stanford University (2013–2014) Bachelor's Degree from the Yao Class at Tsinghua University (2008) Research interests span foundational areas including algorithmic game theory, online optimization, and privacy-preserving mechanisms. He has pioneered work on revenue maximization in single-parameter settings and developed novel frameworks for analyzing price of anarchy in game theory. Key Awards: Early Career Award (Research Grant Council of Hong Kong, 2014) Best Paper Award at ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2015) Morris and Dorothy Rubinoff Dissertation Award (2013) Simons Graduate Fellowship in Theoretical Computer Science (2012–2013) Recent grants include studies on algorithmic foundations of Bayesian mechanism design (HK$675,647), online primal dual techniques (HK$496,028), and privacy-preserving mechanisms (HK$931,737). His work bridges theoretical advancements with practical applications in healthcare, autonomous systems, and cybersecurity. Notable Projects: Medical predictive systems for acute cardiopulmonary events AI-driven maritime navigation using AIS data Secure federated learning frameworks with blockchain