جستجوی استاد راهنمای دانشگاهی

Marco Vassenaمشاهده پروفایل

استادیار

• Security
• Programming Languages
• Cyber Security
• +۳ مورد دیگر

Marco Vassena is an Assistant Professor at the Department of Information and Computing Sciences, Utrecht University, within the Faculty of Science. He focuses on developing principled methods for building secure systems, bridging Security and Programming Languages research communities. His work applies type systems, compilers, program analysis, and verification to ensure reliable security guarantees in software systems. PhD in Computer Science from Chalmers University of Technology Visiting Assistant Professor at Stanford Postdoctoral Researcher at CISPA Helmholtz Center for Information Security Member of the CISPA-Stanford Center for Cybersecurity His research spans language-based security (constant-time programming, memory safety, information flow control), software defenses against Spectre and side-channel attacks, and WebAssembly sandboxing. He leads projects like MSWasm and Blade, targeting microarchitectural attack mitigation through formal verification and compiler design. Scientific recognition includes the Veni Grant (2023). Current projects explore speculative execution security, dynamic information flow control, and secure WebAssembly implementations.

• Embedded Systems
• Cyber-Physical Systems
• Performance Engineering
• +۳ مورد دیگر

Jeroen Voeten is a Full Professor in the Electronic Systems group of the Department of Electrical Engineering at Eindhoven University of Technology (TU/e). He also holds a position as a Research Fellow at the Embedded Systems Institute in Eindhoven and is a Senior Scientist and Scientific Advisor to TNO-ESI since 2017. Academic Background: MSc in Mathematics and Computing Science (1991, TU/e) PhD in Electrical Engineering (1997, TU/e) Voeten's research focuses on formal methodologies for hardware/software system specification, design, and implementation. His work spans computer architectures, embedded systems, performance modeling, and cyber-physical systems. He is currently leading the Carm 2G project with ASML to enhance model-based engineering environments for wafer scanner control systems. His recent publications emphasize advancements in global scheduling, fault-tolerant real-time systems, and hybrid performance modeling. These studies address critical areas like latency reduction, schedulability improvements, and data age analysis in multi-rate task chains. Scientific Awards: Best Paper Award, Forum on Specification and Design Languages (FDL 2005) Best Paper Award, Property-Preserving Synthesis for Unified Control and Data-Oriented Models (2005) Voeten has contributed to 87 conference reports, 13 academic reports, 11 book chapters, and 11 journal articles, reflecting his extensive involvement in both academic and industrial research. Labs and Collaborations: He is affiliated with the Model-Based Design Lab and the High Tech Systems Center at TU/e, collaborating with institutions like TNO-ESI and industry leaders such ASML. His work aligns with the UN Sustainable Development Goals (SDGs) through applications in embedded systems and high-tech manufacturing.

• Artificial Intelligence
• Systems Engineering
• Cyber-Physical Production Systems
• +۵ مورد دیگر

Dr. Saber Darmoul is an Associate Professor specializing in Systems Engineering and Multidisciplinary Design. His research bridges artificial intelligence with industrial applications, focusing on cyber-physical production systems, operational resilience, and smart transportation. He actively explores knowledge representation, reinforcement learning, and agent-based modeling to address complex system challenges. Key Research Interests: Operational resilience, AI in manufacturing, multi-agent systems, smart mobility Technical Expertise: Ontology modeling, simulation platforms, immune-inspired control architectures His recent publications (2025-2019) demonstrate a consistent focus on integrating artificial immune systems into control architectures for transportation and manufacturing. Notable trends include: Development of knowledge-based systems for dynamic reconfiguration Application of multi-criteria decision frameworks in production environments Advancing predictive maintenance strategies through distributed systems Exploring 6G system-of-systems engineering While no explicit awards or student advisement information appears in available records, his 15 most recent publications reflect sustained academic productivity and evolving focus from foundational control systems (2017-2019) to advanced applications in Industry 4.0 (2020-2025).

• Artificial Intelligence
• Edge AI
• Sensors
• +۷ مورد دیگر

Amirreza Yousefzadeh is an Assistant Professor specializing in computer architecture design for embedded systems. His research focuses on hardware acceleration for artificial intelligence, particularly in energy-efficient neuromorphic computing and edge AI applications. Research Interests Neuromorphic computing architectures Event-driven AI hardware Sparsity exploitation in neural networks Embedded vision systems Digital circuit design for AI Research Trends Recent work (2024-2025) demonstrates expertise in spiking neural networks (SNNs), activation sparsity, and hardware-software co-design for neuromorphic processors. Key areas include object detection, energy efficiency optimization, and digital implementations of synaptic delays. Technical Contributions Developed SENMap for multi-objective data-flow mapping Created SENSIM simulator for multi-core neuromorphic systems Investigated 3D stacking for memory-dominated architectures Explored temporal sparsity in event-based processing

Erco Arganteمشاهده پروفایل

مدرس

• Responsible Artificial Intelligence
• Explainable AI
• Reinforcement Learning
• +۵ مورد دیگر

Erco Argante serves as a Lecturer in Computer Science and Researcher at the Applied Responsible Artificial Intelligence research group of Avans University of Applied Sciences in Breda, employed continuously since 2009 after prior roles as technical coordinator and software architect at Ericsson Telecommunications. His academic background includes: Physics studies at Radboud University Nijmegen PhD in Computer Science with doctoral research on parallel processing of CERN's Large Hadron Collider event data Erco specializes in building comprehensive AI domain knowledge with technical focus on reinforcement learning and transformers. He champions responsible AI through explainability and interpretability frameworks, emphasizing that technical understanding must enable informed stakeholder decisions alongside regulatory measures. His work bridges software architecture expertise with AI system development. As core member of the Applied Responsible Artificial Intelligence lectorate, he drives initiatives like the Art-IE project while integrating personal passion for biodiversity conservation into applied research contexts.