جست‌وجوی استاد و پژوهشگر

• Optical Transmission Systems
• Space Division Multiplexing
• Quantum Cryptography
• +۵ مورد دیگر

Chigo Okonkwo is Full Professor and Chair of Secured Ultra High Capacity Transmission at the Department of Electrical Engineering , Eindhoven University of Technology. He leads the high-capacity optical transmission laboratory at the Institute for Photonics Integration and contributes to the Center for Quantum Materials and Technology Eindhoven (QT/e) . Academic Qualifications: MSc in Telecommunications and Information Systems, University of Essex (2002) PhD in Optical Signal Processing, University of Essex (2010) Research Interests: Professor Okonkwo focuses on: Maximizing capacity of single-mode fiber systems through advanced-coded modulation and Probabilistic/Geometrically shaped signals Developing Space Division Multiplexing (SDM) systems for Petabit/s transmission using multi-mode/multi-core fibers Quantum secure communications and cryptographic protocol development Optical vector network analyzer (OVNA) technology for SDM fiber characterization Free-space optical link deployment in urban environments Low-complexity digital signal processing algorithms Recent Publications Trends: His 15 most recent articles (2023-2025) demonstrate active research in: Quantum-classical network integration Extreme capacity fiber transmission (Petabit/s systems) Machine learning for optical diagnostics SDM fiber measurement technologies Hybrid QKD-PQC security frameworks Free-space optical urban communication Scientific Awards: Asia Communications and Photonics Conference (ACP) 2018 Best Paper Award European Conference on Optical Communications (ECOC) 2018 Student Paper Award Optica Student Paper Awards (2022) Corning Outstanding Student Paper Competition Finalist (2025) Advisory & Collaborations: Advisor to 8+ researchers including Menno van den Hout, Vincent van Vliet, and Thomas Bradley Technical Program Committee Member, European Conference on Optical Communications (ECOC) since 2014 Sub Committee Chair for Digital Signal Processing track at ECOC 2018 General Chair for OSA Advanced Photonics Congress on Signal Processing for Photonics Collaborates with EU projects (HOMTech, PhotonDelta) and industrial partners Co-founder and Chief Technology Officer of CUbIQ Technologies Laboratory & Infrastructure: Maintains the world-class High Capacity Optical Transmission Lab at TU/e, featuring: Advanced SDM fiber testing equipment Quantum communication research infrastructure Free-space optical link experimental setups Multi-core fiber amplification systems Coherent transmission testbeds Machine learning-enabled diagnostic tools

Alex Alvaradoمشاهده پروفایل

استاد

• Optical Communications
• Wireless Communications
• Information Theory
• +۳ مورد دیگر

Alex Alvarado is a Full Professor in the Signal Processing Systems department at Eindhoven University of Technology (TU/e), leading the Information and Communication Theory Lab (ICT Lab). He is also affiliated with TU/e's Center for Wireless Technology in Eindhoven. His academic career includes roles as a Senior Research Associate at University College London (2014–2016), Marie Curie Intra-European Fellow (2012–2014), and Newton International Fellow (2011–2012) at the University of Cambridge. Alvarado is a Senior Member of the IEEE and has held editorial and committee positions in major conferences like OFC and ECOC. Alvarado holds an Electronics Engineer degree (2003) and MSc (2005) from Universidad Técnica Federico Santa María, Chile, followed by a Licentiate of Engineering (2008) and PhD (2011) from Chalmers University of Technology, Sweden. His research focuses on high-speed secure data transmission in optical and wireless systems, emphasizing energy-efficient algorithms and theoretical limits of telecommunication systems. Key areas include communication theory, information theory, optical fiber systems, and nonlinear interference mitigation. His recent articles explore advanced modulation formats, machine learning applications for channel estimation and decoding, and innovations in free-space optics and MIMO systems. This work contributes to UN Sustainable Development Goals related to affordable and clean energy, industry innovation, and responsible consumption through energy-efficient communication solutions. Scientific Awards: ERC Starting Grant (2018) NWO VIDI Grant (2016) 2015 Journal of Lightwave Technology Best Paper Award 2015 IEEE Exemplary Reviewer Award 2018 and 2023 Asia Communications and Photonics Conference Best Paper Awards 2019 Optoelectronics and Communications Conference Best Paper Award Alvarado's advising contributions include supervising 12 research works. His grants include NWO VIDI and ERC Starting funding. He leads projects like NESTOR (Next-gen optical networks) and LaiQa (Quantum Key Distribution). His lab, the ICT Lab, drives theoretical and applied research in communication systems.

Erik Bekkersمشاهده پروفایل

دانشیار

• Geometric Machine Learning
• Deep Learning
• Medical Image Analysis
• +۴ مورد دیگر

Erik Bekkers is an Associate Professor at the University of Amsterdam's Informatics Institute, leading research in the Machine Learning Lab (AMLab). His work bridges geometric mathematics and machine learning, focusing on developing robust and efficient deep learning architectures grounded in symmetry, equivariance, and physical principles. Education: PhD in Biomedical Engineering (cum laude) from Eindhoven University of Technology Previous Roles: Postdoctoral researcher in applied differential geometry at TU/e Department of Applied Mathematics His research spans: Group convolutional neural networks Symmetry-preserving representation learning Generative modeling on manifolds Physics-informed neural networks Medical imaging applications Recent publications emphasize geometric latent variable models, equivariant diffusion methods, and applications to molecular generation, medical imaging, and physics-driven AI. His team actively explores structure-preserving and self-supervised learning techniques. Scientific Awards MICCAI Young Scientist Award (2018) Philips Impact Award (MIDL 2018) NWO VENI grant: Context-Aware AI in Medical Imaging (2023) NWO VIDI grant: Neural Ideograms - Geometry-Grounded AI (2024) As co-founder of the ICML'24 GRaM workshop , he promotes geometry-grounded approaches in AI. His lab actively investigates geometric regularization, manifold-based PDE forecasting, and symmetry-aware generative methods.

Maris Ozolsمشاهده پروفایل

استادیار

• Quantum Algorithms
• Quantum Information Theory
• Quantum Cryptography
• +۳ مورد دیگر

Maris Ozols is an Assistant Professor at the University of Amsterdam and a researcher at QuSoft, affiliated with the Algorithms and Complexity department at Centrum Wiskunde & Informatica (CWI). His primary research focuses on quantum algorithms and quantum information theory, with significant contributions to quantum complexity, quantum cryptography, and quantum state discrimination. His research interests span quantum algorithms, quantum information theory, quantum cryptography, quantum complexity, and theoretical computer science. Ozols has developed fundamental techniques in quantum query complexity, quantum state discrimination, and quantum cryptographic security models. His work often bridges theoretical computer science with quantum information physics, demonstrating practical implications for quantum computing architectures. His publication record shows consistent output in top venues including Communications in Mathematical Physics, Leibniz International Proceedings in Informatics, and Quantum journal. Recent work (2022-2025) focuses on quantum state discrimination, quantum circuit optimization, quantum machine learning, and cryptographic applications of quantum algorithms. His research demonstrates strong theoretical foundations with practical implications for quantum computing development. Leverhulme Early Career Fellow (University of Cambridge) Ozols has secured research funding through multiple Netherlands Organisation for Scientific Research (NWO) grants including the Quantum Software Consortium (QSC) and Quantum Computation with Bounded Space projects. His collaborative work spans international institutions including the University of Waterloo (where he earned his PhD), University of Cambridge, IBM Research, and various European quantum computing groups. He maintains active research groups in quantum algorithms at both QuSoft and CWI, with recent focus on quantum machine learning applications and quantum cryptographic protocols.

Daan Brinksمشاهده پروفایل

استادیار

• Neuroscience
• Voltage Imaging
• Optical Microscopy
• +۵ مورد دیگر

Daan Brinks is an Assistant Professor at Delft University of Technology in the Department of Imaging Physics within the Faculty of Applied Sciences. He leads the Brinks Lab, which operates at the intersection of physics, biochemistry, optics, mathematics, and nanofabrication, focusing on developing novel imaging tools for neuroscience applications. His research spans both fundamental biophysics and practical biomedical applications, with significant collaborations including Erasmus MC. Faculty of Applied Sciences, Delft University of Technology Department of Imaging Physics (ImPhys) Brinks Lab leader Founding member of BIOlab (Biomedical Intervention Optimization lab) Lead of a convergence Health and Technology Consortium Dr. Brinks' academic journey began with an MSc in Molecular Nanophotonics from the University of Twente (2002-2007), followed by a PhD at ICFO Institute Barcelona (2007-2012). He then completed prestigious fellowships at Harvard University as a Rubicon Fellow (2012-2014) and HMMI Fellow (2014-2017) before joining TU Delft as an Assistant Professor in 2017. His research interests center on voltage imaging techniques to monitor neural activity, optogenetics for neural control, nonlinear optical microscopy for enhanced resolution, and AI applications in bioimaging . The lab develops tools to transduce information in neurons into detectable photons, addressing questions from biophysical principles to behavioral consequences and from subcellular compartments to complete organisms. Current projects include Voltage nanoscopy using plasmonic enhancement, Absolute Voltage Imaging through fluorescence lifetime measurements, Multiphoton Voltage Imaging for deep tissue applications, and advanced image analysis with machine learning. The publications reveal a strong focus on developing novel optical tools for neuroscience, particularly genetically encoded voltage indicators and plasmonic enhancement techniques. His work bridges physics, molecular biology, and neuroscience, with applications ranging from fundamental understanding of neural circuits to cancer cell identification. The research shows progression from fundamental physics (early career) to increasingly applied neuroscience and biomedical applications (recent work), with publications in top journals including Nature, Science Advances, and Nature Biomedical Engineering. Rubicon Fellow (2012-2014) HMMI Fellow (2014-2017) Publications in Nature, Science Advances, Nature Biomedical Engineering Media coverage in major outlets including Delta TU Delft and Trouw Dr. Brinks actively mentors students and researchers, with his lab welcoming enthusiastic students, PhD candidates, and postdocs interested in multidisciplinary projects at the junction of optics, molecular biology, and neuroscience. His research has received external funding through fellowships and likely additional grants supporting his lab's operations. The Brinks Lab collaborates extensively with both academic and medical institutions, particularly evident in the cancer cell research with Erasmus MC. The lab maintains strong physical infrastructure including advanced microscopy systems and nanofabrication capabilities, supporting their work in voltage imaging, plasmonics, and single-cell analysis. They have developed several hardware and software interfaces for automated interaction with excitable tissues and model dynamics in hybrid systems, reflecting their interdisciplinary approach to neuroscience questions.

Ronald de Wolfمشاهده پروفایل

استاد

• Quantum Computing
• Complexity Theory
• Error-Correcting Codes
• +۳ مورد دیگر

Ronald de Wolf is a part-time Full Professor at the Institute for Logic, Language and Computation (ILLC), University of Amsterdam, and a researcher/group leader at the Algorithms and Complexity group of CWI (Dutch Centre for Mathematics and Computer Science). He is an active member of QuSoft and the Amsterdam Theoretical Computer Science ecosystem. His PhD was completed at CWI and ILLC, followed by postdoctoral research at UC Berkeley. Research Focus: De Wolf specializes in quantum computing, complexity theory, and algorithm design. His work explores quantum advantages in computation, communication, and learning, with applications in optimization, machine learning, and information theory. Recent investigations include quantum algorithms for linear algebra, error correction, and communication complexity. Publication Trends: His recent articles (2020-2025) predominantly focus on quantum algorithmic advantages, complexity bounds, and practical applications in machine learning and optimization. Key themes include quantum speedups for linear algebra, error-resilient quantum protocols, and theoretical limits of quantum computation. Awards & Honors: ERCIM Cor Baayen Award (2003) STOC Best Paper Award (2012) STOC Test-of-Time Award (2022) Gödel Prize (2023) Academic Leadership: He currently advises PhD student Lynn Engelberts and has graduated 10 doctoral students. As coordinator of the NWO Gravitation program Quantum Software Consortium , he oversees major research initiatives. He secured participation in EU projects (QAIP, RESQ, QAP, QCS, QALGO, QuantAlgo) and leads research teams at CWI and QuSoft.

• Soft Matter Physics
• Computational Physics
• Machine Learning in Materials Science
• +۷ مورد دیگر

Laura Filion is an Associate Professor at the Faculty of Science, Utrecht University , specializing in Soft Condensed Matter within the Debye Institute for Nanomaterials Science . Her research leverages advanced computational and machine learning algorithms to investigate self-assembly processes in soft matter systems, with applications to sustainable material design. Email: l.c.filion@uu.nl Phone: +31 30 253 3519 Research Interests span soft matter physics , colloidal self-assembly , machine learning in materials science, crystal nucleation , and defect analysis . Her work bridges computational methods with experimental validation, focusing on structure-dynamics relationships in supercooled liquids and active colloids. Scientific Contributions include pioneering studies on quasicrystal stability , entropic interactions , and microtubule self-organization . Key publications in Physical Review Letters , Nature Reviews Physics , and Soft Matter highlight her expertise. Awards NWO-Veni Fellowship (2013) NWO-Vidi Fellowship (2019) Collaborative Efforts involve interdisciplinary projects with physicists, biologists, and materials scientists. She supervises doctoral and master's students indirectly through her research group's publications and network.

Aida Todri-Sanialمشاهده پروفایل

استاد

• Energy-Efficient Circuits
• Quantum Computing
• Neuromorphic Computing
• +۴ مورد دیگر

Aida Todri-Sanial is a Full Professor in the Integrated Circuits group of the Electrical Engineering department at Eindhoven University of Technology (TU/e). She leads the NanoComputing Research Lab and is affiliated with the Center for Quantum Materials and Technology Eindhoven (CQMT-E), EAISI, and the Integrated Circuits group. Her research focuses on energy-efficient circuits, novel computing paradigms (e.g., 3D integration, neuromorphic computing, quantum computing), and nanotechnology-driven architectures. Education: PhD in Electrical and Computer Engineering, University of California Santa Barbara (2009) Bardeen Fellow at Fermi National Accelerator Laboratory (2009–2010) Scientist/Research Director at CNRS (2011–2021) Visiting Fellow at the University of Cambridge (2016–2017) Research Interests: Dr. Todri-Sanial’s work integrates physics and electronics to design unconventional computing systems. Key areas include: Physical design optimization for energy efficiency Oscillatory neural networks (ONNs) for edge AI Quantum computing hardware and error mitigation 3D integration and monolithic-3D architectures Nanomaterials (e.g., VO₂, MoS₂) for neuromorphic and sensing applications Awards & Grants: ERC Consolidator Grant THERMODON (2023) NWO AiNed Fellowship (2024) NWO Quantum Technology Grant (2024) CNRS Bronze Medal (2016), IBM Quantum Open Science Prize (2021), and IEEE Distinguished Lecturer (2022) Labs & Teams: Principal Investigator of the NanoComputing Research Lab Lead researcher in EAISI (Eindhoven Artificial Intelligence Systems Institute) Collaborator with global institutions (e.g., IBM, STMicroelectronics)

Heinrich Wörtcheمشاهده پروفایل

استاد

• Sensor Technology
• Biomechanics
• Nuclear Physics
• +۳ مورد دیگر

Heinrich Wörtche is a Professor at the Faculty of Medical Sciences/UMCG (University of Groningen) and holds professorships at Hanze University of Applied Sciences (Sensors and Smart Systems, since 2018) and Eindhoven University of Technology (Miniature Wireless Explorative Sensor Systems, since 2015). His work spans interdisciplinary domains including sensor technology, nuclear physics, and biomechanics. Professor, Sensors and Smart Systems, Hanze University of Applied Sciences (2018–present) Professor, Miniature Wireless Explorative Sensor Systems, Eindhoven University of Technology (2015–present) His research focuses on sensor systems for health monitoring, nuclear structure analysis (e.g., neutron-skin modes, isospin properties), and biomechanics. Key applications include dementia care, exergaming, and postural control assessment. Recent publications highlight his work on wireless sensor systems for dementia behaviors (2024), nuclear resonance studies (2016), and biomechanical movement analysis using machine learning (2015). Keywords span Gerontechnology , Nuclear Physics , Biomechanics , and Data Analytics . Collaborations include institutions like Hanze University of Applied Sciences, Eindhoven University of Technology, and the University of Groningen. Research outputs total 96, with 2014–2024 active contributions in physics, sensor technology, and health informatics.

B. (Bernd) Ensingمشاهده پروفایل

دانشیار

• Computational Chemistry
• Molecular Simulations
• Catalyst Design
• +۷ مورد دیگر

Dr. Bernd Ensing is an Associate Professor at the van 't Hoff Institute for Molecular Sciences (HIMS) within the University of Amsterdam's Faculty of Science. He directs the AI4Science Laboratory, focusing on integrating artificial intelligence with molecular simulations. His research spans computational chemistry, catalyst design, and biophysical systems, emphasizing bio-inspired materials and electron/proton transfer mechanisms. Key research areas include: molecular simulations of catalytic processes (e.g., hydrogenase enzymes), multiscale modeling of soft materials, and machine learning-enhanced data analysis. He develops advanced algorithms like Path-metadynamics and FABULOUS for free energy exploration and reaction coordinate identification. Notable contributions include studies on polyether solubility in water, light-activated proteins' signaling mechanisms, and adaptive resolution simulations (Hybrid-atomistic/coarse-grained methods). His group collaborates on AI-driven material discovery and sustainable chemistry solutions. He has supervised numerous student projects at bachelor/master levels, requiring expertise in quantum chemistry, thermodynamics, or programming. The AI4Science Lab promotes open-source tools via GitHub and community-driven initiatives like PLUMED tutorials.

• Distributed Systems
• Cloud Computing
• Edge Computing
• +۷ مورد دیگر

Nishant Saurabh is a tenured Assistant Professor at the Department of Information and Computing Sciences , Utrecht University , Netherlands. His research focuses on resource and data management , application scheduling , performance modeling , and optimization in large-scale hybrid distributed systems including Cloud, Edge, and Quantum computing. Recently, he has expanded into ML workload scheduling and causal performance attribution across the Cloud-Edge continuum. Research Expertise : Distributed Systems and Cloud Computing Quantum-HPC Middleware Systems Performance Modeling and Optimization ML/AI Workload Scheduling Cloud-Edge Continuum Architectures Observability Frameworks Scientific Leadership : Associate Editor, Springer's Journal of Cloud Computing Editorial Board, Frontiers of AI book series IBM HPC-Quantum Working Committee member Workshop Chair, IEEE IPDPS 2025 Supervision : He has supervised 16+ Master/Bachelor students on projects including container migration, reinforcement learning for serverless computing, and quantum middleware evaluation. Current PhD students include Diogo Landau (Performance Observability), Nathan Keyaerts (LLM Methods), and Negar Alizadeh (Energy Efficiency).

• Computational polymer physics
• Soft matter
• Nanoscale materials design
• +۷ مورد دیگر

Andrea Giuntoli is an Assistant Professor at the Micromechanics group within the Faculty of Science and Engineering at the University of Groningen . He holds a PhD in Computational Soft Matter and Polymer Physics from the University of Pisa (2018), followed by postdoctoral work at NIST (2018-2019) and Northwestern University (2019-2021) under the ChiMaD project (part of the Material Genome Initiative). His research focuses on theoretical and computational modeling of nanoscale building blocks for advanced polymer composites , particularly in controlling mechanical properties, impact resistance, and self-healing through polymer architecture and graphene dispersion. He has secured significant grants including a VENI grant (2022) and an NWO-XS grant (2022). Key research trends from his recent publications (2021-2025) include machine learning-optimized coarse-graining , energy renormalization methods , impact-resistant coatings , graphene-polymer interfaces , and self-healing polymer glasses . His work bridges materials science , computational physics , and applied polymer engineering . Scientific Awards: VENI Grant (2022) NWO-XS Grant (2022) He actively collaborates across institutions (USA, Netherlands) and disciplines, with research impacts in medical devices , advanced materials , and surface science . His lab at the Zernike Institute for Advanced Materials integrates multi-scale modeling with experimental validation to enhance polymer composite performance.

Ravindra Shindeمشاهده پروفایل

پژوهشگر

• Computational Materials Science
• Quantum Chemistry
• Exascale Scientific Computing
• +۵ مورد دیگر

Ravindra Shinde is a Research Scientist at the University of Twente , Netherlands, affiliated with the Computational Chemical Physics group under the Faculty of Science and Technology . He is also the founder of The Science Dev , a tech and research blog. Education : Ph.D. in Physics (2014) and M.Sc. in Physics (2009) from IIT Bombay, India. His research spans Exascale Scientific Computing , Quantum Chemistry , Time-Dependent DFT , and Topological Materials . He specializes in method development for quantum mechanical simulations and code modernization for high-performance computing . Recent publications focus on Exascale Computing challenges , Quantum Monte Carlo accuracy, and machine learning integration in force field modeling. Notable awards include SERB Postdoctoral Fellowship and multiple Best Presentation Awards . Scientific Awards : Best Poster Award, UC Riverside (2019) Best Presentation Awards, SERB 2018 & IISc 2018 National Postdoctoral Fellowship, India (2016-2018) All India GATE Physics Rank 73 (2009)

Aswani Kumar Cherukuriمشاهده پروفایل

استاد

• Information Security
• Machine Learning
• Data Mining
• +۵ مورد دیگر

Dr. Aswani Kumar Cherukuri is a Professor of Information Technology at Vellore Institute of Technology (VIT), India, with research spanning information security, machine learning, and quantum computing. He serves as a Senior Member and distinguished speaker of the Association for Computing Machinery (ACM) and as Vice-Chair of the IEEE Taskforce on Educational Data Mining. Education: PhD in informational retrieval, data mining, and soft-computing techniques from Vellore Institute of Technology His research focuses on information security, machine learning, data mining, artificial intelligence, quantum computing, and security/privacy with significant contributions to neural networks, computer networks, and IoT. His work bridges theoretical foundations with practical applications in emerging technologies, emphasizing real-world implementation. Recent publications reveal strong trends in AI ethics (accuracy-bias trade-offs in text detection), autonomous systems (aerial vehicle surveillance), quantum computing (Qinterpreter platform development), and cybersecurity (terrorism prediction using BiGRU, internet anomaly detection via GANs). His editorial work on video conferencing security during the pandemic highlights practical societal impacts. Scientific Awards: Young Scientist Fellowship from Tamilnadu State Council for Science and Technology Inspiring Teacher Award from The Indian Express He has secured major research funding from India's Department of Science and Technology, Department of Atomic Energy, and Ministry of Human Resources Development. With over 150 refereed publications and editorial board memberships at international journals including PeerJ Computer Science, he actively shapes academic discourse through 1,375 editorial contributions.

Simon Rommelمشاهده پروفایل

استادیار

• Electrical Engineering
• Quantum Communication
• Terahertz Technology
• +۳ مورد دیگر

Simon Rommel is an Assistant Professor in the Department of Electrical Engineering at Eindhoven University of Technology (TU/e), specializing in Terahertz Systems and Quantum & Terahertz Systems. He holds a PhD from the Technical University of Denmark (2017) and prior degrees from the University of Stuttgart, Aston University, and Scuola Superiore Sant’Anna. His research focuses on converged mm-wave/THz radio and optical links, 5G/6G systems, quantum key distribution (QKD), and advanced optical fibers. He leads the QKD testbed development under Quantum Delta and QTe initiatives. Key projects include QCINed (National Quantum Communication Infrastructure), HiCONNECTS (Heterogeneous Integration), and ALLEGRO (Secure Networks). Rommel has received awards such as the 2023 EuCNC/6G Summit Best Student Paper and 2021 OECC Best Student Paper. His work spans 155+ publications, with recent articles addressing quantum-resistant TLS, polarization mitigation in optical fibers, and 5G/6G fronthaul architectures. He also contributes to editorial roles in journals like Frontiers in Future Transportation and scientific activities including 5G-MOBIX events.