جست‌وجوی استاد و پژوهشگر

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.

Fiona Sloothaakمشاهده پروفایل

استادیار

• Stochastic Operations Research
• Network Theory
• Cascading Failures
• +۶ مورد دیگر

Fiona Sloothaak is an Assistant Professor at Eindhoven University of Technology (TU/e), affiliated with the Department of Mathematics and Computer Science, specializing in Stochastic Operations Research. She holds the Eurandom Assistant Professor title and contributes to the Stochastic Operations Research group. Her research focuses on cascading failures in complex systems, power grids, battery swapping networks, and stochastic processes. Education: Fiona earned a PhD in Stochastic Operations Research from TU/e in 2020 and completed a Master's in Mathematics (2015). Her doctoral thesis, Criticality in power networks: a probabilistic approach , explores cascading failures in power systems. Research Interests: Fiona’s work addresses systemic risk in infrastructure systems, including power grids and transportation networks. She investigates cascading failure dynamics, load balancing in battery swapping stations, and resource pooling strategies. Her studies often employ probabilistic modeling and queueing theory. Key Projects: She co-authored the MARCONI project (2019–2022), focusing on integrated planning for maritime logistics and service systems. This involved optimizing supply chain resilience and remote control tower operations. Scientific Award: Applied Probability Trust Prize (2020) Teaching: Courses include Stochastic Networks, Insurance and Credit Risk, and Probability and Stochastics 1. Grants: MARCONI project funding for maritime logistics optimization. Labs/Teams: Active in TU/e’s Stochastic Operations Research group and Eurandom institute. Collaborations span network topology analysis and interdisciplinary systems research.

Bert de Vriesمشاهده پروفایل

استاد

• Bayesian Machine Learning
• Signal Processing
• Biomedical Applications
• +۳ مورد دیگر

Bert de Vries is a Professor at the Signal Processing Systems Group at Eindhoven University of Technology (TU/e), where he has been employed since January 2012. He maintains a dual career, also working at GN Hearing in the hearing aids industry since April 1999, where he holds both research and managerial roles. His academic journey began at TU/e, where he earned his MSc in Electrical Engineering in 1986, followed by a PhD from the University of Florida in 1991. Between 1992 and 1999, he worked at Sarnoff Research Center in Princeton, NJ, contributing to diverse signal and image processing projects. Professor de Vries's research centers on Bayesian Machine Learning, with particular focus on the Free Energy Principle and its applications to engineering problems. His work bridges theoretical neuroscience with practical signal processing systems, especially in biomedical applications. He directs the BIASlab research team at TU/e, which develops probabilistic programming tools including RxInfer.jl, ForneyLab.jl, GraphPPL.jl, ReactiveMP.jl, and Rocket.jl. His research spans active inference, variational message passing, probabilistic programming, and Bayesian neural networks, with applications ranging from hearing aids to multi-agent systems. Analysis of his recent publications reveals a strong trend toward practical implementations of Bayesian inference frameworks, particularly through Julia-based probabilistic programming tools. His work shows increasing focus on active inference applications, message passing algorithms, and the intersection of Riemannian geometry with probabilistic modeling. The research demonstrates consistent progression from theoretical foundations toward real-world engineering applications, particularly in biomedical signal processing and autonomous systems. Professor de Vries teaches a graduate-level course on Bayesian Machine Learning at TU/e and actively contributes to open-source software development through his GitHub profile (bertdv), with recent activity as recent as August 2025. His research team has developed several influential probabilistic programming libraries that have gained significant attention in the machine learning community. The BIASlab research group continues to advance the state of the art in Bayesian inference methods with applications in hearing technology, robotics, and signal processing.

Alessandro Bombelliمشاهده پروفایل

استاد

• Operations Research
• Logistics
• Air Transport Management
• +۵ مورد دیگر

Alessandro Bombelli is a Professor at Delft University of Technology (TU Delft) in the field of Aerospace Engineering, Operations & Environment . His research bridges operations research, logistics, and transportation systems, with a focus on air transport, maritime logistics, and optimization frameworks. He actively collaborates with colleagues like I.A. Parmaksizoglou, A. Sharpanskykh, and B. Atasoy to innovate transport solutions. Recent research emphasizes multimodal collaboration in marine terminals, air cargo resilience during disruptions (e.g., extreme weather, pandemics), and interactive learning for optimization. His work spans technical domains like vehicle routing , distributed constraint optimization , and complex network theory , addressing real-world challenges in transport efficiency. Scientific Awards : TU Delft Educator of the Year 2023 Open Education Stimulation Fund 2022 Bombelli contributes to open-access publications and datasets, including the Air Cargo Transport Network (ACTN) Dataset , demonstrating his commitment to accessible research. His recent articles highlight interdisciplinary approaches to logistics and optimization, with applications in both aerial and maritime domains.

R.R. Negenbornمشاهده پروفایل

استاد

• Transport Engineering
• Logistics
• Autonomous Vessels
• +۷ مورد دیگر

Professor R.R. Negenborn is affiliated with Delft University of Technology, specializing in Transport Engineering and Logistics. His research spans autonomous shipping, inland waterway transport, and sustainable logistics solutions. Current projects: PATH2ZERO (Zero-Emission Inland Shipping), AUTOBarge (European Training Network), READINESS (Adaptable Ship Designs), and NOVIMOVE (Innovative Freight Transport). Key research areas: control systems, vessel dynamics, optimization, collision avoidance algorithms, and energy-efficient marine technologies. His editorial roles include contributions to Springer publications and Lecture Notes in Computer Science . Collaborations highlight expertise in integrating automated vehicles with conventional transport systems and advancing resilient inland shipping frameworks.

• Discrete Element Method
• Granular Materials
• Transport Engineering
• +۵ مورد دیگر

D.L. Schott serves as a Professor in the Department of Mechanical Engineering, Transport Engineering and Logistics at Delft University of Technology, specializing in computational modeling of granular systems and transport infrastructure. His research integrates Discrete Element Method (DEM) simulations with emerging AI techniques to solve complex engineering challenges in offshore energy, material handling, and maritime operations. His primary research focuses on particle-scale mechanics in industrial and marine environments, with significant contributions to scour protection systems for offshore wind foundations, hopper discharge dynamics, and metamaterial design. Recent work demonstrates a strategic shift toward AI-enhanced simulation frameworks, particularly using transfer learning for multi-component segregation modeling and dual-regime approaches for time consolidation phenomena. This reflects growing industry demand for computationally efficient solutions in bulk material processing and offshore construction. Professor Schott maintains active industry collaborations, evidenced by 19 datasets on hopper discharge mechanics and press coverage of innovative grab unloader designs with Nemag. His 12 supervised student projects and 26 recent activities—including 22 conference presentations in 2025—highlight sustained engagement in geotechnical and transport engineering communities. Current research trajectories emphasize resilient maritime systems and AI-driven optimization of industrial material flows.

Wouter Kouwمشاهده پروفایل

استادیار

• Probabilistic Machine Learning
• Variational Bayesian Inference
• Active Inference
• +۶ مورد دیگر

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 .

Sjoerd W. Rienstraمشاهده پروفایل

استاد

• Aeroacoustics
• Fluid Mechanics
• Duct Acoustics
• +۳ مورد دیگر

Roles and Affiliations : Sjoerd W. Rienstra is a Professor at Eindhoven University of Technology (TU/e), affiliated with the Department of Aerospace Engineering and the CEAS-ASC (Centre for Aeroacoustics and Acoustics). His work focuses on aeroacoustics, duct acoustics, and fluid dynamics. Research Interests : His research spans analytical and numerical methods in aeroacoustics, including duct mode analysis, shear flow effects, acoustic liners, and noise control. He has contributed to understanding sound propagation in complex geometries and boundary layer interactions. His work also extends to interdisciplinary areas like climate science (ice-shelf melt dynamics). Publications and Trends : Rienstra's recent work emphasizes computational methods, asymptotic solutions, and experimental validations. He has authored/co-authored over 100 publications, including influential papers on Pridmore-Brown modes, duct acoustics, and fluid dynamics. His contributions to the Journal of Sound and Vibration and Applied Mathematical Modelling highlight his expertise in wave propagation and numerical techniques. Labs and Teams : Collaborations include the CEAS-ASC, where he leads research on aeroacoustic modeling and noise reduction in aerospace systems.

L. Peternelمشاهده پروفایل

پژوهشگر

• Human-Robot Interaction
• Robotics
• Rehabilitation Robotics
• +۴ مورد دیگر

L. Peternel is a Robotics researcher at Delft University of Technology's Faculty of Mechanical, Maritime and Materials Engineering, specializing in Human-Robot Interaction and Rehabilitation Robotics. With 56 research outputs including conference contributions, journal articles, and patents, Peternel leads cutting-edge work in impedance control, teleoperation, and collaborative robotics applications spanning medical rehabilitation, off-Earth habitat construction, and service robotics. Research focuses on developing advanced control frameworks enabling natural human-robot collaboration. Key areas include impedance-based teleoperation systems, human motor control-inspired co-manipulation strategies, and biomechanics-aware robotic physiotherapy. Recent work explores quadruped navigation, supermarket service robots with LLM interfaces, and off-Earth habitat construction systems that integrate computer vision with human-robot teamwork. Publications demonstrate strong emphasis on practical implementations with real-world impact across medical, industrial, and extraterrestrial environments. Article trends reveal consistent focus on physical human-robot interaction mechanisms, particularly impedance control methodologies and safety-critical applications. The research portfolio spans rehabilitation robotics (shoulder therapy systems), collaborative construction (off-Earth habitats), and service robotics (supermarket assistants), with increasing integration of AI and computer vision components in recent years. Best Paper Award at FICTA 2024 for Computer Vision- and Human-Robot Interaction-Supported Assembly Finalist Best Interactive Paper Award at Humanoids 2023 for robotic shoulder rehabilitation work Peternel leads the Rhizome project developing autonomous systems for off-Earth habitat construction and collaborates extensively across disciplines including biomechanics, computer science, and aerospace engineering. Media coverage including the Dutch press feature "Een robot als collega" highlights real-world impact of this research. Supervised work includes PhD candidates in robotics, with ongoing projects focusing on patient-centered rehabilitation systems and autonomous construction robotics for space applications.

Den Toonderمشاهده پروفایل

استاد

• Microfluidics
• Biomedical Engineering
• Microactuators
• +۳ مورد دیگر

Den Toonder is a Professor in the Department of Mechanical Engineering at Eindhoven University of Technology (TU/e), leading the Group Den Toonder focused on microfluidics and biomedical device development. His research spans microactuators, organ-on-chip systems, and applications such as cancer diagnostics and glaucoma implants. He oversees a team of 37 researchers and has supervised over 65 student theses, emphasizing collaborative projects with biomedical and clinical groups. His work contributes to UN Sustainable Development Goals through innovations in healthcare and sustainable technologies. Research interests include microfluidic actuation systems, magnetic bead actuation, and biomimetic designs. Notable projects include developing a minimally invasive glaucoma implant and organ-on-chip models for cancer studies. His lab integrates fabrication techniques like femtosecond laser machining and employs advanced sensors for real-time diagnostics. Publications highlight advancements in sweat-based health monitoring, microfluidic mixing via artificial cilia, and tissue barrier sensor chips. His team’s work bridges engineering and medicine, with applications in non-invasive diagnostics and regenerative medicine.

• Coastal Engineering
• Mangrove Restoration
• Sediment Dynamics
• +۷ مورد دیگر

U.S.N. Best is a researcher at the Delft University of Technology , affiliated with the College of Civil Engineering & Geosciences and the Department of Coastal Engineering . Their work spans coastal engineering, structural mechanics, and marine systems. Primary Focus : Coastal resilience (mangrove restoration, sediment dynamics, wave attenuation in Guyana's mudflats). Secondary Focus : Fatigue analysis, computational mechanics, and hydrodynamic modeling for marine structures. Recent research includes multidisciplinary studies on mangrove ecosystem services and advanced numerical methods for structural and fluid-structure interactions. Collaborative datasets highlight fieldwork in Guyana.

S. Balakrishnanمشاهده پروفایل

استادیار

• Critical infrastructure resilience
• Infrastructure resource allocation
• Disaster risks to infrastructure systems
• +۴ مورد دیگر

S. Balakrishnan is an Assistant Professor at the Faculty of Technology, Policy and Management , Delft University of Technology (TU Delft), specializing in Transportation and Logistics . His work focuses on infrastructure resilience, interdependency modeling, and socio-economic impacts of infrastructure systems under extreme climate events. Ph.D.: Civil Engineering, University of Texas at Austin (2020) M.S.: Civil Engineering, Indian Institute of Technology Madras (2016) B.Tech: Civil Engineering, University of Kerala (2012) Research interests include: Quantifying resilience in interdependent infrastructure networks Climate change adaptation in urban systems Stakeholder coordination in disaster recovery Cyber-physical risks in infrastructure His recent publications emphasize simulation frameworks and machine learning for resilience prediction, with applications to water distribution, port operations, and urban traffic systems. Scientific Awards: Best Oral Presentation Award, Nov 2021 Balakrishnan has collaborated with institutions like the Singapore ETH Centre and University of Oxford, contributing to projects funded by Texas Department of Transportation and Singapore's National Research Foundation. His work aligns with UN Sustainable Development Goal 11 (Sustainable Cities and Communities).

J.F.J. Pruynمشاهده پروفایل

پژوهشگر

• Marine Engineering
• Energy Systems
• Operations Research
• +۳ مورد دیگر

J.F.J. Pruyn is a researcher at Delft University of Technology , specializing in Ship Design, Production and Operations . His work bridges marine engineering with optimization techniques, focusing on energy systems and sustainable shipping solutions. Key Research Areas : Ship design, methanol power systems, energy transition, climate scenario modeling, and resource-constrained project scheduling. His recent projects include PATH2ZERO (zero-emission inland shipping) and READINESS (robust ship designs for uncertain transitions). He has contributed datasets to open science platforms and participated in conferences and workshops on environmental policy and maritime engineering.

• Discrete Element Method (DEM) simulations
• Granular material dynamics
• Offshore geotechnics
• +۶ مورد دیگر

Prof. D.L. Schott is a Professor in Transport Engineering and Logistics at TU Delft. His research focuses on granular material dynamics, DEM-based simulations, metamaterial design, and maritime engineering applications. He leads projects involving offshore geotechnics, AI-driven modeling frameworks, and sustainable fuel systems for marine vessels. His work spans academic collaborations across Europe and Asia, with over 208 peer-reviewed publications and 19 datasets. Key contributions include validated DEM frameworks for scour protection systems, agent-based resilient vessel mission frameworks, and optimization strategies for metamaterials under impact loading. Schott actively participates in international conferences and interdisciplinary initiatives like the ISFOG symposium. He co-created datasets on hopper discharge dynamics and advised 12 graduate students. His research bridges computational mechanics with practical industrial challenges in bulk handling, energy systems, and smart maritime logistics. Education details are not explicitly stated, but his academic rank and extensive publications indicate advanced qualifications in mechanical engineering. Research interests emphasize integrating AI with granular flow simulations, structural resilience, and sustainable shipping solutions. Recent article trends highlight advancements in surrogate modeling techniques, metamaterial applications, and climate-responsive shipping activity projections. Scientific awards are not mentioned in the provided texts. Grants and collaborations are evident through his extensive publication and dataset records, including partnerships with companies like Nemag for innovative grab design. His lab activities involve large-scale industrial equipment co-simulations and experimental validation of numerical models.

• Transport Logistics
• Operations Research
• Container Shipping
• +۳ مورد دیگر

S. Fazi is a researcher at the Department of Technology, Policy and Management , Delft University of Technology. Her work focuses on transport logistics , operations research , and container shipping , with particular attention to offshore wind energy , multimodal networks , and freight transportation . Transport & Logistics network design Operations Research for optimization Offshore wind farm logistics Recent research trends include multimodal hub location problems , container drayage optimization , and collaborative air cargo frameworks . She has contributed to offshore wind turbine substructure installation strategies and dry-port logistics through data-driven models and decision support systems. Scientific awards : NWA - ORC 2022 - Onderzoek op Routes door Consortia (2023) Open Education Stimulation Fund 2022 (2023) Her work spans freight network design , maritime container stowage , and resource sharing in wind energy maintenance , often involving large-scale optimization algorithms and collaborative frameworks.