جستجوی استاد راهنمای دانشگاهی

Tim Van de Cruys is a Senior Lecturer at the Faculty of Arts, KU Leuven, serving as Head of the Centre for Computational Linguistics (CCL). He maintains significant affiliations with LECTIO (KU Leuven Institute for the Study of the Transmission of Texts, Ideas and Images), Leuven.AI (KU Leuven Institute for Artificial Intelligence), and LILI (KU Leuven Interdisciplinary Language Institute). His work bridges computational linguistics, artificial intelligence, and humanities research with practical applications across multiple disciplines. Dr. Van de Cruys specializes in computational semantics and creative language generation, with particular expertise in applying NLP techniques to historical and classical texts. His research spans multiple domains including: Natural Language Processing for ancient languages (Latin, Ancient Greek) Computational approaches to lexical and compositional semantics Large language models and their applications in humanities research Creative language generation and human-AI collaboration Named entity recognition and disambiguation in historical contexts Non-autoregressive modeling for sequential generation tasks His recent publications demonstrate a strong focus on applying cutting-edge NLP techniques to humanities challenges, particularly in processing ancient languages. He frequently employs transformer models to address named entity recognition, word sense discrimination, and semantic analysis in low-resource language contexts. His work consistently bridges formal linguistic theory with practical computational applications, creating valuable tools for digital humanities scholars. As promotor and co-promotor on numerous research projects extending through 2029, Dr. Van de Cruys supervises PhD students working at the AI-humanities intersection. His current major projects include "Living Corpora" (exploring human-AI collaboration in digital humanities), "Stochastic processes and non-autoregressive models for sequential generation," and "NIKAW" (exploring knowledge networks from classical antiquity). These projects demonstrate his commitment to advancing both theoretical understanding and practical applications of computational linguistics. He teaches various courses including Computational Linguistics, Scripting Languages, Programming for Humanities, Computational Creativity, and AI for Humanities, training students to work at this critical interdisciplinary crossroads. His leadership of the Centre for Computational Linguistics positions him at the forefront of computational linguistics research in Belgium, where he continues to expand the boundaries of what's possible at the intersection of language, computation, and humanistic inquiry.

• Computational Linguistics
• Natural Language Processing
• Computational Semantics
• +۵ مورد دیگر

Patrick Willems is a full Professor at KU Leuven's Faculty of Engineering Sciences, Department of Civil Engineering. He serves as the head of the Hydraulics Subdivision within the Hydraulics and Geotechnics unit. Professor Willems holds multiple significant roles including chairman of the ADS Bureau, member of the Faculty Council of Engineering Sciences, and participant in the Leuven One Health Institute and KU Leuven Institute for Urban Studies (LUSI). His work addresses critical global water management challenges through advanced hydrological modeling and climate change adaptation strategies. Professor Willems' research spans several critical areas in water resources engineering. His primary expertise includes urban hydrology and river engineering, statistical hydrology with focus on flood prediction and risk analysis, integrated river basin management, precipitation analysis, and climate change impacts on hydrological extremes. He employs both traditional hydrological modeling approaches and innovative machine learning techniques to develop practical solutions for flood warning systems, urban water management, and climate adaptation planning. His research integrates statistical methods, numerical modeling, and data science to address complex water management problems across multiple geographical contexts. Professor Willems leads multiple major international research projects examining hydrological extremes in transboundary river basins, natural climate adaptation measures, hydrological modeling of peatland areas, and deep learning-based prediction of hydrological extremes. His work spans various geographical contexts including Belgium, Vietnam, Bolivia, Tanzania, and the Congo Basin, demonstrating both local relevance and global applicability of his research. Within KU Leuven, Professor Willems teaches diverse courses including Environmental Problems and Techniques, Statistics and Data Science, Stochastic Hydrology, Urban and River Hydrology and Hydraulics, River Modeling, and Probability and Statistics. He also leads the Hydraulic Engineering Project course and an Artificial Intelligence Project course, reflecting his commitment to integrating traditional engineering knowledge with modern computational approaches. As head of the Hydraulics Subdivision, he oversees research activities focused on developing advanced water engineering tools and methodologies that bridge theoretical advancements with practical applications for water management authorities.

• Hydrology
• River Engineering
• Flood Prediction
• +۷ مورد دیگر

Roel Leus is a full professor at KU Leuven's Faculty of Economics and Business (FEB), part of the Operations Research and Statistics Research Group (ORSTAT). He holds roles such as Program Director for the Business Engineering programs and Chairman of the KU Leuven Advisory Committee for the Chinese Region. He earned his PhD in Applied Economics from KU Leuven in 2003, focusing on project planning under uncertainty. His research emphasizes operations research and management, particularly scheduling, project planning, and decision-making under uncertainty. Education: PhD in Applied Economics (KU Leuven, 2003); Master's in Business Engineering (Handelsingenieur, KU Leuven, 1998). He has held academic positions since 2003, including adjunct professorships at Beijing Jiaotong University. His administrative roles include heading ORSTAT research group (2012–2016) and program directorships. Research Interests: Sequencing and scheduling, project planning under uncertainty, discrete optimization, and practical quantitative decision support. He has supervised 12 graduated PhD students as primary supervisor and contributed to numerous publications in top journals like INFORMS Journal on Computing and European Journal of Operational Research. Teaching: Courses include 'Introduction to Operations Research,' 'Operations Research,' and 'Applications of Operations Research.' He coordinates master's theses in Data Science and Business Analytics, focusing on practical optimization problems. Grants and Projects: Acquired over €2 million in research funding from private companies, the National Bank of Belgium, and KU Leuven. His work spans satellite scheduling, supply chain management, and cross-docking logistics. Labs/Teams: Active in ORSTAT, collaborating on projects like drone-assisted delivery and robust scheduling algorithms. His research bridges theoretical advancements with real-world applications in logistics, manufacturing, and aerospace.

• Operations Research
• Operations Management
• Sequencing and Scheduling
• +۶ مورد دیگر

Stefan Vandewalle is a full professor at the Department of Computer Science, Faculty of Engineering Sciences, KU Leuven. His research focuses on numerical analysis, applied mathematics, and computational methods for stochastic differential equations, wind energy modeling, and uncertainty quantification. Department Chair, KU Leuven Member, Subdivision Numerical Analysis and Applied Mathematics Member, iSi Health Institute Observer, Faculty Council of Sciences Chair, Department Council for Computer Science His recent work explores multiscale modeling, Monte Carlo methods, and data assimilation techniques. Projects include micro-macro Parareal algorithms, wind turbine aeroelasticity, and turbulent flow reconstruction for wind farms. He supervises PhD candidates and collaborates on interdisciplinary studies involving structural mechanics and renewable energy systems. Publications highlight advancements in parallel-in-time methods, stochastic optimization for tokamak reactors, and DNS-based control of turbulent flows. Key keywords: Multiscale numerical methods Uncertainty quantification Wind energy simulation Monte Carlo algorithms PDE-constrained optimization Stochastic differential equations He contributes to academic governance as a member of extended faculty boards and evaluation committees.

• Numerical Analysis
• Applied Mathematics
• Computational Fluid Dynamics
• +۵ مورد دیگر

Philip Dutré is a full professor at the Department of Computer Science , Faculty of Engineering Science , KU Leuven. He leads the Computer Graphics Research Group and chairs the Human-Computer Interaction division . His teaching portfolio includes courses on algorithms, data structures, and computer graphics fundamentals. Research Focus : Rendering algorithms, photo-realistic and image-based rendering, perceptual-based rendering, material models, and intuitive controls for computer animation. He explores deep learning applications in global illumination and uses quantum field theory for efficient light transport in participating media. Publications : Recent work includes advancements in temporal coherence for light transport (2017–2023), functional integrals for scattering models (2025), and optimization of spatial data structures (2019). Teaching Innovations : Advocate for ungrading (feedback-only assignments), flipped classroom techniques, and interactive learning. His approach emphasizes conceptual understanding over rote memorization, with structured, self-contained lessons and active student engagement. Leadership : Serves on multiple academic councils and committees including the Commission on Research Integrity and Student Services Council .

• Computer Graphics
• Rendering Algorithms
• Photo-realistic Rendering
• +۹ مورد دیگر

Frédéric Vrins is a Professor at the Louvain School of Management (LSM) , UCLouvain , affiliated with the Louvain Institute of Data Analysis and Modeling in economics and statistics (LIDAM) and Louvain Finance (LFIN). His work bridges theoretical and applied finance, with a focus on risk modeling, portfolio optimization, and machine learning applications. His research interests include: Quantitative Finance: Derivatives pricing, stochastic processes, and model calibration. Risk Management: Credit concentration risk, recovery rates, and wrong-way risk in financial markets. Portfolio Optimization: Mean-variance strategies, diversification metrics, and robustness under parameter uncertainty. Machine Learning in Finance: Applications to recovery rate prediction and option pricing frameworks. Recent publications highlight trends in: Credit risk modeling for Collateralized Loan Obligations (CLOs) and consumer credit. Machine learning integration in derivatives pricing and portfolio construction. Stochastic methods for Brownian bridges, CDS spreads, and recovery rates. Empirical studies on Loan-to-Value policies and business cycle impacts. Affiliations and locations: Louvain School of Management (LSM) - Building B, Chaussée de Binche 151, 7000 Mons Louvain Finance (LFIN) - Traverse d'Esope 1, 1348 Louvain-la-Neuve Louvain School of Management (LSM) - BATA Building, Chaussée de Binche 151, 7000 Mons

• Finance
• Quantitative Finance
• Risk Management
• +۳ مورد دیگر

Dr. Freija De Vleeschouwer is a postdoctoral researcher and teaching faculty member in the Department of Chemistry at Vrije Universiteit Brussel (VUB) in Brussels, Belgium. With an ORCID identifier 0000-0003-0563-1509, she has established herself as a prominent researcher in computational chemistry with 927 citations and a 15 h-index. Her academic journey includes multiple FWO postdoctoral fellowships and a Research Professor appointment in Basic, Nature & Applied Sciences (2020). Dr. De Vleeschouwer's research focuses on the application of computational quantum chemical methods to solve complex problems in molecular design and materials science. Her work spans several key areas including density functional theory, molecular reactivity, self-healing polymers, and nonlinear optical materials. She employs a multidisciplinary approach combining computational predictions, molecular dynamics simulations, and experimental validation to advance understanding in these fields. Her recent research output demonstrates a strong trend toward computational-experimental integration, particularly in the development of self-healing polymer networks through Diels-Alder chemistry. She has also made significant contributions to understanding hexaphyrin compounds and their optical properties using explainable machine learning approaches. This work bridges traditional computational chemistry with modern data science techniques. Scientific Awards: FWO postdoctoral fellowship (2010) for molecular design using conceptual DFT FWO postdoctoral fellowship (2013) for inverse molecular design in radical chemistry Poster prize at the 15th International Congress of Quantum Chemistry (2015) Research Professor in Basic, Nature & Applied Sciences (0.1 ZAP) (2020) Dr. De Vleeschouwer actively supervises graduate students and has served on PhD committees. Her research is supported by multiple competitive grants including FWOTM and SRP projects. She organizes international conferences, including the 19th International Conference on Density Functional Theory and its Applications (2022), and participates in international collaborations such as research stays at Palacky University Olomouc. She leads several active research projects through 2026-2027, including FWOTM1148 on accelerating Diels-Alder kinetics in self-healing polymers and SRP73 on molecular and material property prediction using combined quantum chemical approaches.

• Computational Chemistry
• Density Functional Theory
• Quantum Chemistry
• +۶ مورد دیگر

Tom Wenseleers is a Professor at KU Leuven's Department of Biology within the Faculty of Science, where he leads the Laboratory of Socioecology and Social Evolution. His research spans theoretical and experimental approaches to evolutionary biology, with particular focus on social insect systems. Research spans social insects (ants, bees, wasps), microbes, viruses, and human systems Primary model organisms: social insects studying major evolutionary transitions Current projects examine caste determination, chemical communication, and evolutionary conflicts His research integrates theoretical modeling with experimental, behavioral, and comparative studies. Recent work combines genomic techniques and high-throughput GC/MS analysis to decipher chemical communication systems. Current trends show increasing interdisciplinary work spanning virology (SARS-CoV-2 variants), microbial ecology (antibiotic resistance), and robotics (pollinator behavior monitoring). The research demonstrates consistent application of evolutionary theory to diverse biological systems while maintaining social insects as the core model. Wenseleers actively mentors PhD students and postdocs, with recent graduates including Kamiel Debeuckelaere and Viviana Di Pietro. His lab receives substantial funding through multiple concurrent research projects, including Promotor roles on grants examining caste development in bee societies and microbial metabolite screening. The laboratory maintains strong international collaborations across Europe and South America. The lab operates within the Ecology, Evolution and Biodiversity Conservation unit at KU Leuven, with physical location at Naamsestraat 59, box 2466, 3000 Leuven. The research group maintains active outreach programs including science workshops for schools and public engagement events focused on insect conservation.

• Theoretical Biology
• Evolutionary Biology
• Behavioural Ecology
• +۷ مورد دیگر

Prof. Wim Desmet is a full professor at the Faculty of Engineering Science and head of the Department of Mechanical Engineering at KU Leuven . His research focuses on advanced modeling techniques for mechanical systems, including: noise and vibration control in automotive and industrial systems computational acoustics and interval field uncertainty modeling metamaterials for broadband vibroacoustic performance AI-driven diagnostic systems in renewable energy and manufacturing Current research projects address challenges in electric vehicle drivetrains, wind turbine monitoring, and multi-physical digital twin development. He actively contributes to academic governance as: Managing Director of KU Leuven Head of Subdivision HIST Chair of multiple executive committees Member of 15+ academic and administrative councils

• Noise Abatement in Machines and Vehicles
• Numerical Modeling in Mechanics
• Automotive Structures and Dynamics
• +۱۲ مورد دیگر

Pierre-Antoine Absil is a Full Professor at the Louvain Polytechnic School (EPL) , part of the Université catholique de Louvain (UCLouvain) , affiliated with the Mathematical Engineering Center (INMA) and the Institute of Information and Communication Technologies, Electronics and Applied Mathematics (ICTEAM) . His research spans Riemannian optimization , matrix manifolds , and low-rank approximation with applications in astronomical imaging , signal processing , and environmental data imputation . His work emphasizes Riemannian optimization algorithms matrix and tensor completion geometric data analysis applications in astrophysics and bioinformatics Recent publications focus on Stiefel and Grassmann manifolds , variable projection methods , and exoplanet detection via alternating minimization . While no explicit scientific awards are listed, his collaborations with institutions like IEEE and Springer highlight his impact in computational mathematics and engineering. He has supervised researchers such as Simon Vary , Guillaume Olikier , and Valentin Christiaens through projects in direct imaging , economic dispatch , and graph-based data processing . His laboratory, INMA , drives methodological advances in manifold-valued data analysis and nonlinear optimization .

• Riemannian Optimization
• Matrix Manifolds
• Low-Rank Matrix Completion
• +۴ مورد دیگر

Jannik Matuschke serves as Associate Professor in the Department of Decision Sciences and Information Management at KU Leuven's Faculty of Economics and Business (FEB). He is an active member of both the KU Leuven Institute for Artificial Intelligence (Leuven.AI) and the KU Leuven Institute for Mobility (LIM), holding office at Hogenheuvelcollege (HOGC) 04.123 in Leuven, Belgium. His academic career spans multiple prestigious institutions across Europe, reflecting his international recognition in operations research and theoretical computer science. Dr. Matuschke completed his PhD in Mathematics in 2013 at Technische Universität Berlin under Martin Skutella and Britta Peis. His academic journey included a postdoctoral position at Universidad de Chile (2014), a DAAD P.R.I.M.E. fellowship at the University of Rome 'Tor Vergata' (2015), and a junior group leader/lecturer position at Technische Universität München (2016-2018) before joining KU Leuven in 2019. His research focuses on the intersection of discrete mathematics, theoretical computer science, and operations research, with specific expertise in combinatorial optimization, algorithm design and analysis, game theory and social choice, robustness and uncertainty, and logistics applications. Dr. Matuschke has made significant contributions to network flow theory, security games, and robust optimization frameworks, developing both theoretical foundations and practical applications. Analysis of his recent publications reveals a strong emphasis on robustness under uncertainty, with increasing focus on security applications and theoretical aspects of scheduling problems. His work demonstrates consistent innovation in decomposing complex optimization problems and developing approximation algorithms for challenging combinatorial settings. 2024 Meritorious Service Reward of the journal Operations Research Dr. Matuschke actively mentors several PhD students and postdocs, including Yanfei Chen, Léonie Gallois, Phablo Moura, Felix Rauh, and Fei Wu. He leads significant research projects such as 'Rigidity and Flexibility: Structures and Algorithms' (starting 2025), 'Designing resilient and recoverable infrastructures via multi-level and multi-stage optimization' (2022), and 'Optimization and analytics for stochastic and robust project scheduling' (2020), with funding from diverse sources including KU Leuven start-up grants, FWO research projects, and DAAD fellowships. As an integral member of the academic community, Dr. Matuschke serves as Associate Editor for Omega (since 2023), Operations Research Letters (since 2024), and OR Spectrum (since 2019). He co-chairs the program committee for WAOA 2025 and has participated in numerous prestigious conference committees. At KU Leuven, he coordinates the 'Master's Thesis in Production and Logistics' program and serves on the Teaching Portfolio Peer Review Committee.

• Combinatorial Optimization
• Algorithm Design and Analysis
• Game Theory and Social Choice
• +۴ مورد دیگر

Jennifer Alonso-García is a tenured Professor of Actuarial Science in the Department of Mathematics at the Faculty of Sciences, Université Libre de Bruxelles (ULB), a position she has held since October 2019. She concurrently serves as an Associate Investigator at CEPAR, a Netspar Fellow, and treasurer of the PBSS board. Previously, she was a tenure-track Assistant Professor at the University of Groningen's Department of Economics, Econometrics and Finance and a Senior Research Associate at CEPAR. Her academic foundation includes mathematics studies completed in Spain and Germany, culminating in a PhD in Actuarial Science from the Université Catholique de Louvain in 2015. She maintains professional certification as an IA|BE Qualified Actuary by the Belgian Institute of Actuaries and brings industry experience as a Risk Advisor specializing in Solvency II and MCEV frameworks. Dr. Alonso-García's research program centers on actuarial science with emphasis on pension systems, retirement income security, longevity risk quantification, and variable annuity product design. Her work addresses critical challenges in demographic risk management, intergenerational equity, and sustainable pension financing through advanced stochastic modeling techniques. She investigates how socio-economic factors impact mortality patterns and retirement outcomes, with particular focus on fairness in pension design. Analysis of her 15 most recent publications (2021-2025) reveals consistent thematic focus on pension economics and actuarial modeling, characterized by three dominant trends: intergenerational risk-sharing mechanisms in public pension schemes, innovative variable annuity contract designs with hybrid guarantees, and socio-demographic mortality analysis incorporating AI techniques. Her work demonstrates strong methodological rigor in applying risk measures to pension sustainability assessments. Her scholarly contributions have been recognized through prestigious awards: ICA 2018 Best Paper Award IAA Section IAAHS Best Paper Award (2018) IAA Section PBSS Best Paper Award (2019) Dr. Alonso-García actively shapes her field through significant service commitments including Associate Editor for Annals of Actuarial Science, Editorial Board membership at ASTIN Bulletin, and Scientific Board position at Anales del Instituto de Actuarios Españoles. She co-organizes the One World Actuarial Research Seminar and frequently participates in international collaborative projects, evidenced by upcoming engagements including a workshop on pension design in Andros, Greece (September 2025), a research visit to UNSW Sydney (October 2025), and the 1st ASTIN Bulletin Conference in Zürich (January 2026).

• Actuarial Science
• Pension Systems
• Retirement Income
• +۳ مورد دیگر

Prof. Damien Ernst is a faculty member at the Montefiore Institute, Department of Electrical Engineering and Computer Science, University of Liège (Belgium). His research focuses on energy systems, remote renewable energy hubs, reinforcement learning, and optimization algorithms. He actively contributes to decarbonization strategies for hard-to-abate sectors like shipping and aviation. Academic Rank: Professor University: University of Liège School: Montefiore Institute Department: Electrical Engineering and Computer Science Research interests include: Design and techno-economic analysis of remote renewable energy systems Reinforcement learning applications in energy and optimization Energy transition policy and sustainability modeling Machine learning techniques for energy system transparency Integration of nuclear, hydrogen, and battery technologies His recent publications demonstrate expertise in: Remote Renewable Energy Hub (RREH) design Small Modular Reactor (SMR) integration Asymmetric Actor-Critic algorithms Energy system optimization and modeling Grid stability and hosting capacity analysis Explainable AI for closed-domain question answering Prof. Ernst leads PhD projects at the intersection of Operations Research and Energy Systems, focusing on energy systems models' transparency and optimization techniques.

• Energy Systems
• Operations Research
• Remote Renewable Energy Hubs
• +۵ مورد دیگر

Hakan Ergun serves as an Associate Professor at KU Leuven's Faculty of Engineering Science within the Department of Electrical Engineering (ESAT). He leads the Subdivisie EnergyVille Electa - Ergun and holds key roles in EnergyVille initiatives, including membership in the Division EnergyVille and the Council of the Faculty of Engineering Science. His research focuses on power systems engineering with specialization in HVDC grid technology, renewable energy integration, and stochastic optimization. Current projects include predictive maintenance for wind farms, congestion management for offshore HVDC grids, and development of hybrid AC/DC grid software tools. His work addresses critical challenges in grid resilience, uncertainty modeling, and multi-national offshore grid coordination. Recent publications demonstrate strong trends in hybrid AC/DC grid optimization under uncertainty, with emphasis on stochastic programming, polynomial chaos expansion, and risk-based operational models. Key themes include offshore grid protection, frequency stability with energy storage, and spatio-temporal variability in power system planning. Ergun actively supervises doctoral candidates including K. Phillips and C.K. Jat. His research portfolio includes significant EU-funded projects such as CROCODILE (Cross-border Coordination of Offshore Grids) and advanced HVDC grid development initiatives with multi-year funding through 2028-2029. He directs the EnergyVille Electa subdivision focused on electrical energy systems applications, collaborating with industry partners on real-world grid implementation challenges. Current work emphasizes practical solutions for multi-GW offshore energy hubs and resilient power systems leveraging HVDC transmission flexibility.

• Power Systems Engineering
• HVDC Grid Technology
• Renewable Energy Integration
• +۲ مورد دیگر

Tijl De Bie is a Senior Full Professor at the University of Ghent, specializing in machine learning, data science, and their applications in bioinformatics, computational social sciences, and HR analytics. He leads the AI and Data Analytics (AIDA) research group within IDLab-ELIS. PhD in Machine Learning (KU Leuven, 2005) Worked at U.C. Berkeley, U.C. Davis, University of Southampton, and University of Bristol His research focuses on foundational aspects of data science, including fairness in AI, network embeddings, and human-centric methodologies. Recent work explores temporal network simulation, bias mitigation, and large-scale career trajectory datasets. Notable awards include an FWO Odysseus Group I grant and three ERC grants (Consolidator, Proof of Concept, Advanced). Current projects involve ethical AI frameworks and dynamic network analysis. Scientific Awards : FWO Odysseus Group I, ERC Consolidator, ERC Proof of Concept, ERC Advanced Grant He collaborates extensively in interdisciplinary research, applying machine learning to social media analysis and financial domains. His team develops open-source tools like EvalNE and Fondue for network embedding evaluation.

• Foundations of Data Science
• Human-Centric Data Science
• Exploratory Data Analysis
• +۲ مورد دیگر