جست‌وجوی استاد و پژوهشگر

• Inverse Problems
• Variational Methods
• Total Variation Regularization
• +۷ مورد دیگر

Jose A. Iglesias Martínez is an Assistant Professor in the Department of Applied Mathematics at the University of Twente, affiliated with the Mathematics of Imaging and AI (MIA) group within the Faculty of Electrical Engineering, Mathematics and Computer Science. He conducts research at the intersection of variational analysis, inverse problems, shape analysis, and machine learning, with a geometric perspective on regularization and optimization. University: University of Twente School: Faculty of Electrical Engineering, Mathematics and Computer Science Department: Department of Applied Mathematics Research Group: Mathematics of Imaging & AI (MIA) His research focuses on analytic and variational methods for inverse problems in imaging, particularly involving total variation and related regularization models. The geometric structure of function domains and convex geometry in minimization problems plays a central role in his work. He applies these methods to imaging, shape analysis, and machine learning, with strong mathematical foundations in PDEs, functional analysis, and optimization. The recent publications reflect a consistent focus on variational regularization, extremal point analysis, sparse optimization, and PDE-constrained problems. Key themes include total variation, TGV, nonlocal perimeters, and shape optimization, with applications in image denoising, optical flow, and fluid dynamics. His work spans both theoretical convergence analysis and algorithmic development, often with computational implementations. Scientific Awards and Recognition: Member of the Editorial Board, Numerical Functional Analysis and Optimization (since August 2023) He actively teaches in applied mathematics, including courses such as Analysis 3, Mathematics behind Data-Driven Methods, and interdisciplinary topics like Art, Mathematics and Technology. He has supervised tutorials and projects in calculus, linear algebra, and modeling. His academic training includes dual MSc degrees in Mathematics and Telecommunication Engineering from Madrid, a PhD (2015) and habilitation (2021) in Mathematics from the University of Vienna, followed by postdoctoral work at the Radon Institute in Linz. He has no listed students yet, but is actively publishing and contributing to the mathematical imaging community. He is involved in editorial work and maintains a strong publication record in top-tier applied mathematics journals.

Paul M.J. Van den Hofمشاهده پروفایل

استاد

• Data-driven modeling
• Control systems
• Dynamic networks
• +۶ مورد دیگر

Paul M.J. Van den Hof is a Full Professor at the Department of Electrical Engineering, Eindhoven University of Technology (TU/e), specializing in data-driven modeling and control of dynamic systems. He leads the Control Systems Group and is affiliated with multiple research centers, including EAISI High Tech Systems, Mobility, and Foundational, as well as the EIRES Research initiative. Research Interests: His work focuses on developing fundamental techniques for dynamic network modeling, closed-loop identification, data analytics, experimental design, and model-based control. Applications span industrial process control, oil reservoir engineering, high-tech mechatronic systems, and cyber-physical systems. Recent projects include SYSDYNET (dynamic network identification), NAPAS (nanometer-accurate actuation), and CADUSY (data-driven modeling using symbolic methods). Scientific Contributions: Van den Hof has authored over 250 research outputs, including foundational work on identifiability in dynamic networks, frequency domain identification, and distributed control algorithms. His 2024-2025 publications address challenges in fault detection, Bayesian network topology identification, and multi-step least squares methods. He emphasizes practical implementation through tools like the SYSDYNET MATLAB toolbox. ERC Advanced Research Grant (2015) Honorary Member, Hungarian Academy of Sciences (2016) IEEE Fellow (2007) and IEEE Life Fellow (2023) IFAC Advisor (2020)

Jack van Wijkمشاهده پروفایل

استاد

• Information Visualization
• Visual Analytics
• Mathematical Visualization
• +۳ مورد دیگر

Jack van Wijk is a Full Professor in Visualization at Eindhoven University of Technology (TU/e). He holds a MSc (1982) and PhD (1986) in Computer Science from Delft University of Technology. His research focuses on information visualization, visual analytics, and mathematical visualization, with notable contributions to flow visualization and cartographic projections. He has co-authored over 160 papers and served as program co-chair for multiple IEEE Visualization conferences (2003–2023). Awards include the IEEE Visualization Technical Achievement Award (2007), Eurographics 2013 Outstanding Technical Contributions Award, and the VGTC Lifetime Achievement Award (2021). In 2023, he was honored with the Order of the Netherlands Lion. He co-founded MagnaView BV and SynerScope BV, and served as Scientific Director of the Data Science Center Eindhoven (2018–2021). Notable projects include SequoiaView (disk visualization), myriahedral projections, and IBFV (Image-Based Flow Visualization).

Thijs van de Laarمشاهده پروفایل

استادیار

• Bayesian Machine Learning
• Active Inference
• Probabilistic Programming
• +۳ مورد دیگر

Thijs van de Laar is an Assistant Professor at the BIASlab (Bayesian Intelligence and Autonomous Systems Laboratory) within the Department of Electrical Engineering at Eindhoven University of Technology. His research bridges advanced computational principles with real-world applications in uncertainty modeling. Education: PhD in Machine Learning (2019), Eindhoven University of Technology MSc in Natural Sciences (2010), Radboud University Nijmegen Research Focus: Bayesian machine learning, active inference, and probabilistic programming, with applications in autonomous agent control, hearing loss compensation, and efficient real-time decision-making systems. His work integrates insights from physics and neuroscience to develop novel computational frameworks. Software Contributions: Key contributor to ForneyLab.jl, a Julia toolbox for automated Bayesian inference through message passing on factor graphs. Also developed Herring.jl, a Poisson node extension for probabilistic modeling. Publications: His 15 most recent articles focus on variational message passing, active inference agents, epistemic value in graphical models, and factor graph-based algorithm design. These works span disciplines including artificial intelligence, control theory, and biomedical engineering.

Silvia Rossiمشاهده پروفایل

پژوهشگر

• Immersive Multimedia Systems
• Extended Reality (XR)
• User Behavior Analysis
• +۳ مورد دیگر

Dr. Silvia Rossi is a postdoctoral researcher in the Distributed and Interactive Systems (DIS) group at Centrum Wiskunde & Informatica (CWI) in the Netherlands. Her work focuses on user behavior analysis and system design for immersive multimedia systems like volumetric video in Extended Reality (XR) applications. She earned her PhD from University College London (UCL) in the Learning and Signal Processing (LASP) group , where she developed clustering algorithms to analyze user navigation patterns in VR systems. Her research bridges human-centric behavioral studies with technical solutions for Quality of Experience (QoE) in 6-DoF VR platforms. Recent work presented at conferences like IEEE VR and ACM Multimedia explores how spatial constraints affect user movement, open-source social VR systems ( VR2Gather ), and behavioral data collection tools. She co-organizes key events like the Spring School on Social XR and chairs QoMEX 2025 sessions. Scientific Recognition: 2023 ACM SIGMM Award for Outstanding PhD Thesis 2022 Lombardi Prize for best UCL EEE doctoral thesis Dr. Rossi's publications highlight trends in XR user modeling , adaptive streaming , and social VR design , with keywords spanning computer science , human-computer interaction , and multimedia engineering . She collaborates extensively with researchers like Pablo Cesar and Irene Viola , and contributes to open-source frameworks in immersive communication.

Just van Rossumمشاهده پروفایل

مدرس

• Type Design
• Typography
• Graphic Design
• +۳ مورد دیگر

Just van Rossum (born 1966) is a Lecturer at the Royal Academy of Art, The Hague, teaching type design and programming in the Graphic Design department for both the Bachelor Graphic Design program and Master Type and Media program. As an independent type designer, graphic designer, and software developer, he bridges academic instruction with professional practice in visual communication design. Education Graduated from the Royal Academy of Art, The Hague in 1989 under Gerrit Noordzij Research Interests Type Design Typography Graphic Design Software Development for Design Computational Design Coded Animations His work pioneers the integration of programming with type design, creating influential tools that transform digital typography workflows while exploring experimental visual forms through coded animation and generative design systems. Scientific Awards Permanent collection of MoMA, New York (for FF Beowolf typeface) Collaborations and Creative Practice LettError collaboration with Erik van Blokland producing award-winning typefaces Lowlands Festival Identity project with Hansje van Halem Dailydrawbot.tumblr.com generative art initiative Academic Contributions He shapes design education through specialized instruction in type programming and experimental typography, mentoring students in the intersection of traditional design principles and computational techniques within the Graphic Design department's curriculum.

• Probability Theory
• Random Graphs
• Stochastic Processes
• +۲ مورد دیگر

Dr. S.A. Donderwinkel is a researcher at the Bernoulli Institute within the Faculty of Science and Engineering at the University of Groningen. Their work focuses on probability theory, random graph models, and stochastic processes, with recent publications exploring graphic sequences, critical tree structures, and directed configuration models. They actively contribute to academic research through collaborations and peer-reviewed publications. University: University of Groningen School: Faculty of Science and Engineering Department: Bernoulli Institute Role: Researcher Email: s.a.donderwinkel@rug.nl Research interests include: Integrated random walks and graphic sequences Critical tree analysis and Cauchy distributions Height bounds in random trees Universality in directed configuration models Asymptotic behavior of random structures Their recent publications (2024-2025) demonstrate expertise in probabilistic combinatorics and graph theory, with applications in theoretical computer science and mathematical physics. All articles exhibit rigorous peer-reviewed academic contributions.

• Visual Communication
• Data Visualization
• Language and Communication
• +۵ مورد دیگر

Dr. Lisanne van Weelden serves as an Associate Professor in the Department of Languages, Literature and Communication within the Faculty of Humanities at Utrecht University. She is affiliated with the Language and Communication research group and the Humanities Institute for Language Sciences, where she focuses on visual communication and data interpretation. Her research examines how visual elements influence understanding across various domains including financial communication, legal contexts, and public policy. Van Weelden's research interests center on visual communication , data visualization , and language processing . She investigates how visual forms affect metaphorical conceptualization, how shape influences semantic memory organization, and how visual representations impact decision-making processes. Her work has particular emphasis on the communication of complex information in pension systems, legal contexts, healthcare, and governmental communications, with significant contributions to understanding how visual elements can either clarify or obscure meaning. Her publication record demonstrates consistent scholarly output with 23 research publications through 2025, showing an evolving focus from foundational work on visual metaphor processing to applied research on data visualization in real-world contexts. Recent work increasingly addresses practical applications of visual communication in financial literacy, legal systems, and public administration, with notable emphasis on pension communication and the use of icons in municipal communications. Her research bridges cognitive science with practical communication challenges, examining both theoretical aspects of visual processing and applied communication effectiveness. Van Weelden actively collaborates with researchers across disciplines including cognitive psychology, legal studies, and public administration. Her work has been featured in academic journals such as IEEE Transactions on Visualization and Computer Graphics, Metaphor and Symbol, and Cognitive Science, as well as in professional and public-facing publications addressing practical communication challenges.

• Robotics and Automation
• Control Systems
• Biomedical Engineering
• +۴ مورد دیگر

Dr. Tajdari is a distinguished researcher at Delft University of Technology, specializing in interdisciplinary fields at the intersection of robotics, control systems, and biomedical engineering. His work focuses on advanced control methodologies, non-rigid registration techniques for medical imaging, intelligent transportation systems, and personalized product design through digital fabrication. He has contributed significantly to the development of adaptive controllers for robotics systems, including Stewart platforms and surgical robots, as well as innovative approaches to 3D/4D human mesh registration for applications in healthcare and biomechanics. Key Research Areas: Autonomous Vehicles, Medical Robotics, Intelligent Transportation, 3D Reconstruction, and Human-Motion Analysis His recent research emphasizes integrating machine learning with traditional control theory to address challenges in traffic management, spinal deformity prognosis, and human-centered design. Collaborations include projects on smart infrastructure systems and personalized medical devices. Over 25 peer-reviewed articles demonstrate his expertise in both theoretical and applied engineering domains.

João Frazãoمشاهده پروفایل

پژوهشگر

• Quantum Cryptography
• Quantum Key Distribution
• Free-Space Optical Communication
• +۳ مورد دیگر

João Frazão is a researcher active in the field of quantum cryptography, with a focus on experimental continuous-variable quantum key distribution (QKD) systems. His work explores the application of QKD over free-space optical channels, addressing challenges such as turbulence, noise power, and real-time signal processing. He collaborates with institutions like Optica Publishing Group and has contributed to advancements in secret key generation, error correction, and adaptive reconciliation protocols. 2021: Active in the NGF - Integration ECO1 project as a project member. 2024: Published multiple conference papers on QKD optimization and real-time quantum communication systems. 2025: Released a significant article on rate-adaptive reconciliation techniques for free-space QKD. His research interests span quantum cryptography, secure communication protocols, optical engineering, and quantum information theory. João's work frequently involves graphics processing units (GPUs) and local oscillator technologies to enhance QKD performance in turbulent environments. João's publications highlight his expertise in quantum key distribution, continuous-variable systems, and free-space optical communication. His projects often collaborate with researchers such as C. M. Okonkwo, K. Gümüş, and A. Albores-Mejia, contributing to the development of practical QKD implementations. He is currently affiliated with institutions involved in the Optical Fiber Communication Conference (OFC) and works on cutting-edge quantum communication technologies.

Martin Roa-Villescasمشاهده پروفایل

پژوهشگر

• Probabilistic graphical models
• Bayesian Machine Learning
• Tensor Networks
• +۵ مورد دیگر

Martin Roa-Villescas is a Doctoral Candidate and Teaching Assistant in the Department of Electronic Systems within the Electrical Engineering school at Eindhoven University of Technology (TU/e). He also holds an external position as a Docent (Lecturer) at Fontys University of Applied Sciences since August 2023. His educational background includes a B.Sc. in Electronic Engineering from the National University of Colombia (2010) and an M.Sc. in Embedded Systems from TU/e (2013). Between 2013 and 2018, he worked as an embedded software designer at Philips Research in Eindhoven. Roa-Villescas' research focuses on probabilistic graphical models, Bayesian machine learning, and tensor network applications. His work spans both theoretical advancements in probabilistic inference algorithms and practical implementations in open-source software. He has made significant contributions to optimizing message passing algorithms and developing efficient execution schedules for Bayesian inference. His recent publications demonstrate a clear trajectory toward improving the scalability and efficiency of probabilistic inference methods, with applications spanning audio signal processing, robotics, and hearing aid technology. The development of TensorInference, a Julia package for tensor-based probabilistic inference, represents his commitment to open-source tools that advance the field. As a researcher involved in the STW Zero Autonomous Acoustic Systems project (2017-2024), he has contributed to advancing acoustic sensing technologies through probabilistic modeling approaches. His work aligns with UN Sustainable Development Goals related to technology innovation and accessibility.

• Protein Intake
• Vegan Dietary Patterns
• Muscle Health in Ageing
• +۴ مورد دیگر

Pol Grootswagers is an Assistant Professor in Nutritional Biology at Wageningen University , focusing on plant-based nutrition and muscle health during aging. His research bridges nutritional science with clinical applications through collaborations across Europe. Active in NHANES data analysis Co-promotor in multiple PhD projects Recipient of James Lind Prijs 2021 Research interests center on protein intake optimization in older adults, plant-based diet impacts , and biological aging markers . Current projects examine resistance training interventions, sustainable protein sources, and AI applications in nutritional assessment. Scientific contributions include developing the Meal Protein Quality Score tool and analyzing telomere length relationships with dietary patterns. Media frequently cites his work on omega-3's anti-aging effects and plant protein adequacy . James Lind Prijs 2021

• Computer Vision
• Computer Graphics
• Machine Learning
• +۶ مورد دیگر

Dimitrios Tzionas is an Assistant Professor for 3D Computer Vision at the University of Amsterdam (UvA), leading research at the intersection of Computer Vision, Computer Graphics, and Machine Learning. His work focuses on reconstructing and modeling 3D human-body interactions with objects and scenes, supporting applications in Robotics, Mixed Reality, and the Metaverse. Academic Affiliation: University of Amsterdam (since 2022), Max Planck Institute for Intelligent Systems (2016-2022) Education: PhD in Computer Science (University of Bonn, 2017), MSc in Electrical & Computer Engineering (Aristotle University, Thessaloniki) His research emphasizes whole-body 3D interaction , including pose estimation, grasp synthesis, and contact-aware modeling. He develops methods like InteractVLM for semantic contact estimation and PICO for dense 3D contact datasets, leveraging vision-language models and optimization frameworks. Recent publications at CVPR, ICCV, and SIGGRAPH Asia highlight advancements in 3D reconstruction, avatar synthesis (PuzzleAvatar), and interactive dynamics (InterDyn). His work is supported by an ERC Starting Grant (2024-2030) and industry partnerships (Google, NVIDIA). Scientific Awards ERC Starting Grant (2024) ELLIS Scholar (2025) Outstanding Reviewer at CVPR, ICCV, ECCV He advises multiple PhD students, including Alvaro Budria and Lixin Xue , and collaborates with institutions like ETH Zurich and MPI-IS. His team's tools (e.g., ICON, GRAB) are widely adopted in academic and industrial research.

Frank van der Meulenمشاهده پروفایل

استاد

• Statistical Inference for Stochastic Processes
• Bayesian Computation
• Filtering Methods
• +۴ مورد دیگر

Frank van der Meulen is a Professor of Mathematical Statistics at the Vrije Universiteit Amsterdam (VU), where he leads the Department of Mathematics. He holds leadership roles including Director of the VU Bachelor Programme in Business Analytics, Chair of the Mathematical Statistics section at the Netherlands Society for Statistics and Operations Research (VVSOR), and Organizer of the nationwide Van Dantzig seminar. His research focuses on statistical inference for stochastic processes, Bayesian computation, and applications in fields like sports engineering, climate science, and maritime engineering. He has developed influential methods such as 'backward filtering forward guiding' for simulating conditioned Markov processes. Frank obtained his PhD in 2005 from VU Amsterdam and has held academic positions at TU Delft (2007–2022) before returning to VU as a Full Professor in 2022. He teaches courses in statistics, probability, and data science, and has authored packages like BridgeLandmarks and BayesianDecreasingDensity. His work bridges theoretical advancements with practical applications, emphasizing collaboration across disciplines. Research interests include Bayesian computational methods (MCMC, SMC), stochastic differential equations, and inference for diffusions on manifolds. Recent work explores stochastic phylogenetic models and fatigue calculations for maritime structures. He consults on statistical and machine learning projects, offering expertise through his GitHub repositories and published software tools.

• Bayesian Statistics
• Computational Statistics
• Bayesian networks
• +۴ مورد دیگر

Marco Grzegorczyk is an Associate Professor of Computational Statistics at the University of Groningen, affiliated with the Department of Statistics and Probability within the Bernoulli Institute. His research focuses on Bayesian networks, computational statistics, and their applications in systems biology and gene regulatory network analysis. He holds editorial roles at journals like Computational Statistics and Statistica Neerlandica . Education: PhD in Statistics (2006, TU Dortmund University), Habilitation (2012, TU Dortmund), and Diplom in Statistics (2003, Dortmund University). Research Interests : Bayesian network development for systems biology, statistical inference of gene regulatory networks, and machine learning approaches for biological data analysis. His work bridges statistical methodology with applications in genetics, proteomics, and clinical studies. Key contributions include advancements in non-homogeneous dynamic Bayesian networks and methodologies for handling incomplete data. His supervision of 10+ PhD students has led to impactful studies in clonal tracking and gene therapy safety analyses. Awards : Basis Kwalificatie Onderwijs (2017), FIT Fellowship (2017), and recognition for teaching innovation at Groningen University. He co-leads the Data Science & System Complexity group and actively participates in grants, including former DFG-funded research on Bayesian networks in systems biology.