جست‌وجوی استاد و پژوهشگر

Vedran Dunjkoمشاهده پروفایل

استاد

• Quantum Computing
• Quantum Machine Learning
• Quantum Artificial Intelligence
• +۷ مورد دیگر

Professor Vedran Dunjko is a faculty member at the Leiden Institute of Advanced Computer Science (LIACS), Leiden University, with affiliations to the Leiden Institute of Physics (LION). He leads the Applied Quantum Algorithms group and co-founded the Quantum@LIACS initiative, focusing on the intersection of quantum computing, machine learning, and artificial intelligence. His research interests include quantum machine learning, quantum-enhanced reinforcement learning, quantum heuristics, and the application of AI to quantum computing challenges. Dunjko's work bridges theoretical foundations with experimental implementations on near-term quantum devices, exploring both quantum advantages in learning and the use of classical AI for quantum system design. The recent publications show a strong trend toward proving quantum advantages in learning tasks, optimization, and topological data analysis, with publications in Nature , Nature Communications , and NeurIPS . Key themes include quantum policy gradients, quantum TDA, and reinforcement learning for quantum circuit optimization. ERC Consolidator Grant (2024) PNAS Cozzarelli Prize (2018) Editor’s Suggestion in Physical Review Letters (2014, 2018) Featured in Physics (American Physical Society) (2014, 2018) Dunjko advises several PhD candidates and postdocs, including Rahul Bandyopadhyay, Sofiene Jerbi, and Lea Trenkwalder. He has received competitive grants, most notably the ERC Consolidator Grant in 2024. His group fosters international collaborations with institutions across Europe and industry partners. The Applied Quantum Algorithms group and the Quantum@LIACS team combine theoretical investigations with practical implementations on quantum hardware, focusing on scalable quantum algorithms and AI-driven quantum discovery.

• Neuromorphic Computing
• Memristor-Based Architectures
• Energy-Efficient AI Hardware
• +۷ مورد دیگر

Said Hamdioui serves as a full Professor in the Department of Computer Engineering within the Faculty of Electrical Engineering, Mathematics and Computer Science at Delft University of Technology. His research focuses on cutting-edge hardware architectures for neuromorphic computing and energy-efficient AI acceleration, with particular emphasis on memristor-based systems, emerging memory technologies, and fault-tolerant designs for edge applications. His research interests span Neuromorphic Computing , Memristor-Based Architectures , and Energy-Efficient AI Hardware , addressing critical challenges in hardware security, computation-in-memory, and reliable edge AI deployment. Recent work demonstrates significant advancements in RRAM/FeFET testing methodologies, spiking neural network implementations, and spin wave computing alternatives to traditional CMOS. His publications reveal strong trends toward real-world deployment of brain-inspired hardware with practical constraints like power efficiency, testability, and security. Award highlights include: DATE'20 Best Paper Award DFT'21 Outstanding Student Paper ETS 2021 Best Paper Award LATS 2018 & 2022 Best Paper Awards Professor Hamdioui actively contributes to the research community through editorial roles at IEEE Transactions on VLSI Systems , IEEE Design & Test , and Journal of Electronic Testing from 2017-2018. His leadership in multi-partner projects like CONVOLVE and NEUROKIT2E demonstrates strong industry-academia collaboration for edge AI solutions. Current work shows increasing focus on practical deployment challenges including in-field fault monitoring, security vulnerabilities in neuromorphic systems, and realistic brain simulation frameworks.

• RF and Microwave Engineering
• Power Amplifiers
• Digital Transmitters
• +۴ مورد دیگر

Leonardus Cornelis Nicolaas de Vreede is a Professor at Delft University of Technology in the Faculty of Electrical Engineering, Mathematics and Computer Science. With over 237 research publications and extensive conference activities, he is a leading researcher in RF and microwave engineering with specialization in power amplifiers, digital transmitters, and mm-wave circuits for wireless communications applications. Dr. de Vreede's research focuses on the intersection of circuit design and signal processing for next-generation wireless systems: Advanced Power Amplifier Architectures including Doherty and Out-phasing techniques Energy-Efficient Digital Transmitters with high linearity and power efficiency mm-Wave Circuit Design for 5G/6G applications Machine Learning Applications for Digital Predistortion CMOS RF Integrated Circuit Implementation Wideband Signal Processing Techniques His recent publications demonstrate a clear research trajectory toward integrating machine learning with traditional RF circuit design to solve the efficiency-linearity tradeoff in wireless transmitters. This work is particularly relevant for current and future wireless infrastructure requiring high spectral efficiency across wide bandwidths while maintaining energy efficiency. Dr. de Vreede has received significant recognition for his contributions to the field: EuMC Microwave Prize (2024) for groundbreaking work on wideband Doherty amplifiers Recognition for innovative characterization techniques for high-power RF transistors (2015) As an active researcher and educator, Dr. de Vreede has supervised 16 students and regularly participates in major international conferences including serving on program committees for the IEEE MTT-S International Microwave Symposium. His work bridges theoretical advances with practical implementations for wireless infrastructure applications, with numerous patents and industry collaborations evident from his research portfolio.

Farhad Merchantمشاهده پروفایل

استادیار

• Hardware Security
• Neuromorphic Computing
• Algorithm-Architecture Co-design
• +۳ مورد دیگر

Dr. Farhad Merchant is an Assistant Professor of Innovative Computer Architecture at the Bernoulli Institute, University of Groningen, since July 2024. Previously, he served as a Lecturer (Assistant Professor) at Newcastle University (2022–2024) and held research roles at Bosch Research, NTU, and RWTH Aachen University. His research focuses on emerging technology-based computing and hardware-oriented security, including neuromorphic architectures, in-memory computing, and secure hardware design. Education: PhD in Electronics Engineering from the Indian Institute of Science, Bangalore, with a DAAD-funded visit to RWTH Aachen University. He also holds industry experience from Bosch Research. Research Interests : - Hardware Security - Neuromorphic Computing - Algorithm-Architecture Co-design - Reconfigurable Computing - Computer Arithmetic Projects : - Coordinator for the REACT project (2025–2029): Focuses on self-aware neuromorphic architectures. - Principal Investigator for Privacy-Preserving Computer Architectures (CogniGron, 2025–2029). - Completed BioNanoLock project (DFG-funded, focusing on bio-nanoelectronic security). Awards : - Best Paper Awards at ISQED 2022, NEWCAS 2023, and VLSI-DAT 2024. - Minerva Fellowship (Technion, Israel), HiPEAC Technology Transfer Award (2019). He co-founded the SeHAS workshop (since 2019) and serves on editorial and program committees for major conferences like DAC, ISLPED, and VLSI-SoC.

• Computational Neuroscience
• Machine Learning
• Neural Networks
• +۵ مورد دیگر

Prof. Sander Bohte is a part-time full professor of Computational Neuroscience at the University of Amsterdam (Swammerdam Institute of Life Sciences) and an honorary full professor of Bio-inspired Neural Networks at the University of Groningen. He serves as a Scientific Staff Member and Group Leader in the Machine Learning department at CWI, Amsterdam. His work bridges computational neuroscience and machine learning with a focus on continuous-time information processing. Key research interests include: Spiking Neural Networks with predictive coding and multi-compartment models Biologically Plausible Learning in recurrent and deep architectures Working Memory modeling via reinforcement learning Neuromorphic Computing for real-time systems and GPU acceleration His recent publications highlight trends in neural adaptation , predictive coding , and SNN hardware-software co-design . Awards include the Veni Innovational Research Grant (2004) and ERCIM grant (2013) . He actively supervises MSc theses and leads grants like the NWO KIC project 'Selfhealing Neuromorphic Systems' (2024).

• Wireless Communication
• 6G Networks
• 5G Networks
• +۶ مورد دیگر

A. Asadi is an Assistant Professor at the Faculty of Electrical Engineering, Mathematics and Computer Science at TU Delft. He leads the Wireless Communication and Sensing (WISE) Lab within the Embedded Systems Group, focusing on the integration of wireless communication and sensing systems for Beyond-5G and 6G networks. His research leverages machine learning to develop practical solutions for next-generation wireless networks, with strong industrial collaborations from companies such as Nokia, NEC, and National Instruments. Research Themes : Wireless Sensing, 6G Networks, Physical Layer Security, Reconfigurable Intelligent Surfaces (RIS), mmWave Communication Key Collaborations : Industry partnerships with Nokia, National Instruments, and NEC Recent research outputs highlight his work on Reconfigurable Intelligent Surfaces (RIS) for 6G systems, including liquid crystal-based designs for fast beam switching and temperature compensation. His publications emphasize practical implementations in mmWave communication, security protocols, and experimental validation. Scientific Awards : Athene Young Investigator Prize (2017) Educational Fellowship (2025) Asadi contributes to the academic community through committee roles at major conferences like IEEE INFOCOM , IEEE ICNP , and ACM CoNEXT , and his work on D2D communication has been cited as an ESI highly cited paper.

Geoffrey Nelissenمشاهده پروفایل

استادیار

• Real-Time Systems
• Schedulability Analysis
• Multicore Platforms
• +۳ مورد دیگر

Geoffrey Nelissen is an Assistant Professor in the Department of Mathematics and Computer Science at Eindhoven University of Technology. He holds additional roles as a Research Scientist and Investigador Auxiliar at INESC TEC (Portugal), contributing to interdisciplinary research in real-time systems. His work focuses on schedulability analysis, parallel task execution, and real-time communication protocols, with applications in embedded systems and multicore architectures. Research Interests: Real-Time Scheduling Response Time Analysis Multi-core and Parallel Systems Time-Sensitive Networking (TSN) Formal Verification Recent work emphasizes schedule abstraction frameworks, memory contention analysis, and deterministic communication protocols. His research has received recognition through multiple best paper awards including ICESS 2021 and RTAS 2022. He actively contributes to conferences like RTSS and ECRTS while teaching courses on Real-Time Systems and Operating Systems. Collaborations span European institutions with focus on embedded systems, autonomous driving, and safety-critical applications. Current projects explore holistic approaches to WCRT analysis and resilient real-time communication architectures.

Freek J. Beekmanمشاهده پروفایل

استاد

• Biomedical Imaging
• Nuclear Imaging
• Image Reconstruction Algorithms
• +۱۲ مورد دیگر

Prof. Freek J. Beekman is a Full Professor and head of the Biomedical Imaging section within the Department of Radiation Science & Technology at Delft University of Technology (TU Delft), Faculty of Applied Sciences. He is a leading figure in biomedical imaging, with extensive contributions to nuclear imaging technologies, including SPECT, PET, and CT. His research spans detector development, image reconstruction algorithms, hybrid photonic imaging, and the application of artificial intelligence in medical imaging. Research Interests: His work focuses on advancing imaging modalities through innovations in hardware (e.g., multi-pinhole collimators) and software (e.g., deep learning for attenuation correction). He has pioneered ultra-high-resolution imaging systems, particularly for preclinical and clinical SPECT, and has developed integrated platforms like U-SPECT-BioFluo. His recent research explores glymphatic delivery of nanoparticles, infection imaging, and AI-driven reconstruction techniques, reflecting a strong translational focus. Publication Trends: His most recent publications (2021–2023) emphasize deep learning in SPECT, multi-isotope imaging, high-resolution ex vivo systems, and applications in neuroimaging and oncology. The articles demonstrate a consistent focus on improving image quality, resolution, and clinical utility through physics-informed and AI-enhanced methods. Scientific Awards: NWO Physics Valorization Prize Innovation of the Year Award by the World Molecular Imaging Society (2015, 2018) Edward Hoffman Memorial Award (2017) Bruce Hasegawa Memorial Award (2021) FOM Valorization Award (2013) TU Delft Entrepreneurial Award (2010) Advising and Grants: While specific student names are not listed, his leadership in large collaborative projects and supervision of numerous publications suggests active mentoring. He has secured significant funding through national and international grants, evidenced by his invention of over 20 patent families and successful technology transfer. His founding and leadership of MILabs BV (sold to Rigaku) highlights his impact on commercialization and industry-academia collaboration. Labs and Teams: He leads the Biomedical Imaging research group at TU Delft, which develops cutting-edge imaging systems such as VECTor (SPECT-PET) and EXIRAD-HE. His teams have produced technologies used globally in academic and pharmaceutical research, contributing to tracer development and therapeutic innovation.

• Artificial Intelligence
• Cultural AI
• Digital Platform Governance
• +۴ مورد دیگر

Fabian Ferrari is an Assistant Professor in Cultural AI at Utrecht University, working in the Department of Media and Culture Studies within the Humanities faculty. He is affiliated with the Centre for Digital Humanities and is a member of the focus area Governing the Digital Society . Previously, he served as a Postdoctoral Researcher (2022-2024) in the same focus area and was a Visiting Scholar (2021-2022) at the Milieux Institute for Arts, Culture and Technology in Montréal. Dr. Ferrari's research focuses on the intersection of artificial intelligence, digital platforms, and society. His work examines AI governance, algorithmic power, digital labor, and the infrastructural geographies of AI systems. He investigates how public investments in AI infrastructure can reconcile competitiveness with public value creation, particularly through his upcoming NWO-funded Veni project Conditional Computing: Reimagining the Governance of Public AI Infrastructure , which begins in January 2026. His publication record demonstrates significant scholarly impact, with articles in top journals including Nature Machine Intelligence , Cultural Studies , New Media & Society , Big Data & Society , and Competition & Change . He has also co-edited the open-access book Digital Work in the Planetary Market published by MIT Press. Ferrari's work is frequently cited and has influenced policy discussions, as evidenced by multiple policy citations across his publications. NWO Veni grant for research on public AI infrastructure Dr. Ferrari's research collaborations span multiple institutions and international teams. He has frequently co-authored with scholars including Mark Graham, José van Dijck, and Anne Helmond. His work bridges technical, social, and policy dimensions of AI systems, with particular attention to labor implications and governance frameworks. He is actively engaged in both academic and public discourse on AI's societal implications, contributing to progressive policy visions for generative AI.

• Software Engineering
• Technical Debt Management
• Software Architecture
• +۳ مورد دیگر

Paris Avgeriou is a Professor of Software Engineering at the University of Groningen, affiliated with the Faculty of Science and Engineering and the Bernoulli Institute. He leads the Software Engineering and Architecture research group and serves as Editor-in-Chief of the Journal of Systems and Software . His expertise spans technical debt management, software architecture, self-adaptive systems, and embedded systems design. Avgeriou holds an office at Nijenborgh 9, Groningen, and actively advises academic institutions and funding bodies globally. Research Interests: Avgeriou's work focuses on advancing software architecture principles, technical debt lifecycle management, and the integration of AI in software engineering. His research emphasizes practical solutions for improving software quality, maintainability, and system dependability, particularly in embedded and self-adaptive contexts. Recent Contributions: Recent studies include frameworks for benefit-cost-risk decision-making in self-adaptive systems, automated technical debt management using ML, and tools for tracing architecture-related debt. He collaborates internationally, contributing to standards like the Copenhagen Manifesto for human-centered AI in software engineering. Grants & Awards: While no specific awards are listed, his editorial role and frequent conference contributions reflect recognition in the field. He chairs conference tracks and oversees workshops, fostering early-career researchers and artifact evaluation. Labs & Teams: His group is part of the Bernoulli Institute, working on platforms like SDK4ED for embedded systems and tools such as DebtViz for technical debt monitoring. The team explores intersections between systems engineering and software architecture in complex systems-of-systems.

Kevin A. Williamsمشاهده پروفایل

استاد

• Photonic Integrated Circuits
• Semiconductor Lasers
• Optical Communications
• +۲ مورد دیگر

Kevin Williams is Full Professor and Chair of Photonic Integration at Eindhoven University of Technology. His research focuses on scaling photonic circuits for energy-efficient optical components in communications and sensing. Key research themes include: 1) Generic integration methodologies, 2) Heterogeneous integration of photonic components with silicon electronics, and 3) Integrated nano-photonics using InP membranes. His work enables high-speed optical transceivers and novel computing paradigms. Honors include the 2010 NWO Vici Award for ultrafast optical processor chip research and the Royal Society University Fellowship. Current projects focus on InP-based photonic integration platforms for applications in AI acceleration and optical communications.

Sofie Haesaertمشاهده پروفایل

استادیار

• Cyber-Physical Systems
• Control Theory
• Formal Verification
• +۳ مورد دیگر

Sofie Haesaert is an Assistant Professor in the Control Systems group at the Department of Electrical Engineering, Eindhoven University of Technology. Her work focuses on formal verification and control synthesis methods for cyber-physical systems, particularly through stochastic simulation relations and temporal logic specifications. Education: BSc (cum laude) and MSc (cum laude) in Mechanical Engineering and Systems & Control from Delft University of Technology; PhD from Eindhoven University of Technology (2017) Experience: Postdoctoral researcher at Caltech (2017-2018), then returned to TU/e as Assistant Professor Her research interests include: Cyber-physical systems verification Stochastic control methods Temporal logic specification Markov decision processes Formal methods in control engineering Model abstractions and simulation relations Recent publications show strong focus on: Stochastic temporal logic control Robust and risk-aware control Multi-agent system verification Formal synthesis via simulation relations AI integration in control systems Software tools for formal control Scientific achievements: Veni Grant recipient (2020) Co-developer of the SySCoRe toolset for stochastic control synthesis Contributor to formal verification benchmarks through ARCH-COMP reports She contributes to education through courses on: Control principles for engineered systems Control challenges in autonomous racing Supervisory control of cyber-physical systems Haesaert collaborates across disciplines including computer science, applied mathematics, and robotics, with over 750 citations and significant contributions to formal control theory for stochastic systems. Her work bridges theoretical developments with practical applications in autonomous systems and complex control architectures.

Anuj Pathaniaمشاهده پروفایل

استادیار

• Low Power Design
• Sustainable Systems
• Electronic Design Automation
• +۴ مورد دیگر

Anuj Pathania serves as an Assistant Professor in the Parallel Computing Systems (PCS) group within the Informatics Institute at the University of Amsterdam's Faculty of Science. His research pioneers sustainable computing systems operating under severe power, thermal, and reliability constraints, with significant contributions to energy-efficient hardware design and embedded systems. Education: PhD in Computer Science (2018), Karlsruhe Institute of Technology MSc in Computer Science (2012), National University of Singapore B.Tech in Computer Science (2009), Maharaja Agrasen Institute of Technology Pathania's research centers on low-power design and sustainable systems for constrained environments, with particular expertise in thermal management of 3D-stacked architectures and energy-efficient machine learning inference . His work bridges electronic design automation with real-world reliability challenges, developing novel power budgeting techniques like T-TSP that incorporate transient temperature effects ignored by conventional methods. Current projects include EU-funded initiatives on energy labeling for digital services, addressing ecological impacts through technological, behavioral, and legal frameworks. His publication trajectory reveals a strategic evolution toward zero-waste computing , with recent work (2023-2025) focusing on hardware-software co-design for edge AI, energy modeling across computing continua, and parameter-efficient neural adaptation. Key themes include thermal-aware scheduling for S-NUCA many-cores, cooperative processor utilization in heterogeneous systems, and sustainability metrics for digital services. Scientific Recognition: Best Paper Award Nomination at IEEE Computer Society Annual Symposium on VLSI 2023 for 3D-TTP power budgeting technique Pathania actively mentors 4 PhD students (Ehsan Aghapour, Saeedeh Baneshi, Sudam Wasala, Yixian Shen) and has successfully supervised 5 Master's theses (including Cum Laude defenses by Joris op ten Berg and Jurre Wolff). His research is supported by major grants including Energy Labels for Ecologically Sustainable Digital Services (2023-2024) and Towards Zero-Waste Computing (2021-2025), developing simulation frameworks like HotSniper and CoMeT for thermal analysis. The PCS group maintains strong industry collaborations with ARM and NVIDIA, particularly through tools like ARM-CO-UP for heterogeneous processor utilization.

• Model-Based Design
• Design Automation
• Optimization
• +۴ مورد دیگر

Marc C.W. Geilen is an Associate Professor at the Electronic Systems group , Eindhoven University of Technology. He leads the Model-Based Design Lab and contributes to the CompSOC Lab and High Tech Systems Center . His work focuses on model-based design methods, design automation, and optimization for real-time and embedded systems. Research Keywords: Cyber-Physical Systems, Real-Time Systems, Embedded Systems, Performance Analysis, Design Automation Key Collaborations: EU ECSEL TRANSACT project, SAM-FMS project, Arrowhead Tools initiative His recent publications address weakly-hard timing constraints in server-based systems, hybrid performance modeling for cyber-physical systems, and neural network optimization for communication. Article trends span Real-Time Scheduling , Trustworthy Modeling , Neural Network Efficiency , and Resource Allocation in distributed environments. Scientific Awards : Partial-Order Reduction for Performance Analysis (2018) Teaching activities include courses in Computational Modeling , Embedded Signal Processing , and Discrete Mathematics . He collaborates across projects like TRANSACT, SAM-FMS, and Arrowhead Tools, focusing on flexible manufacturing and cloud-to-edge transitions.

Nicola Calabrettaمشاهده پروفایل

استاد

• Optical Communication Systems
• Photonics
• Telecommunications Engineering
• +۶ مورد دیگر

Nicola Calabretta is a Full Professor in Electro-Optical Communication Systems and Senior Research Fellow at Eindhoven University of Technology (TU/e). His work focuses on smart optical networks, high-speed electronics, FPGA implementations for scheduling algorithms, and photonic integrated circuits. He holds a PhD from TU/e (2004) and previously conducted research at DTU Fotonik and the Sant'Anna School of Advanced Studies. His expertise spans optical signal processing, multi-level modulation formats, and applications in data center and metro networks. Key research areas include optical switching architectures (e.g., SOA-based switches), WDM systems, and low-latency interconnect networks. He has led projects like ADAPTOR (resource optimization), SmartTWO (future telecom technologies), and 5G-MOBIX (cross-border mobility). His courses include 'Optical Fibre Communication Technology' and 'Optical Interconnection Networks.' Collaborations involve institutions globally, with recent work emphasizing photonic integration for neural networks, ultra-fast switching, and edge computing. His contributions align with UN SDGs through sustainable telecom infrastructure advancements.