جستجوی استاد راهنمای دانشگاهی

Haneen Farahمشاهده پروفایل

دانشیار

• road infrastructure design
• road user behavior
• traffic safety
• +۷ مورد دیگر

Dr. Haneen Farah is an Associate Professor in the Department of Transport & Planning at Delft University of Technology and co-director of the Traffic and Transportation Safety Lab. She also serves as head of the Traffic Systems Engineering section. Her research focuses on road infrastructure design, road user behavior, and traffic safety, integrating transportation engineering, human factors, and econometrics. Prior to TU Delft, she was a postdoc at KTH Royal Institute of Technology and earned her M.Sc. and Ph.D. in Transportation Engineering from the Technion-Israel Institute of Technology. Her work includes national/international projects like SAMEN (mixed automated/human traffic implications), AfroSAFE (road safety in Africa), and XCARCITY (sustainable city mobility). She teaches undergraduate and graduate courses on road design and traffic safety, including online programs for low/middle-income countries. Farah supervises multiple PhD and Master students in her research areas, contributing to over 50 peer-reviewed publications. Key research themes include infrastructure design for automated vehicles, driver behavior modeling, cyclist safety, and policy implementation of the Safe System approach. Her interdisciplinary approach bridges engineering and psychology to enhance traffic safety and efficiency through advanced analytics and simulation models.

Ron H.J. Peerlingsمشاهده پروفایل

دانشیار

• Micromechanics
• Micro-plasticity
• Multiscale modelling
• +۷ مورد دیگر

Ron H.J. Peerlings is Associate Professor in the Department of Mechanical Engineering at Eindhoven University of Technology (TU/e) , where he leads the Mechanics of Materials research group. Promoted to Associate Professor in 2007 after joining as Assistant Professor in 2000, he has built an extensive portfolio in theoretical and computational mechanics of materials. Education: PhD (1999) – Eindhoven University of Technology, thesis: Enhanced damage modelling for fracture and fatigue Post-doctoral research (1999–2000) – University of Cambridge, Engineering Department Research interests revolve around micromechanics , micro-plasticity , multiscale modelling , homogenisation , damage and fracture , and enriched continuum theories . His work spans advanced high-strength steels, composites, paper and fibrous networks, with strong emphasis on coupling rigorous theoretical developments to industrially motivated problems. His recent publications (2023-2025) demonstrate a clear trajectory towards integrating advanced experimental techniques (e.g., digital image correlation, micro-mechanical testing) with high-fidelity computational frameworks such as crystal-plasticity finite-element modelling, FFT-based solvers and micromorphic homogenisation. Dominant themes include: Deformation and fracture in lath martensite and dual-phase steels Hygro-mechanics of paper and fibrous networks Pattern-transforming mechanical metamaterials Discrete-to-continuum scale bridging methods Scientific awards are not explicitly listed in the provided material; however, his prolific output (294 research items, >6500 citations) attests to significant peer recognition. Teaching & supervision: He delivers courses on Computational Mechanics – Numerical Methods for Fluids and Solids and Fracture Mechanics – Theory and Application , and has supervised >80 student works and numerous PhD candidates whose names appear on joint publications. Laboratory & teams: He heads the Group Peerlings within the Mechanics of Materials cluster, maintaining close collaboration with the Mechanics of Materials Group Geers and extensive national/international experimental and computational networks.

• Photovoltaics
• Solar Cells
• Silicon Solar Cells
• +۵ مورد دیگر

Olindo Isabella serves as a Full Professor within the Faculty of Electrical Engineering, Mathematics and Computer Science at Delft University of Technology. She heads the Photovoltaic Materials and Devices (PVMD) research group, driving innovation in solar energy conversion technologies. Her academic role encompasses teaching, research leadership, and extensive collaboration with industry and international institutions to advance photovoltaic science and engineering. Professor Isabella's research spans multiple domains of photovoltaics, including silicon and perovskite solar cells, thin-film technologies, offshore floating systems, and agrivoltaics. She investigates material properties, device physics, and system performance to enhance efficiency, reliability, and environmental sustainability of solar energy solutions. Her work integrates experimental and computational approaches for comprehensive analysis. Analysis of her recent publications indicates a strategic focus on machine learning for PV-climate classification, impedance spectroscopy of silicon solar cells, offshore floating platform engineering, and perovskite crystallization processes. These studies collectively address key barriers to large-scale solar deployment, such as performance prediction, structural integrity in marine environments, and novel material synthesis. Scientific Awards: The available information does not mention any specific awards or honors for Professor Isabella. She has guided the research of 20 students and secured competitive funding for impactful projects. Currently, she leads SYMBIOSYST (2023-2026), which explores symbiotic relationships between solar PV and agriculture, and recently completed TRUST-PV (2020-2024), aimed at improving PV plant integration across market segments through machine learning and monitoring technologies. The PVMD group under her direction operates state-of-the-art laboratories for solar cell fabrication and characterization. The team collaborates with global partners on field trials, data analysis, and technology development, contributing to both fundamental knowledge and practical applications in renewable energy.

• 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.

• Process Mining
• Healthcare Informatics
• Data Security
• +۳ مورد دیگر

Dr. Jeewanie Jayasinghe Arachchige is a Lecturer in the Department of Computer Science at Vrije Universiteit Amsterdam, Faculty of Science. She teaches undergraduate courses including Bachelor Project Computer Science, Professional Development, and Software Engineering Processes for the academic year 2024–2025. Her research focuses on process mining , healthcare informatics , and data security . She applies process mining to analyze healthcare pathways and subpopulation treatment variations, develops explainable AI frameworks for predictive analytics, and examines data governance in emerging architectures like Data Lakehouses. Her work intersects legal informatics, particularly formalizing Sri Lankan civil court processes using ontology engineering. Recent publications highlight trends in balancing simplicity and complexity in process modeling, Industry 4.0 healthcare applications, and cybersecurity in model-driven web development. She has contributed to over 20 peer-reviewed articles since 2006, spanning topics from service-oriented architectures to value network analysis. Her teaching and research emphasize practical applications of IT in healthcare, legal systems, and enterprise environments. No ancillary activities are currently recorded.

Jakob Schoefferمشاهده پروفایل

استادیار

• Responsible AI
• Explainable AI
• Human-Centered AI
• +۶ مورد دیگر

Jakob Schoeffer is a tenure-track Assistant Professor in the Artificial Intelligence department at the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence, Faculty of Science and Engineering, University of Groningen (Netherlands). His work focuses on the intersection of human decision-making and artificial intelligence, particularly in high-stakes contexts where fairness, transparency, and appropriate human-AI collaboration are critical. Dr. Schoeffer's research interests center on responsible and explainable AI, with specific focus areas including: Human-AI collaboration dynamics in decision-making processes Fairness perceptions and interventions in AI systems Appropriate reliance on AI recommendations Explainable AI techniques for high-stakes domains Transparency mechanisms that improve human-AI team performance Label indeterminacy issues in medical AI applications His recent publications (2023-2025) reveal a strong trend toward applying AI research in critical domains like healthcare (particularly neurological recovery prediction), while maintaining a rigorous focus on the human aspects of AI deployment. His work spans both theoretical foundations of human-AI interaction and practical implementations, often employing mixed-methods approaches that combine technical AI development with behavioral studies. Dr. Schoeffer actively collaborates with researchers across institutions including the University of Texas at Austin and has made significant contributions to top conferences in AI ethics, fairness, and human-computer interaction. His research has been featured in multiple news outlets and policy discussions, indicating real-world impact of his work on responsible AI development. Prior to his current appointment, Dr. Schoeffer was a Postdoctoral Research Fellow at the University of Texas at Austin. He received his PhD from the Karlsruhe Institute of Technology (KIT) in Germany with a dissertation titled "On the Interplay of Transparency and Fairness in AI-Informed Decision-Making." He also holds a master's degree in Operations Research from Georgia Tech and industry experience as a Senior Data Scientist at IBM.

Raquel Fernándezمشاهده پروفایل

استاد

• Computational Linguistics
• Dialogue Systems
• Cognitive Science
• +۳ مورد دیگر

Raquel Fernández is Full Professor of Computational Linguistics and Dialogue Systems at the University of Amsterdam, where she leads the Dialogue Modelling Group at the Institute for Logic, Language & Computation (ILLC). As Vice-Director for Research at ILLC and a Fellow of the ELLIS Society, she bridges computational linguistics, cognitive science, and artificial intelligence through her research on language use in multimodal and conversational contexts. PhD in Computational Linguistics from King's College London Prior research positions at University of Potsdam and Stanford University's CSLI Her work explores how cognitive constraints, social interaction, and perception shape language use, with a focus on: Visually-grounded language processing Multimodal dialogue modeling Model uncertainty and calibration Language grounding in multimodal data Language learning and semantic change Dialogue reference resolution Recent publications analyze multimodal reasoning limitations, cross-lingual knowledge consistency, and uncertainty modeling in dialogue systems. She has received multiple accolades including an ERC Consolidator Grant , NWO VENI/VIDI/Aspasia fellowships , and EMNLP/GenBench awards . Outstanding Paper Award (EMNLP 2023) Best Data Award (GenBench Workshop 2023) ELLIS Society Fellow ERC Consolidator Grant #819455 recipient NWO VENI/VIDI/Aspasia awardee As a leader in academic service, she serves on the SIGDAT Executive Committee and chairs multiple conference committees. Her lab develops models for multimodal dialogue, visual storytelling, and grounded language understanding.

Steven Hoekstraمشاهده پروفایل

دانشیار

• Atomic Physics
• Molecular Physics
• Stark Deceleration
• +۵ مورد دیگر

Prof. dr. Steven Hoekstra is an Associate Professor of Atomic and Molecular Physics at the University of Groningen's Faculty of Science and Engineering, within the Van Swinderen Institute. His research focuses on precision measurements using cold molecules to explore fundamental physics, including Stark deceleration, laser cooling, and searches for physics beyond the Standard Model. He leads the NL-eEDM program at Nikhef, investigating the electron's electric dipole moment. Hoekstra is also involved in educational innovation, having received the Teacher of the Year award (2020) and a Senior Teacher Qualification (2023). He has supervised over 11 PhD theses and currently mentors 5 students. His work combines experimental techniques with theoretical insights, addressing questions like symmetry violations and quantum dynamics. Key projects include manipulating BaF molecules with electrostatic fields and exploring levitated nanoparticles as sensors. Hoekstra has secured major grants, including NWO VICI (2022) and VIDI (2013), and collaborates internationally on projects like the European Strategy for particle physics. Recent articles highlight advancements in molecular beam control, spin-precession methods for EDM searches, and opportunities in radioactive molecules. He actively participates in the Physics Olympiad Netherlands as chair, contributing to science outreach and education.

Yali Tangمشاهده پروفایل

استادیار

• Fluid Dynamics
• Multiphase Flow
• Physicochemical Conversions
• +۷ مورد دیگر

Yali Tang is an Assistant Professor in the Department of Mechanical Engineering at Eindhoven University of Technology (TU/e), specializing in fluid dynamics and transport phenomena within multiphase flows and physicochemical conversions . Her work targets Iron Power technology , green steel production , and alkaline water electrolysis for hydrogen generation, combining advanced computational models with experimental validation . Education: Master's in Chemical Engineering from Sichuan University (2011) PhD in Mechanical Engineering at TU/e (2015) with Prof. Hans Kuipers Research Interests: She focuses on interphase interactions , interfacial transport mechanisms , and high-resolution simulations (down to 40 nm mesh) to predict bubble coalescence and film dynamics. Her studies on hydrogen bubble growth , dendritic iron formation , and gas distribution in electrolyzers aim to refine reactor design and industrial processes. Collaborations with industrial partners ensure practical applicability of her computational models. Recent Publications: Her 2025 work includes dimensional analysis of liquid film formation, solutal Marangoni effects in electrolysis, and X-ray validation of gas distribution models. Earlier studies (2020–2023) cover defluidization behavior of iron fines, CFD-DEM modeling of raceways, and acoustic field applications in particle dynamics. Labs & Collaborations: She leads computational efforts within the Power & Flow group under Prof. Niels Deen, contributing to the EIRES Research cluster. Her work bridges academic research with industrial innovation in fluid dynamics and energy transition technologies.

Hans van Lintمشاهده پروفایل

استاد

• Traffic Simulation
• Transportation Engineering
• Data Analytics
• +۳ مورد دیگر

Prof. Hans van Lint is a Professor of Traffic Simulation and Computing at Delft University of Technology (TU Delft), where he holds the Anthony van Leeuwenhoek Chair since 2013. He is affiliated with the Department of Transport & Planning within the Faculty of Civil Engineering and Geosciences. His research focuses on the intersection of traffic flow theory, data analytics, and traffic simulation, with applications in estimating and predicting traffic states in networks. He has supervised numerous PhD students and contributed to valorization projects translating research into practical solutions. Van Lint earned his MSc in Civil Engineering in 1997 and returned to TU Delft for his PhD, which he completed in 2004 on 'Freeway Travel Time Prediction.' He has held roles including Assistant Professor (until 2009), Associate Professor, and has served as Director of Education for the MSc Transport, Infrastructure and Logistics program from 2010–2016. His research interests include traffic simulation frameworks, data assimilation techniques, and the development of tools for traffic state estimation. He has authored influential papers on topics such as microscopic traffic modeling, congestion pattern analysis, and macroscopic fundamental diagrams. His work emphasizes bridging theoretical models with real-world applications, enhancing traffic management and infrastructure planning. Van Lint teaches courses like 'Transport & Planning' and 'Interdisciplinary Fundamentals,' reflecting his commitment to both research and education. He actively contributes to TU Delft's labs, including the Traffic Dynamics, Modelling and Control Lab, advancing interdisciplinary approaches to mobility challenges.

• Climate Change
• Deforestation
• Agricultural Science
• +۵ مورد دیگر

Confidence Duku is a researcher at Wageningen University & Research, specializing in climate resilience and agricultural systems. Their work integrates climate science, hydrology, and machine learning to address food security, deforestation impacts, and flood forecasting in data-scarce regions. Research Interests: Climate change modeling in Eastern Africa Hydrology-guided neural networks for flood forecasting Agricultural resilience (common bean, green gram) under climate stressors Economic impacts of deforestation in Brazil Climate services for financial institutions and SMEs Notable Contributions: Developed frameworks for climate-smart business planning and flood prediction, with a focus on regions like East Africa and Brazil. Their work emphasizes ecosystem services and adaptation strategies. Collaborations: Active in multi-institutional projects, including partnerships with SNV and Copernicus. Led LVVN projects on cascading climate risks and reforestation impacts.

Massimo Mischiمشاهده پروفایل

استاد

• Biomedical Signal Processing
• Diagnostic Imaging
• Ultrasound Technology
• +۴ مورد دیگر

Massimo Mischi is a Full Professor at the Faculty of Electrical Engineering of the Eindhoven University of Technology (TU/e) and chairs the Signal Processing Systems (SPS) Division , the largest division at TU/e with over 250 researchers. He founded the Biomedical Diagnostics (BM/d) Lab in 2012, which now includes 180 researchers and clinical/industrial advisors, focusing on biomedical signal processing for diagnostics and monitoring.

• Neuroscience
• Neurobiology
• Cerebellar Plasticity
• +۷ مورد دیگر

Dr. Ting-Feng Lin is an Assistant Professor at the Cell Biology, Neurobiology and Biophysics department within the Faculty of Science at Utrecht University, Netherlands. His research focuses on understanding the mechanisms of learning and memory formation in the cerebellum, particularly how synaptic and intrinsic plasticity mechanisms coordinate to regulate neuronal signaling and behavior. He employs advanced microscopy, optogenetic, and chemogenetic techniques in transparent zebrafish models to study these processes in vivo, with implications for neurodevelopmental disorders like autism spectrum disorder (ASD) and schizophrenia. 2025: Assistant Professor, Utrecht University 2019-2025: Postdoctoral Researcher, University of Chicago 2015-2019: PhD in Neuroscience, Neuroscience Center Zurich (ZNZ) 2010-2014: MS in Physiology, National Taiwan University 2006-2010: BS in Sports Medicine, China Medical University His work investigates how sensory experiences shape cerebellar processing during development, focusing on climbing fiber pathways and their role in sensory prediction errors. His group also studies the interaction between synaptic, intrinsic, and structural plasticity mechanisms in neural circuits, using zebrafish models with genetic modifications (e.g., Grid2 knockout) to model human neurological conditions. Dr. Lin has received scientific recognition including the SfN Trainee Professional Development Award for his work on Purkinje cell plasticity and the JNS Meeting Award for research on parallel fiber ramping activity and LTD. His publications span topics from cerebellar plasticity to voltage-gated K+ channel dynamics, reflecting his interdisciplinary approach to neurobiology.

• Evolutionary Computation
• Machine Learning
• Natural Computing
• +۵ مورد دیگر

Thomas Bäck is a Professor at the Leiden Institute of Advanced Computer Science (LIACS) , Leiden University , Netherlands, and a member of the interdisciplinary programme Society, Artificial Intelligence and Life Sciences (SAILS) . His academic career spans roles at Leiden University (1996–present) and leadership positions at the Center for Applied Systems Analysis in Dortmund (1994–2000). Education : Diplom-Informatiker (Computer Science), Technische Universität Dortmund (1990) Dr. rer. nat. (Computer Science), Technische Universität Dortmund (1994) Research Interests : Dr. Bäck specializes in evolutionary computation , machine learning , and their applications in sustainable smart industry and healthcare . Recent work focuses on integrating large language models (LLMs) and quantum computing into optimization frameworks, with projects like CIMPLO (predictive maintenance), ECOLE (experience-based optimization), and SAPPAO (airline operations optimization). Scientific Contributions : His 526+ publications cover evolutionary algorithms, quantum optimization, and LLM-driven design, with recent trends including: Quantum computing (e.g., quantum approximate optimization, quantum advantage challenges) LLM integration (e.g., hyperparameter tuning, mutation control, code evolution graphs) Healthcare and industry (e.g., predictive maintenance, anomaly detection, melt quality prediction) Algorithm benchmarking (e.g., IOHprofiler, MA-BBOB, explainable benchmarking) Scientific Awards : IEEE Fellow (2022) Royal Netherlands Academy of Arts and Sciences (KNAW) member (2021) Academia Europaea member (2022) IEEE Computational Intelligence Society Evolutionary Computation Pioneer Award (2015) Fellow, International Society of Genetic and Evolutionary Computation (2003) Best Ph.D. thesis award, German Society of Computer Science (GI) (1995) Advising and Grants : He supervises Ph.D. candidates in evolutionary computation and machine learning and has secured 7 major grants from organizations like the Dutch Research Council , European Commission , and The Research Council of Norway . His editorial roles include Editor-in-Chief of the Evolutionary Computation Journal and associate editorships in leading AI journals.

Niels van Oortمشاهده پروفایل

دانشیار

• Public Transport Planning
• Data-Driven Design
• Transport Sustainability
• +۵ مورد دیگر

Niels van Oort is an Associate Professor of Public Transport at Delft University of Technology (TU Delft), co-director of the Smart Public Transport Lab, and affiliated with the Department of Transport & Planning within the Faculty of Civil Engineering and Geosciences. His work focuses on public transport planning, data-driven design, and societal impacts including inclusiveness, land-use, and sustainability. He holds a dual role as a part-time consultant via his company Van Oort Mobility Consultancy since 2020. Education: MSc in Public Transport from TU Delft (2003), PhD in Service Reliability in Public Transport (2011). Professional experience includes roles at HTM (public transport operator), MIT (2009), and Goudappel Coffeng consultants (2007–2012). Transitioned to academia as a part-time assistant professor at TU Delft in 2012, becoming full-time in 2018. Research emphasizes network optimization, timetable reliability, micromobility, and first/last mile solutions. Key areas include pandemic impacts on transport behavior, digital inequality in mobility access, and sustainable transport policies. Supervises PhD students on integrated networks and passenger behavior. Teaching includes courses on public transport operations, advanced modelling, and transport networks. Active in academic publishing and conferences, with over 20 peer-reviewed articles since 2010. Engaged in interdisciplinary labs like SUM Lab (Smart Urban Mobility) and contributes to public discourse through media and consultancy. Labs/Teams: Smart Public Transport Lab (co-director), SUM Lab, and Delft Transport Modelling Group. Grants and projects focus on data-driven solutions for public transport efficiency and equity.