جستجوی استاد راهنمای دانشگاهی

Claudia Lopez Camara is an Assistant Professor at the Mechanical Engineering Department of Eindhoven University of Technology (TU/e) , appointed in January 2024. Previously, she held postdoctoral positions at the University of Duisburg-Essen (2021-2023) and completed her Ph.D. in Numerical Combustion at the University of California, Irvine (2020). Education : BSc in Chemical Engineering (University Rovira i Virgili, Spain), MSc in Nanotechnology and Nanoscience (University Rovira i Virgili) Her research focuses on gas-phase synthesis of nanomaterials , particularly graphene and mesoporous silica nanoparticles for sensors and energy applications . Current work explores experimental methods including flame, plasma, and hot-wall reactors for nanomaterial production. Recent publications highlight her expertise in nanoparticle morphology control and composite sensor development , with 10 Scopus-indexed works between 2015-2025. Key collaborations exist with institutions including KAUST, LLNL, and UW-Madison . Scientific Awards & Funding Undergraduate Mobility Balsells Fellowship Grant of Excellence Catalunya-La Pedrera NSF Intern Fellowship DFG research unit FOR2284 & SPP2289 International Max Planck Research School SurMat As Principal Investigator of the Group López Camara at EIRES Research , she leads projects involving scalable aerosol-based synthesis and self-folding graphene mechanisms . Her work combines numerical modeling with experimental validation to advance nanomaterials engineering.

• Nanomaterials synthesis
• Gas-phase reactor engineering
• Plasma and flame synthesis
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Cristian Picioreanu is a Full Professor at the Biological and Environmental Science and Engineering Division of King Abdullah University of Science and Technology (KAUST). His research focuses on numerical modeling of interactions between physical, chemical, and biological processes, particularly in environmental and biotechnological applications. Research Areas: Biofilms, Membrane Bioreactors, Computational Fluid Dynamics, Multi-scale Modeling, Water Reuse His work addresses challenges in biofouling, bioclogging, and microbial fuel cells through computational approaches. Recent publications highlight collaborations with experts in membrane technology and environmental engineering, emphasizing hydrodynamic and mechanical property analyses of biofilms. Key affiliations include TU Delft's Environmental Biotechnology group.

• Environmental Science and Engineering
• Chemical Engineering
• Biotechnology
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Prof. Frits C.R. Spieksma is a full professor in the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e) , where he leads research within the Combinatorial Optimization Group. He has held academic positions at Maastricht University, KU Leuven, and the University of British Columbia, and has been at TU/e since 2018. Education: M.Sc. in Econometrics, University of Groningen (1987) Ph.D. in Operations Research, Maastricht University (1992) Research Focus: His work lies at the intersection of combinatorial optimization and real-world applications . Key themes include: Scheduling and clustering problems, especially in sports tournaments Organ allocation optimization for Eurotransplant Assignment and transportation problems Approximation algorithms and graph-theoretic optimization Scientific Service & Leadership: Founder and ex-Chair, EURO Working Group OR in Sports Member, Steering Committees of MAPSP and MathSports International President, EURO (Association of European Operational Research Societies) Former Vice-President, IFORS Former President, Belgian Society of Operations Research (ORBEL) Editorial Boards: Associate Editor, 4OR (2015–present) Associate Editor, Journal of Quantitative Analysis in Sports (2014–present) Associate Editor, Operations Research Letters (2008–2024) Former Associate Editor, INFORMS Transactions on Education , OMEGA , Computers & Operations Research , IIE Transactions , Naval Research Logistics PhD Supervision & Mentoring: He has supervised more than 25 PhD theses at KU Leuven and TU/e, many of whom now hold academic positions worldwide. Conference & Workshop Organisation: Recent leadership roles include General Chair of IPCO 2022 (Eindhoven), organiser of Benders Day 2024 , and co-organiser of the Dagstuhl Seminar on Fairness in Scheduling and Resource Allocation (March 2025).

• Combinatorial Optimization
• Operations Research
• Scheduling
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Dengpeng Huang is an Assistant Professor specializing in Artificial Intelligence and Robotics within the field of Elastomer Technology and Engineering . His work bridges computational modeling with advanced materials, focusing on applications in smart materials and mechanical systems. Research Interests: Development of AI-driven models for predicting elastomer properties Multiscale analysis of rubber composites Electromechanical coupling in dielectric elastomer actuators Meshfree methods for metal cutting and chip formation Ultra-precision polishing of optical surfaces Recent Trends: His 2024–2025 publications emphasize data-driven modeling of rubber's viscoelastic behavior, multiscale analysis of composites, and CNN-based approaches for material characterization. Earlier work (2014–2022) explores tool path optimization, beam modeling, and computational machining. Scientific Recognition: Holds an h-index of 5 according to Scopus citations, with recognition as an AI and robotics expert in the service industry. Advising & Collaboration: Collaborates with researchers like Anna Blume, Evgeny Karaseva, and Tim Bor on elastomer composites. Supervised at least one academic work, though specific students are not named in the provided data. Labs & Teams: Affiliated with simulation and robotics teams in the smart materials sector, likely within an advanced materials or mechanical engineering research group.

• Artificial Intelligence
• Robotics
• Materials Science
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Yanqiu Huang is an Assistant Professor in Pervasive Systems, focusing on interdisciplinary research in Internet of Things (IoT), cyber-physical systems, embedded systems, wireless communication, and optimization. Their work addresses resource-constrained networks, emphasizing energy efficiency and collaborative algorithms for IoT devices. Research Interests Design of energy-efficient algorithms for IoT networks Integration of wireless communication and control systems Edge AI and sensor technologies for intelligent transport Recent Publications Key contributions include advancements in Bluetooth Low Energy (BLE) discovery, DNN task allocation for edge computing, and cyclist behavior prediction via IMU data. Research spans environmental monitoring, industrial ventilation, and smart mobility solutions like connected bicycles. Scientific Awards Best Poster Award: DNN Task Allocation for Edge-Aided IoT (2023) Best Poster Award: Smart Connected Bikes (2023) Best Presentation Award (2025) Activities Active in organizing and participating in international conferences (PerVehicle 2024/2025), hosting academic visitors (Koojana Kuladinithi, Konrad Fuger), and delivering invited talks on privacy-preserving crowdsensing.

• Internet of Things (IoT)
• Cyber-Physical Systems
• Embedded Systems
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Martin Schmettow is an Assistant Professor at the Digital Society Institute, affiliated with the Cognition, Data and Education school. His research spans interdisciplinary domains including human-AI interaction, usability evaluation, and applications in healthcare and robotics. Usability & User Experience Human-AI Interaction Neurological Clinical Research Ecological Remediation Recent publications focus on chatbot usability validation, postictal recovery analysis, and ant bioturbation impacts. He has developed multilanguage psychometric scales and contributed to Bayesian statistical methodologies in design research. Collaborations highlight intersections between simulation technology, wearable devices, and medical informatics. Key research areas evident from publications include: Usability engineering for high-risk systems Human factors in robotic surgery training Bayesian modeling applications Neurological recovery post-ECT studies Ecological rehabilitation strategies Human-robot interaction dynamics

• Usability
• Human-Computer Interaction
• User Experience
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Dr. Saber Darmoul is an Associate Professor specializing in Systems Engineering and Multidisciplinary Design. His research bridges artificial intelligence with industrial applications, focusing on cyber-physical production systems, operational resilience, and smart transportation. He actively explores knowledge representation, reinforcement learning, and agent-based modeling to address complex system challenges. Key Research Interests: Operational resilience, AI in manufacturing, multi-agent systems, smart mobility Technical Expertise: Ontology modeling, simulation platforms, immune-inspired control architectures His recent publications (2025-2019) demonstrate a consistent focus on integrating artificial immune systems into control architectures for transportation and manufacturing. Notable trends include: Development of knowledge-based systems for dynamic reconfiguration Application of multi-criteria decision frameworks in production environments Advancing predictive maintenance strategies through distributed systems Exploring 6G system-of-systems engineering While no explicit awards or student advisement information appears in available records, his 15 most recent publications reflect sustained academic productivity and evolving focus from foundational control systems (2017-2019) to advanced applications in Industry 4.0 (2020-2025).

• Artificial Intelligence
• Systems Engineering
• Cyber-Physical Production Systems
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Christoph Brune is a Full Professor at the University of Twente , affiliated with the Digital Society Institute and TechMed Centre . His research bridges Artificial Intelligence , Deep Learning , and Medical Imaging with applications in Robotics and Computational Fluid Dynamics . Keywords: Machine Learning , Network Analysis , Optimal Transport , Medical Image Segmentation Research Trends : Recent publications focus on physics-informed neural networks , equivariant learning for vascular modeling, and operator learning for PDE-constrained problems. His work emphasizes geometric deep learning , implicit neural representations , and robust AI for clinical settings. Scientific Awards : CMI-NEN seed-money award (2022) for medical imaging innovation Collaborative Networks : Active in graph neural networks , optimal transport , and Barron space theory . Key collaborations include Zenodo dataset contributions and ArXiv preprints with multidisciplinary teams in AI, medicine, and engineering.

• Machine Learning
• Deep Learning
• Computer Vision
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Fabian Akkerman is a researcher at the Digital Society Institute within the Industrial Engineering & Business Information Systems department at the University of Twente . His work bridges theoretical advancements in machine learning with practical applications in logistics, energy sustainability, and transportation systems. Primary Affiliation : University of Twente, Industrial Engineering & Business Information Systems Research Focus : Artificial Intelligence, Reinforcement Learning, Autonomous Systems, and Sustainable Logistics Fabian's research specializes in sequential decision-making problems, particularly in dynamic and stochastic environments. A key area of his contributions lies in applying reinforcement learning and optimization techniques to address challenges in: Vehicle routing with uncertain demand Inventory management and warehouse operations Time slot pricing for delivery services Smart transportation and freight logistics Stochastic modeling for supply chain resilience Industry 4.0 adoption in production systems His work demonstrates a strong emphasis on developing algorithmic frameworks (e.g., DynaPlex) that combine statistical modeling with real-world implementation. Recent publications highlight applications in autonomous vehicles, intelligent transport systems, and circular economy strategies. Scientific Awards : 2024 Transportation Science Meritorious Service Award 2025 2nd Place in ISIR Research Challenge for Production-Inventory Planning at ASML

• Artificial Intelligence
• Machine Learning
• Autonomous Agent Systems
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Bruno F. Santos is an Assistant Professor in Airline Operations at Delft University of Technology's Faculty of Aerospace Engineering. His research bridges theoretical optimization methods with practical airline operations challenges, focusing on making aviation systems more efficient and sustainable through data-driven approaches. Dr. Santos's research interests center around aircraft maintenance optimization , predictive maintenance using AI , stochastic modeling for airline operations , and strategic planning for sustainable aviation . His work applies advanced computational techniques including Bayesian frameworks and deep reinforcement learning to solve real-world problems in the aviation industry. A key focus is transforming traditional fixed-schedule maintenance into condition-based approaches that respond to actual aircraft system health. His recent publications demonstrate a strong trajectory in high-impact journals, with a focus on counterfactual explanations for remaining useful life estimation, deep reinforcement learning for airport operations, and multidisciplinary coupling for hybrid-electric aircraft design. These works collectively address the critical challenge of making aviation more efficient, sustainable, and cost-effective through digital transformation. TRA VISIONS 2022 Senior Researcher Award Airborne AIAA Electrified Aircraft Technology Technical Committee Best Paper Award (2023) AIAA Software Best Paper Award (2024) Dr. Santos leads significant research initiatives including the €6.8 million ReMAP project, which successfully demonstrated through a six-month trial at KLM that AI models can predict aircraft system health and optimize maintenance scheduling. This project involved collaboration with multiple European universities and industry partners. His editorial roles for Transportation Research Procedia and Transport Policy demonstrate his standing in the academic community. Dr. Santos actively translates research into practical applications, with media coverage highlighting how his work can save airlines hundreds of millions while improving operational efficiency. His Aircraft Maintenance and Operations Research Group focuses on developing adaptive maintenance planning systems that use real-time data to optimize maintenance scheduling, reducing unnecessary maintenance while preventing system failures. The group's work represents a significant shift from traditional fixed-schedule maintenance to condition-based approaches that respond to actual aircraft system health.

• Aircraft Maintenance
• Airline Operations
• Predictive Maintenance
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Gerwin Hoogsteen is an Assistant Professor at the University of Twente, affiliated with the Computer Architecture for Embedded Systems chair. He focuses on smart grids, cyber-physical systems, and applying theoretical research in field-tests. PhD in Decentralized Energy Management (2017, University of Twente) His research integrates machine learning , distributed coordination , and cybersecurity into smart grid optimization. Recent work emphasizes multi-objective optimization for EV charging hubs, energy community resilience, and congestion management. Key article trends include EV charging algorithms , decentralized control , and hybrid storage systems . He contributes to UN SDGs like Climate Action and Affordable Energy . Founder of DEMKit and ALPG open-source software Collaborator in EU projects (SUSTENANCE, SERENE, LocalRES)

• Smart Grids
• Energy Management
• Cyber-Physical Systems
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F. Mulder is a Lecturer in the Department of Computer Science & Engineering at the School of Electrical Engineering, Mathematics and Computer Science. His work focuses on educational technology, particularly in peer and self-assessment systems, as demonstrated in his 2021 case study on grading 600+ students. Research Trends : Recent publications (2024-2025) highlight expertise in electrochemical systems, energy storage, and materials science, with applications in lithium-ion batteries, CO2 conversion, and hybrid battery-electrolyzers. Technical Focus : Specializes in 3D electrode modeling, solid-state electrolytes, and optimizing mass transport in electrochemical devices.

• Software Engineering Education
• Peer Assessment
• Self-Assessment
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Paula Smith serves as Lector (Professor) at Inholland University of Applied Sciences, leading the Empowerment & Professionalization Social Domain research group. Her work bridges academic research and practical social work through collaborations with organizations including HvO-Querido and Amsterdam University of Applied Sciences, focusing on translating findings into actionable professional resources. Her research concentrates on: Network support systems for homeless individuals in urban environments Youth and family dynamics, particularly financial stress interventions Community development and citizen participation frameworks Empowerment strategies for vulnerable populations Recent publications reveal a strong emphasis on practical implementation, with the 2024 'Social Network First?' project demonstrating how urban context shapes effective network support for homeless clients. This work identifies concrete methods for professionals to involve family members, navigate organizational barriers, and adapt interventions to specific city environments through evidence-based protocols. Supported by active research funding, Smith's projects generate tangible outputs including training materials, podcasts for knowledge dissemination, and implementation guides used by social professionals. The research maintains direct relevance to practice through ongoing collaboration with frontline organizations and municipal services. The Empowerment & Professionalization Social Domain Lectorate functions as an innovation hub where research directly informs social work practice. Current initiatives focus on developing context-sensitive network activation strategies for homeless services, with findings rapidly translated into professional development resources that address immediate challenges in urban social care settings.

• Homelessness and Network Support
• Youth and Family Studies
• Social Work Practice
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Prof. Leo Veldhuis serves as Full Professor of Flight Performance and Propulsion (FPP) at the Faculty of Aerospace Engineering, Delft University of Technology. His research focuses on developing sustainable aviation solutions through improved aircraft aerodynamics and propulsion systems integration. Veldhuis leads multiple European research projects aimed at reducing aviation's environmental impact through innovative aircraft design approaches. His primary research interests include aircraft aerodynamics, propulsion systems, sustainable aviation, electric flight, hybrid propulsion, distributed propulsion, and novel aircraft design. Veldhuis has specialized expertise in propeller propulsion systems, having conducted PhD research on propellers and propeller-wing interaction. He advocates for a transition toward electric and hybrid propulsion systems, recognizing both the potential and challenges of battery technology for aviation applications. His work addresses the critical need for more energy-efficient aircraft designs as the aviation sector continues to grow at approximately 5% annually worldwide. Veldhuis and his team are actively engaged in three major projects focusing on hybrid and electric propulsion systems. His research explores distributed propulsion concepts where electric engines are strategically placed across the aircraft rather than using traditional jet engines mounted on wings. He also investigates the resurgence of propeller propulsion, which offers approximately 30% better fuel efficiency compared to jet propulsion. Veldhuis collaborates extensively with industry partners including Royal NLR (Netherlands Aerospace Centre), Airbus, and companies developing small electric aircraft. Veldhuis has contributed to significant national initiatives, including the Dutch government's action plan on hybrid electric flying. He maintains an active research agenda examining the entire spectrum of sustainable aviation solutions, from technological innovations to policy recommendations. His work recognizes that technological developments alone cannot keep pace with aviation's growth, advocating for a broader societal approach to mobility that considers when and why air travel is necessary.

• Aircraft Aerodynamics
• Propulsion Systems
• Sustainable Aviation
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