جستجوی استاد راهنمای دانشگاهی

• Autonomous Systems
• Robotics
• Motion Planning
• +۳ مورد دیگر

Javier Alonso-Mora is a Professor in the Department of Mechanical Engineering at Delft University of Technology, specializing in Learning & Autonomous Control. His research focuses on autonomous systems, robotics, motion planning, and transportation logistics, with applications in mobile manipulation, dynamic environments, and urban mobility. He leads key projects such as INTERACT (Intuitive Interaction for Robots among Humans) and ACT (Perceptive Acting Under Uncertainty), exploring human-robot interaction, autonomous vehicles, and healthcare robotics. Notable achievements include an ERC Starting Grant (2022) and a Veni Grant (2017). His work addresses challenges in robot navigation, control systems, and fleet optimization, with contributions to both theoretical advancements and practical implementations. Projects like TRiLOGy focus on sustainable water transportation, while HARMONY advances assistive robotics in healthcare. Alonso-Mora’s research leverages geometric fabrics for motion planning, probabilistic modeling for dynamic environments, and multi-agent coordination. He collaborates internationally and contributes to open-source frameworks for robotics. His recent publications emphasize safety-aware control, instance-aware semantic mapping, and adaptive systems for cluttered environments.

Ieke Moerdijkمشاهده پروفایل

استاد

• Algebraic Topology
• Differential Topology
• Mathematical Logic
• +۳ مورد دیگر

Prof. Dr. Ieke Moerdijk is a distinguished Professor of Mathematics at the Mathematical Institute of Utrecht University, part of the Faculty of Science. Previously, he held positions at Radboud University (2011–2016) and has been affiliated with institutions like the University of Chicago, Cambridge, and the University of Amsterdam, where he earned his PhD in Mathematics (1985, Cum Laude). His research focuses on algebraic and differential topology, homotopy theory, and applications of topological structures to mathematical logic. He is renowned for co-authoring influential books such as Sheaves in Geometry and Logic (with S. Mac Lane) and Introduction to Foliations and Lie Groupoids (with J. Mrcun). Moerdijk has received prestigious awards including the Spinoza Prize (2012) and the Descartes-Huygens Prize (2011), and is a member of the KNAW and Academia Europaea. His current research emphasizes the theory of dendroidal sets and homotopy operads. He has held visiting positions at institutions like Cambridge, McGill, and Sydney. His academic contributions span editorships, teaching, and supervising numerous students. Moerdijk’s work bridges foundational mathematics with advanced categorical and topological frameworks, influencing areas from algebraic geometry to logic. Education: Bachelor’s/Master’s in Mathematics, Philosophy, and Linguistics at University of Amsterdam PhD in Mathematics, University of Amsterdam (1985) Awards: Spinoza Prize (2012), Descartes-Huygens Prize (2011) Member of KNAW (2006), Academia Europaea (2014) Huygens Fellowship (1986), PIONIER Grant (1995) Research Interests: Algebraic topology, homotopy theory, operads, category theory, and mathematical logic. Moerdijk’s publications include foundational works on dendroidal sets and simplicial methods, with recent contributions addressing ∞-operads and univalent completion. His research often explores connections between algebraic structures and topological spaces, with applications to higher category theory.

Andre Bergerمشاهده پروفایل

دانشیار

• Operations Research
• Optimization Algorithms
• Combinatorial Optimization
• +۳ مورد دیگر

Andre Berger is an Associate Professor of Operations Research at Maastricht University, affiliated with the QE Operations Research department within the School of Business and Economics. He holds a PhD in Mathematics from Emory University (2006) and completed a postdoc at Technical University Berlin. His research focuses on optimization algorithms, combinatorial optimization, and their applications in scheduling, network design, and operations research. Notable contributions include work on the many-visits Traveling Salesman Problem and cluster editing algorithms. Berger’s recent publications span scheduling theory, MRI-based clinical research collaborations, and theoretical advancements in facility location models. He is based at Tongersestraat 53, Maastricht, and can be reached via a.berger@maastrichtuniversity.nl. Education: MSc in Mathematics, Emory University (2003) PhD in Mathematics, Emory University (2006) Research Interests: Berger’s work bridges theoretical computer science and practical applications in operations research, emphasizing algorithm design for complex optimization problems. Key areas include scheduling algorithms, network flow optimization, and geometric optimization challenges such as the Apollonius problem in facility location. His interdisciplinary approach integrates mathematical programming with real-world scenarios in telecommunications and healthcare.

Daniela Kraftمشاهده پروفایل

استاد

• Self-Assembly
• Soft Matter Physics
• Biophysics
• +۴ مورد دیگر

Daniela Kraft is a Professor of Experimental Physics at the Huygens-Kamerlingh Onnes Laboratory , part of the Leiden Institute of Physics (LION) at Leiden University. She obtained her Ph.D. cum laude from Utrecht University and completed postdoctoral research at New York University's Center for Soft Matter Research with a Rubicon grant. Her research bridges self-assembly in soft and biological matter , including colloidal particles , lipid membranes , and active systems . Key awards include the NWO Athena Prize (2019) , ERC Starting Grant , VENI/VIDI fellowships , and the Biophysical Journal Paper of the Year (2017) . She has published extensively in journals like Nature Communications , ACS Nano , and Physical Review Letters , with recent work on membrane-deforming colloids , non-additive interactions , and anisotropic microswimmers . Research Focus : Self-organization principles in biological and synthetic systems, colloidal model systems, and non-equilibrium physics. Labs : Leads the Kraft Lab at Leiden University. Education : Ph.D. in Physics (Utrecht University), Postdoc in Soft Matter Physics (NYU).

Pascal Mettesمشاهده پروفایل

استادیار

• Hyperbolic Deep Learning
• Computer Vision
• Vision-Language Models
• +۳ مورد دیگر

Pascal Mettes is a tenured Assistant Professor at the University of Amsterdam within the Informatics Institute, specializing in Artificial Intelligence. He leads groundbreaking research in hyperbolic deep learning, a field he has significantly advanced through theoretical developments and practical applications in computer vision and multimodal learning. His research focuses on three primary domains: hyperbolic vision-language models that address the hierarchical nature of language-vision relationships; hierarchical deep learning using hyperbolic embeddings that naturally accommodate exponential growth patterns; and robust deep learning in hyperbolic space that improves out-of-distribution detection and network resilience. Mettes has established himself as a leading figure in this emerging field through numerous publications at top-tier conferences including CVPR, ICCV, ICML, NeurIPS, and ICLR. His recent work demonstrates how hyperbolic geometry provides natural solutions to fundamental limitations in modern deep learning, particularly regarding hierarchical data structures that cannot be adequately represented in Euclidean space. The publication trends show increasing impact and recognition in the computer vision and machine learning communities, with multiple papers receiving oral presentations and best paper nominations. Best paper nomination ESWC25 for 'Designing Hierarchies for Optimal Hyperbolic Embedding' Finalist MM 2023 Best Open-Source Software Competition (for HypLL) Multiple reviewer awards across major conferences including CVPR, ICLR, ECCV, ICML, and NeurIPS MM 2016 Best Doctoral Student Award TRECVID 2015 Winner Multimedia Event Detection Benchmark Mettes actively mentors eight PhD students working on hyperbolic learning and related topics, while also securing significant research funding including ELLIs PhD Award, NWO ClickNL, Google Perception Academic Funding, and Data Science Centre PhD Grants. He serves in prominent academic roles as Program Chair for International Conference on Multimedia Retrieval 2026 and has organized multiple workshops on hyperbolic learning at major conferences. His leadership in establishing hyperbolic deep learning as a recognized research direction is evident through his survey paper in IJCV 2024 and the development of the HypLL library for hyperbolic learning.

Theo Hofmanمشاهده پروفایل

دانشیار

• Powertrain Systems
• Automotive Engineering
• Hybrid Electric Vehicles
• +۵ مورد دیگر

Theo Hofman is an Associate Professor and Program Director in the Mechanical Engineering Department at Eindhoven University of Technology (TU/e). He specializes in integrated design methods for complex engineering systems, focusing on powertrain systems for automotive, maritime, and aerospace applications. His work emphasizes computational design synthesis, machine learning, and model-based optimization. Education: Hofman holds an MSc (1999) and PhD (2007) in Mechanical Engineering from TU/e. He has held roles at Thales Cryogenics and Drivetrain Innovations before joining TU/e. He also served as an Invited Professor at ETH Zurich and Université Polytechnique Hauts-de-France. Research Interests: His research spans hybrid electric vehicles, powertrain design, energy management systems, and sustainable transportation. Key areas include automated design tools, thermal management, and co-design of plant and control systems. Applications include electric trucks, ships, and aircraft. Articles Trends: His recent publications (2021–2025) emphasize electric vehicle infrastructure optimization, battery systems, and control strategies. Key themes include energy efficiency, thermal management, and co-design methodologies for automotive and mobility systems. Scientific Awards: IEEE VPPC 2024 Best Paper Award. Advising & Grants: He has supervised over 104 MSc, 14 PDEng, and 10 PhD students. Active projects include the 'Green Transport Delta' initiative (2021–2024) and Bosch Transmission collaborations. His courses include 'Electric and Hybrid Vehicle Powertrain Design' and 'Automotive Systems Engineering Project.' Labs/Teams: He leads the Group Hofman and collaborates with the MEGEVH (France) and TU/e’s EAISI Mobility initiative. His work contributes to UN Sustainable Development Goals related to affordable and clean energy, industry innovation, and climate action.

Tobias Müllerمشاهده پروفایل

استاد

• Combinatorics
• Probability Theory
• Random Graphs
• +۵ مورد دیگر

Prof. Tobias Müller is a Professor at the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence at the University of Groningen. His academic journey includes previous positions at Utrecht University, CWI (Centrum Wiskunde & Informatica), Tel Aviv University, and Eindhoven University of Technology, with a doctorate from the University of Oxford under Colin McDiarmid. His research focuses on combinatorics, probability theory, random graphs, percolation, discrete and stochastic geometry, and combinatorial game theory. He has contributed extensively to understanding complex networks, hyperbolic models, and geometric random structures. Research Interests: Random Graphs and Percolation Theory Discrete and Stochastic Geometry Hyperbolic Network Models Probabilistic Combinatorics Geometric Probability Graph Algorithms and Connectivity Notable Contributions: Analysis of Voronoi and Poisson-Voronoi percolation in hyperbolic planes. Studies on Mallows random permutations and their cycle structures. Research on component games and logical limit laws in graph theory. Investigations into the geometry and properties of random geometric graphs. Grants & Collaborations: Active in organizing workshops and conferences on random graphs and geometric networks, including the BIRS Workshop on Random Geometric Graphs and the STAR Workshops series. Labs/Teams: Member of the Bernoulli Institute’s research groups, focusing on stochastic studies, combinatorics, and algorithmic methods.

Federico Toschiمشاهده پروفایل

استاد

• Fluid Dynamics
• Statistical Physics
• Soft Condensed Matter
• +۵ مورد دیگر

Federico Toschi is a Full Professor at Eindhoven University of Technology (TU/e), holding joint appointments in Applied Physics and Mathematics and Computer Science departments. His research focuses on multi-scale transport phenomena, combining statistical physics, fluid dynamics, and computational methods. He leads projects in the 4TU Centre for Multiscale Phenomena and EAISI. Education: PhD in Physics (University of Pisa, 1998) and academic background at Scuola Normale Superiore di Pisa. Interdisciplinary expertise in fluid dynamics turbulence, Lagrangian turbulence, crowd dynamics, and Lattice Boltzmann methods. Recipient of APS Fellow (2015), Euromech Fluid Mechanics Fellow (2012), and Ig Nobel Prize for Physics (2021). Research emphasizes turbulence modeling, pedestrian dynamics, and active matter, with applications in environmental flows and crowd management. His work bridges computational innovations with experimental validations. Recent articles explore kinetic data-driven turbulence modeling, pedestrian flow optimization, and turbulence effects in biological systems. Projects include digital twins for seismicity modeling and rarefied gas dynamics. Teaches fluid mechanics, computational physics, and chaos theory courses. Founded Flow Matters Holding BV, applying research to practical solutions.

• Robotics
• Control Systems
• Multi-Agent Systems
• +۶ مورد دیگر

Herman Bruyninckx is a Part-Time Full Professor at Eindhoven University of Technology (TU/e) in the Mechanical Engineering department, specifically within the Control Systems Technology group and EAISI High Tech Systems initiative. He also serves as a professor (Hoogleraar) at KU Leuven in Belgium. Academic focus on robotics, control systems, and multi-agent coordination Active research in model predictive control , semantic mapping , and dynamic constraint algorithms Recent publications address industrial automation , agro-food robotics , and haptic technology Research Highlights : Developed hybrid decision-making frameworks for multi-agent navigation Innovated swing-free control methods for robotic pick-and-place operations Formulated constrained dynamics algorithms with LQR-Gauss principle integration Created ExoTen-Glove for haptic feedback in virtual environments Collaborative Projects : Coordinated with researchers like René van de Molengraft , Elena Torta , and Koen de Vos Contributed to NWO/TTW FlexCRAFT project for cognitive robotics in agro-food technology

Sofía Caleroمشاهده پروفایل

استاد

• Materials Science
• Computational Physics-Chemistry
• Renewable Energy
• +۷ مورد دیگر

Prof. Sofía Calero is a Full Professor at the Eindhoven University of Technology (TU/e) and Vice Dean of the Department of Applied Physics & Eindhoven School of Education. She leads the Materials Simulation & Modelling group, focusing on computational methods for renewable energy and nanostructured materials. MSc (1995) and PhD (2000), University Complutense of Madrid Marie Curie Fellow (2001–2003), University of Amsterdam Ramón y Cajal Fellow (2004) and Full Professor (2017) at University Pablo de Olavide (Spain) Her research bridges computational physics-chemistry and industrial applications, developing force fields, algorithms, and simulation methods to reverse-engineer material properties. She specializes in adsorption , metal-organic frameworks , zeolites , and molecular simulation , contributing to SDGs like climate action and clean energy. Recent publications focus on halide perovskites , carbon dioxide capture , and nanostructured materials , with software tools like RASPA and iRASPA as key outputs. Articles span Nano Letters , Chem , and Journal of Physical Chemistry C . ERC Proof of Concept Grant (2018) Marie Curie Excellence Award (2005) Fellow of the Royal Society of Chemistry (2024) She has supervised 36 research works and taught courses like Advanced Materials Modelling and Mechanics . Her work involves collaborations with industries and institutions across Europe.

Guy G. Drijkoningenمشاهده پروفایل

دانشیار

• Applied Geophysics
• Seismic Experiments & Modelling
• Seismic Data Acquisition
• +۳ مورد دیگر

Guy G. Drijkoningen is an Associate Professor in Applied Geophysics at Delft University of Technology (TU Delft), Faculty of Civil Engineering and Geosciences. He is actively involved in teaching and research within the Department of Applied Geophysics & Petrophysics. Education: MSc, Delft University of Technology, The Netherlands PhD, Cambridge University, UK Research Focus: His work centers on Seismic Experiments & Modelling , particularly in exploration and shallow-subsurface contexts. Key areas include: Seismic data acquisition on land Continuous seismic monitoring Shallow shear-wave imaging (land and marine) Seismic wave propagation in porous media Current projects leverage advanced sensor networks (e.g., LOFAR), full-waveform inversion for tunnel-boring machines, and novel vibrator technologies. Publications Trend: Recent works (2011–2016) emphasize seismic modeling, inversion techniques, and experimental validation across marine and terrestrial environments. Topics span poroelastic wave theory, ambient-noise interferometry, and innovative seismic source design, reflecting a blend of theoretical and applied geophysics. Scientific Awards: Best-paper award Geophysics 2015 for "A seismic vertical vibrator driven by linear synchronous motors" Professional Memberships & Editorial Roles: Member: Society of Exploration Geophysicists (SEG) Member: European Association of Geoscientists and Engineers (EAGE) Associate Editor: Geophysics Teaching: He teaches undergraduate and graduate courses including Introduction to Geophysics, Reflection Seismology, and specialized PhD-level modules on seismic data analysis.

Ana Lucicمشاهده پروفایل

استادیار

• Machine Learning
• Artificial Intelligence
• Interpretable Machine Learning
• +۶ مورد دیگر

Dr. Ana Lucic is an Assistant Professor at the University of Amsterdam , holding a joint appointment between the Institute for Logic, Language, and Computation (ILLC) and the Informatics Institute . Her research focuses on interpretable machine learning for applications in science and society, with emphasis on Earth system modeling and AI for environmental forecasting . PhD in Explainable Machine Learning (University of Amsterdam, 2022) MSc/BSc in Mathematics (McMaster University, Canada) Former researcher at Microsoft Research AI for Science and Partnership on AI Her recent work includes Aurora , a foundation model for Earth system forecasting published in Nature , and Clifford-Steerable CNNs at ICML 2024. Ana actively mentors PhD students and leads projects in mechanistic interpretability and geospatial machine learning . Scientific awards include top placements in ML competitions. She contributes to open science through reproducibility initiatives and collaborates with AI for climate consortia.

Gabriele Ligaمشاهده پروفایل

استادیار

• Digital Communications
• Information Theory
• Optical Communications
• +۵ مورد دیگر

Gabriele Liga is an Assistant Professor at the Department of Electrical Engineering, Eindhoven University of Technology (TU/e), affiliated with the Signal Processing Systems (SPS) Group. He holds a Marie Curie Eurotech Fellowship focusing on signal shaping techniques for nonlinear optical fiber channels. His academic journey includes a Ph.D. in optical communications from University College London, followed by postdoctoral research in digital signal processing and nonlinearity compensation. Education: B.Sc. in Telecommunications Engineering from Università degli Studi di Palermo (2005), M.Sc. in Telecommunications Engineering from Politecnico di Milano (2011), and a Ph.D. in Optical Communications from University College London (2017). Research Interests: Digital communications, information theory, fiber-optic systems, nonlinearity compensation, channel coding, and multi-user optical communication theory. His work emphasizes achieving transmission limits through signal shaping and advanced signal processing techniques. Projects: Active roles in NESTOR (Next-gen optical networks), QuNEST (quantum communication security), Fun-NOTCH (nonlinear optical channel fundamentals), and SSTOC (signal shaping tailored to optical channels). Collaborations span institutions globally, focusing on optical fiber communication challenges. Awards: 2023 ACP/POEM Best Student Paper Award and 2019 OECC Best Paper Award. Serves as a reviewer for IEEE journals and OSA publications. Labs/Teams: Core member of the SPS Group and involved in interdisciplinary projects blending theory and experimental validation.

L.J. Sluysمشاهده پروفایل

استاد

• Computational Mechanics
• Computational Mechanics of Materials
• Modelling of Failure Processes
• +۱۲ مورد دیگر

Professor L.J. Sluys is a Full Professor and Chair of Computational Mechanics at the Faculty of Civil Engineering and Geosciences, Delft University of Technology (TU Delft). He has been a leading figure in computational mechanics since 1999, heading the Computational Mechanics group and serving as head of the Department of Materials, Mechanics, Management and Design (3MD) from 2018 to 2024. His research is centered on the computational modeling of material behavior, particularly focusing on failure processes and high-performance materials. His research interests include computational mechanics of materials, modeling of failure and fracture processes, multi-scale methods, and the computational modeling of high-performance materials such as composites and concrete. He employs advanced numerical techniques including the finite element method, extended finite element method (XFEM), level-set methods, and cohesive zone modeling to simulate complex mechanical behaviors under static and dynamic loading conditions. His work spans civil, mechanical, and materials engineering domains, with applications in infrastructure, energy, and sustainable materials. The recent publications highlight a strong trend in modeling fracture, fatigue, and degradation in heterogeneous materials such as composites, concrete, and geological formations. His work integrates multi-physics and multi-scale approaches, often coupling mechanical, thermal, and chemical effects. There is a consistent focus on numerical robustness, model validation, and the development of adaptive computational frameworks for simulating progressive damage and failure. Research Fellow of the Netherlands Academy of Arts and Sciences (KNAW) Professor Sluys has taught core courses such as Introduction to the Finite Element Method and Computational Methods in Non-linear Solid Mechanics for over a decade, indicating a strong commitment to academic education. He has supervised numerous students, though specific names are not listed in the provided texts. He leads an active research group in computational mechanics, contributing to both fundamental and applied research in solid mechanics. His work involves collaboration with international institutions and industry partners, particularly in the areas of infrastructure durability and advanced materials.

Sirui Liمشاهده پروفایل

پژوهشگر

• CO2 Conversion
• Plasma Catalysis
• Carbon Capture
• +۵ مورد دیگر

Sirui Li is a Postdoctoral Researcher in the Department of Chemical Engineering and Chemistry at Eindhoven University of Technology, specializing in plasma-based technologies for sustainable chemical processes. Their research focuses on carbon capture and utilization, plasma catalysis, and reactor design for CO 2 conversion and nitrogen fixation. Research interests center on plasma-assisted CO 2 conversion , with key areas including: Plasma-sorbent systems for simultaneous CO 2 capture and conversion Gliding arc and DBD reactor design for NO x synthesis and methane conversion Techno-economic analysis of plasma-based sustainable processes Dielectric materials and nanoparticle synthesis for catalytic applications Recent publications demonstrate a clear trend toward integrated plasma-reactor systems for carbon management, with emphasis on process intensification, thermal effects analysis, and scalability. The work bridges fundamental plasma chemistry with industrial application feasibility, particularly in renewable energy integration and fertilizer production. Award highlights include: Baldur Eliasson Award (2022) Best oral presentation award for 'Plasma-sorbent system for CO 2 capture and conversion' (2022) IEEE NPSS Young Professional Travel Grant (2024) Li actively contributes to major research projects including PLACHEM (plasma-assisted CO 2 conversion), GICO (gasification with CO 2 capture), and LEAP-Agri (on-site fertilizer production), while serving as guest editor for Frontiers of Chemical Science and Engineering and participating in international symposia on plasma technology.