Maurice Heemels is a Full Professor at Eindhoven University of Technology (TU/e), leading the Control Systems Technology group. He holds additional professorships in EAISI Mobility, EAISI Foundational, EAISI Health, and EAISI High Tech Systems. His research focuses on hybrid and networked systems, emphasizing resource-aware control, event-triggered strategies, and cyber-physical systems integration. He is an IEEE Fellow and chairs the IFAC Technical Committee on Networked Systems. Academic Background: MSc and PhD in Mathematics (TU/e, 1995 and 1999, both summa cum laude ) Visiting Professorships: ETH Zurich (2001), UC Santa Barbara (2008) Industry Experience: Research & Development at Océ NV Research Interests: Hybrid Systems, Networked Control, Event-Triggered Control Model Predictive Control (MPC) in healthcare and high-tech systems Cyber-Physical Systems for applications like lithography and precision agriculture Key Contributions: Developed Hybrid Integrator-Gain (HIGS) systems and Projection-Based Control methodologies Recipient of a VICI Grant for wireless control systems research Oversaw over €7M in research funding from NWO, EU, and industry Awards & Recognition: Automatica Outstanding Service Award (2014) Best Paper Awards (EBCCSP 2017, etc.) Invited Keynote Speaker at ECC, CDC, and others Grants & Projects: Current Projects: COMEDI (Cost-effective Mechatronics), PROACTHIS (Projection-based Control) Past Projects: Fault Detection in Wafer Scanners, Drone-based Farming Labs & Teams: Active in TU/e’s Cyber-Physical Systems and Systems Engineering research groups, collaborating globally on nonsmooth dynamics and hybrid systems.
جستوجوی استاد و پژوهشگر
استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشیتان را پیدا کنید و با او ارتباط بگیرید.
نمایش ۱-۱۵ از ۷۰ استاد راهنما
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Muharrem Bayraktarمشاهده پروفایل
استادیار
Muharrem Bayraktar is an Assistant Professor at the MESA+ Institute for Nanotechnology at the University of Twente, specializing in XUV Optics. His research focuses on extreme ultraviolet (EUV) optics, plasma spectroscopy, and adaptive optical systems. He leads projects involving EUV source metrology, piezoelectric thin film actuators, and laser-driven plasma diagnostics. Research Interests: Bayraktar’s work centers on developing advanced EUV light sources for nanolithography applications. He investigates plasma physics in tin-based EUV emitters, optimizing thin film materials for adaptive optics, and improving spectral characterization techniques. His group explores piezoelectric thin films for precision wafer tables and multilayer mirror systems to enhance EUV beam control. Awards: 3rd Place in Simon Stevin Fellow Contest (2016) Best poster award (2018) Best poster award (2019) Advising & Activities: Supervises research on EUV source development and piezoelectric actuators. Engages in international collaborations on plasma diagnostics and adaptive optics. Active in presenting at conferences on topics like ‘EUV Source Metrology’ and ‘Nanolithography Systems’. Labs/Teams: Leads the XUV Optics team within MESA+, collaborating with industry partners on EUV lithography systems and advanced optical components.
- Mechatronics
- Nonlinear Control Systems
- Robotics
- +۵ مورد دیگر
Prof. Bayu Jayawardhana is a Full Professor in Mechatronics and Control of Nonlinear Systems at the University of Groningen, affiliated with the Faculty of Science and Engineering. He leads the Jayawardhana Group focusing on opto-mechatronics and advanced nonlinear control theories. His roles include Director of Engineering and Scientific Director of the Engineering and Technology Institute Groningen. He holds editorial positions in journals like International Journal of Robust and Nonlinear Control and European Journal of Control . Education: PhD in Control and Power Group from Imperial College London (2006), M.Eng from Nanyang Technological University (2003), and B.Eng from Institut Teknologi Bandung (2000). Research interests span opto-mechatronics for high-tech systems, nonlinear control, and systems biology. Key projects include digital twins for energy optimization, control of ocean energy systems, and modeling of cryogenic actuators for telescopes. His work integrates AI and model-based methods for high-performance systems. Notable awards include the 2016 FSE Faculty Teacher of the Year Award and the Ben Feringa Impact Award (2020). He advises on ventures like Ocean Grazer B.V. and Sencilia B.V. Teaching includes graduate courses on nonlinear control, opto-mechatronics, and fitting dynamical models to data. His research labs include the Groningen Centre for Systems and Control and the Data Science and Systems Complexity Center.
Sara Magliacaneمشاهده پروفایل
استادیار
Sara Magliacane is an Assistant Professor at the University of Amsterdam , affiliated with the Amsterdam Machine Learning Lab (AMLab) and the Informatics Institute . She also holds a Research Scientist position at the MIT-IBM Watson AI Lab and has been an ELLIS Scholar since 2022. Education PhD in Artificial Intelligence (2017), VU Amsterdam MSc in Computer Engineering (2011), Politecnico di Milano BSc in Computer Engineering (2008), Università degli Studi di Trieste Research Focus : At the intersection of Causality and Machine Learning , her work addresses Causal Representation Learning from high-dimensional data (images, sequences) Causal Discovery in latent confounder scenarios Causality-inspired Reinforcement Learning for robustness and adaptability Neurosymbolic AI for theoretical guarantees Publication Trends : Her recent work explores Factored adaptation in non-stationary environments (NeurIPS 2022) Temporal causal identifiability (ICML 2022) Binary interaction-based causal discovery (UAI 2023) Safe exploration in visual RL (HSCC 2021) Structure learning lower bounds (NeurIPS 2020) Scientific Recognition : ELLIS Scholar (2022–present) Spotlight presentations at ICML 2022 and ICLR 2022 Advising & Collaborations : Currently supervising 6 PhD students at the University of Amsterdam and AUMC, with 12 alumni advisees. Collaborates with researchers at MIT-IBM Watson AI Lab, Simons Institute, and TUM.
Ralf Peeters is a Full Professor in Mathematics of Knowledge Engineering at Maastricht University's Faculty of Science and Engineering , Department of Advanced Computing Sciences. He serves as Vice-Dean of Research and Director of the STEM Graduate School, while leading the university's team at the inter-university research school DISC and co-chairing the Mathematics Centre Maastricht. Education: PhD in Mathematics (Free University, Amsterdam, 1994) Technical Mathematics (Delft University of Technology, 1988) Research Interests span applied mathematics, systems and control theory, signal/image processing, artificial intelligence, and biomedical engineering applications. His work bridges mathematical techniques with real-world challenges in healthcare and industrial systems. Recent Publications highlight advancements in deep learning for cardiac signal reconstruction, tensor-based signal decomposition, and recurrence plot analysis. These works integrate machine learning with clinical diagnostics, particularly in electrocardiographic imaging and arrhythmia characterization. Key Collaborations: Mathematics Centre Maastricht Dutch Mathematics Platform Dutch Institute of Systems and Control Leadership Roles: Vice-Dean of Research (FSE), Director of STEM Graduate School, Head of DISC-affiliated team, and Co-Chair of Mathematics Centre Maastricht. He has supervised over 25 PhD projects, emphasizing applied research across health and industrial domains.
Nima Monshizadeh Naini is a Professor in the Faculty of Science and Engineering at the University of Groningen. He holds the position of Chair of the IEM Program Committee and serves on the boards of ENTEG and YSEN. His academic journey includes a PhD in Control Systems from the University of Groningen (2013, Cum Laude), followed by postdoctoral research at the University of Cambridge (2016-2017) and the University of Groningen (2014). He has been an Assistant Professor since 2018 and was awarded the NWO Open Competition Grant in 2021. His research focuses on Cyber-Physical Human Systems (CPHS) , addressing two core areas: (1) Coordination of self-interested users in power systems and traffic networks using dynamic information design and game-theoretic mechanisms; and (2) Privacy-aware control and optimization with tailored encryption methods for dynamic systems. Applications include energy markets, microgrids, and smart grids. He has published extensively in top venues like IEEE CDC and Automatica, with key topics including privacy-preserving algorithms, distributed control, and optimal intervention design. His work contributes to UN Sustainable Development Goals related to affordable energy and responsible consumption. Education: PhD in Control Systems, University of Groningen (2013) Research Associate, University of Cambridge (2016-2017) Postdoctoral Researcher, University of Groningen (2014) Awards: Cum Laude distinction for PhD thesis (2013) NWO Open Competition Grant (2021) Advising & Grants: Supervised 5 PhD students Editorial roles in IEEE journals and conference proceedings Labs/Teams: Leading the Cyber-physical systems group within the Smart Manufacturing Systems institute.
Rodrigo Gonzálezمشاهده پروفایل
استادیار
Rodrigo González is an Assistant Professor at the Department of Mechanical Engineering, Eindhoven University of Technology, since 2022. His research focuses on data-driven modeling, estimation, and control methods for high-tech precision systems, with applications in motion control and continuous-time system identification. Education: Ph.D. in Electrical Engineering (KTH Royal Institute of Technology, 2022) M.Sc. in Electronic Engineering (Universidad Técnica Federico Santa María, 2016) His work emphasizes continuous-time system identification, state-space modeling, and Bayesian estimation techniques. Key research themes include motion control tuning, multivariable systems, and noise/disturbance modeling in precision engineering applications. Rodrigo has received the Best Electronic Engineering Student Award (2016) and Best Thesis Award from Universidad Técnica Federico Santa María. He has active collaborations with institutions like Universidad Técnica Federico Santa María through visiting researcher appointments. Scientific awards include: Best Electronic Engineering Student Award (2016) Best Thesis Award (Universidad Técnica Federico Santa María)
Han La Poutré is a Professor at Delft University of Technology and a Senior Researcher/Manager at CWI's Intelligent and Autonomous Systems group. His research focuses on multi-agent systems, computational intelligence, and optimization techniques for Smart Energy Systems (SES), integrating electrical engineering and economics frameworks. M.Sc. in Mathematics (1986, TU Eindhoven) Ph.D. in Computer Science (1991, Utrecht University) His work spans game theory , reinforcement learning , and market mechanism design for energy grid optimization, addressing challenges in congestion management, demand-side bidding, and AI-driven media sector innovation. Recent projects include AI, Media & Democracy Lab and RESCUE (Cyber-Physical Energy Security). Key trends in his 2020-2025 publications include: Hybrid fairness/welfare frameworks for grid congestion Double-sided auction mechanisms for heat/power markets Deep reinforcement learning in discrete action spaces Game-theoretical cybersecurity modeling Multi-temporal demand response coordination Scientific Awards 2015: Best paper award at GECCO-2015 He has led NWO-funded projects like Computational Capacity Planning in Electricity Networks and served as Vice President of ERCIM. Current affiliations include ACM Transactions on Intelligent Systems editorial board.
Claudio De Persis is a Professor in the Faculty of Science and Engineering at the University of Groningen, Netherlands. He holds a Laurea degree (cum laude) in Electrical Engineering from the University of Rome La Sapienza (1996) and a PhD in Control Systems (2000) from the same institution. His research focuses on automatic control, particularly data-driven control, nonlinear systems, cyber-physical systems, and energy systems. He has held academic positions at the University of Rome La Sapienza (2002–2011), the University of Twente (2009–2011), and currently leads the Groningen Center for Systems and Control within the Engineering and Technology Institute. His expertise includes fault detection in nonlinear systems, resilient control under Denial-of-Service attacks, and distributed control of energy networks. He has authored over 250 publications, including seminal works on quantized control and cyber-physical systems. He serves on editorial boards of journals like Automatica and IEEE Transactions on Automatic Control . De Persis has received two IEEE Outstanding Paper Awards for contributions to control theory. His research integrates control theory with data science, addressing challenges in smart grids and distributed systems. He holds patents for energy system control and collaborates on interdisciplinary projects, such as data center optimization and resilient networked systems. His current research emphasizes data-driven methods for controller synthesis, leveraging convex optimization and system identification to ensure stability and performance. He also explores privacy-preserving distributed control algorithms for power networks and aggregative games.
Valentina Breschiمشاهده پروفایل
استادیار
Valentina Breschi is an Assistant Professor in the Control Systems Group at the Department of Electrical Engineering, Eindhoven University of Technology (TU/e). She holds a Ph.D. from IMT School for Advanced Studies Lucca, with postdoctoral and junior faculty experience at Politecnico di Milano. Her research focuses on data-driven control, jump model learning, meta-learning for system identification, and human-centered policy design for mobility systems. She contributes to UN Sustainable Development Goals related to sustainable infrastructure and innovation. Education: B.Sc. in Electronic and Telecommunication Engineering (University of Florence, 2011) M.Sc. in Electrical and Automation Engineering (University of Florence, 2014) Ph.D. in Control Systems (IMT School for Advanced Studies Lucca, 2018) Research Interests: Her work spans data-driven control methodologies, including LPV control, predictive control, and ethical frameworks for policy design. She explores applications in sustainable mobility, energy systems, and healthcare, emphasizing fairness and social impact. Labs/Teams: She is part of the Control Systems Group, collaborating on projects like the CONSIDER study and the design of fair-MPC frameworks. Her work integrates theoretical control principles with real-world applications in smart systems and social networks.
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.
Gert Witvoetمشاهده پروفایل
استادیار
- Motion Control
- Nuclear Fusion
- Astronomy
- +۷ مورد دیگر
Gert Witvoet is a part-time Assistant Professor at the Mechanical Engineering Department of Eindhoven University of Technology (TU/e) , specializing in motion control for scientific applications. He is also a Senior Scientist at TNO Technical Sciences since 2012, working on optomechatronic control systems in space, astronomy, and Big Science projects. Research Focus: Motion control, feedback control, and injection locking in fusion plasmas Teaching: Coordinating Control Engineering and Motion Control Tuning courses Collaborations: TNO, DIFFER, and FOM Rijnhuizen His research explores the intersection of nuclear fusion and control technology, with a particular emphasis on stabilizing plasma instabilities in tokamak devices. He has contributed to projects like TROPOMI , LISA , and ITER , focusing on precise control mechanisms for high-tech systems. Recent work involves free-space optical communication systems, where he develops control algorithms for accurate pointing mechanisms in satellite-ground communications. His article trends highlight expertise in reset control , feedback stabilization , and dynamic noise budgeting . 2008: Best Junior Presentation (BJP) Award 2020: Best Paper Recognition at IEEE AMC2020 At TU/e, Witvoet supervises research projects and collaborates with industry partners via the Mechatronics Academy. His grants include TNO and FOM Rijnhuizen funding for fusion control systems. He works with the Control Systems Technology Group and contributes to the Learning, Identification and Control of High-Tech Systems research area.
Xiaodong Chengمشاهده پروفایل
استادیار
- Control Systems
- Optimization
- Machine Learning
- +۵ مورد دیگر
Xiaodong Cheng is an Assistant Professor at the Mathematical and Statistical Methods (Biometris) group in the Department of Plant Science at Wageningen University & Research. His research focuses on control systems, optimization, and machine learning, with applications in agricultural and energy systems. He holds a Ph.D. (cum laude) from the University of Groningen, under Prof. Jacquelien Scherpen, and prior roles include Research Associate at the University of Cambridge and Postdoctoral Researcher at Eindhoven University of Technology. Education: B.S. and M.E. from Northwestern Polytechnical University, China (2011, 2014) Ph.D. (cum laude) in Engineering from the University of Groningen, Netherlands (2018) Research Interests: Data-driven modeling, dimensionality reduction, learning-based control, system identification, and applications in agriculture and energy. He emphasizes practical implementations through tools like SYSDYNET and Bayesian neural ODEs for greenhouse systems. Key Contributions: His work spans model reduction for network systems, fault-tolerant control, and stochastic MPC for greenhouse production. Recent trends in his publications highlight advancements in resilient microgrid control, precision agriculture via drone-based sensing, and Bayesian methods for dynamic systems. Awards: Automatica Paper Prize Award (2017–2019) IEEE Transactions on Control Systems Technology Outstanding Paper Award (2020) Labs/Teams: Leads the Biometris group's efforts in integrating control theory and machine learning for sustainable systems. His work often collaborates with agricultural and energy sector stakeholders for real-world impact.
Koen Tielsمشاهده پروفایل
استادیار
Koen Tiels is an Assistant Professor in the Control Systems Technology (CST) group at the Department of Mechanical Engineering of Eindhoven University of Technology (TU/e). His research focuses on the identification of nonlinear dynamical systems, combining techniques from system identification and machine learning. Education Master's in Electromechanical Engineering, Vrije Universiteit Brussel (2010) PhD in Electromechanical Engineering, Vrije Universiteit Brussel (2015) His work contributes to areas such as magnetic hysteresis modeling using physics-aware neural networks, optimal control design with low computational cost, and kernel-based identification methods for sampled data. He has collaborated with institutions like Uppsala University and TU/e's EAISI (Eindhoven Artificial Intelligence Systems Institute) on high-tech systems and mechatronics. Recent publications emphasize applications in recurrent neural networks for magnetic hysteresis, sparse modeling of piezoelectric systems, and robust experiment design for MIMO systems. His research aligns with UN Sustainable Development Goals related to clean energy and advanced technologies.
Wouter Kouwمشاهده پروفایل
استادیار
Wouter Kouw is an Assistant Professor at the Electrical Engineering department of Eindhoven University of Technology (TU/e) , leading the Bayesian Intelligent Autonomous Systems lab. With a dual PhD in Computer Science (2018, TU Delft) and MSc in Neuroscience (2013, Maastricht University) , he bridges neurobiology and artificial intelligence through variational Bayesian inference and active inference frameworks. Research Focus : Probabilistic machine learning systems using message passing algorithms on factor graphs , applied to mobile robotics and adaptive control Key Projects : CONTACT-AI (contact-rich robot navigation), FEP-walker (active inference-based locomotion), and BayesBrain (hybrid neuro-in-silico computing) His work spans nonlinear system identification , uncertainty quantification , and sensor modeling , with recent publications in IEEE Transactions , Entropy , and Communications in Computer and Information Science . Awards include the Niels Stensen Fellowship (2017) and TU/e Team Science Award nomination (2023) . Collaborations extend to institutions in Germany, USA, and Denmark, with teaching responsibilities in Bayesian Machine Learning and Neuro Computation .