جست‌وجوی استاد و پژوهشگر

Julien Blondeauمشاهده پروفایل

استاد مهمان

• Thermodynamics
• Combustion
• Thermal Power Plants
• +۵ مورد دیگر

Julien Blondeau serves as an Unpaid Guest Professor in the Department of Applied Mechanics within the Faculty of Engineering at Vrije Universiteit Brussel (VUB), Brussels. His research focuses on sustainable energy systems with particular emphasis on thermodynamics, combustion processes, thermal power plants, and biomass energy conversion. He maintains active collaborations between VUB and ULB through joint doctoral projects and seed funding initiatives. His research interests span Thermodynamics , Combustion Engineering , Biomass Energy Systems , Carbon Capture Technologies , and Urban Energy Transitions . Current work investigates ammonia-hydrogen combustion in gas turbines, forestry biomass energy return on investment, and the development of Positive Energy Districts through multi-objective optimization. His fingerprint analysis reveals strong expertise in gas turbines (56%), hot temperature applications (51%), boilers (48%), and carbon capture (43%). Analysis of his 15 most recent publications shows a clear trajectory toward integrated urban energy solutions, with increasing focus on techno-economic analysis of sustainable transitions. His 2024-2025 work demonstrates particular emphasis on Brussels-specific energy challenges, biomass optimization, and hybrid storage systems under uncertainty. Blondeau actively supervises doctoral candidates including Cyril Freyling through the VUB-ULB joint PhD program. His current research portfolio includes 27 active projects with significant funding from initiatives like SRP98 (Spatio-temporal data-driven modeling), IOF3029 (Huis van Duurzame Transities), and BASGO22 (FLOW research group). He participates in key research networks focused on thermal and fluid dynamic systems, contributing to workshops like the Extreme CFD series and presenting at international conferences on topics ranging from carbon fiber graphitization to flue gas condenser retrofitting. His work bridges fundamental fluid dynamics with practical urban sustainability challenges.

Thomas Geuryمشاهده پروفایل

پژوهشگر

• Electric Vehicles
• Vehicle-to-Grid Systems
• Energy Storage
• +۴ مورد دیگر

Thomas Geury is a postdoctoral researcher at the MOBI - Electromobility Research Centre within the Free University of Brussels (VUB) , specializing in Electrical Engineering-Power Technology. His work focuses on advanced power electronics, energy storage, and electric vehicle systems. Education: PhD in Engineering Sciences and Technology (2017), Université libre de Bruxelles Master in Electrical Engineering (2012), Université libre de Bruxelles Bachelor in Electromechanical Engineering (2010), Université libre de Bruxelles His research interests include electric vehicles , vehicle-to-grid systems , energy storage , and power electronics . He has contributed to projects involving battery management, modular converters, and sustainable energy integration. Recent work highlights optimization frameworks for DC-DC converters , microgrid design for marine applications , and smart charging infrastructure . His publications emphasize efficiency, modularity, and interoperability in renewable energy and electric mobility systems. Scientific Awards: The Best Paper Award on Energy for Sustainable Mobility (2024) Geury collaborates on EU-funded projects like HARPOONERS (marine electrification) and FLEXMSC (megawatt charging). He has served as a chair for IEEE conference sessions on modular converter design and control systems.

• Serious games
• Patient rehabilitation
• Gesture recognition
• +۵ مورد دیگر

Bart Jansen is a Researcher at the Department of Electronics and Informatics within the College of Engineering at Vrije Universiteit Brussel (Belgium). With over 241 research outputs and an h-index of 24, his work spans computer science, biomedical engineering, and clinical applications. Research Interests: AI and virtual twin technology for stroke rehabilitation 3D imaging and augmented reality in medical contexts Gesture recognition and electromyography (EMG) systems Serious games for elderly healthcare Frailty and calcinosis detection Scientific Achievements: Recipient of two international app development awards (2019) Supervised 11 theses including PhD-level work Active in 45 projects (2003-2029) Professional Engagement: Regular participant in conferences like ESMAC, 3DBODY.TECH, and AIxVR, with additional roles as symposium organizer at Care4: International Scientific Nursing Conference (2024).

• Power Electronics
• Artificial Intelligence in Design Automation
• DC-DC Converters
• +۷ مورد دیگر

Diego Gerardo Bernal Cobaleda is a researcher at KU Leuven , affiliated with the Electrical Engineering Department (ELEKTRA) and the EnergyVille research institute. His work focuses on power electronics design automation, integrating artificial intelligence (AI) and machine learning (ML) techniques to optimize converter efficiency and component selection. Research Highlights : AI-driven semiconductor datasheet analysis, variable transformer design for wide voltage ranges, reinforcement learning for converter parameter optimization. Collaborators : Fanghao Tian, Wilmar Martinez, Camilo Suarez Buitrago, Miguel Vivert. His recent publications address: Automated extraction of dynamic characteristics from MOSFET datasheets using computer vision. Development of resonant multi-input multi-output (MIMO) converters for aerospace applications. Integration of variable transformers in LLC and dual active bridge (DAB) topologies for improved efficiency. Application of deep reinforcement learning (DDPG) to optimize converter parameters. He has contributed to journals including IEEE Transactions on Power Electronics , Energies , and IEEE Access , as well as conferences such as IEEE APEC, ECCE Asia, and ISIE.

• Management Accounting
• Costing Systems
• Environmental Accounting
• +۴ مورد دیگر

Prof. dr. Sophie Hoozée is an Associate Professor of Management Accounting and Control at Ghent University and a Visiting Professor at Antwerp Management School and the University of Antwerp . Her expertise centers on the design and application of costing and management control systems, particularly time-driven activity-based costing . She teaches across bachelor's, master's, and executive education programs in cost accounting, management accounting, and management control. Associate Professor at Ghent University Visiting Professor at Antwerp Management School Visiting Professor at the University of Antwerp Her research focuses on the societal impact of management accounting practices in healthcare and recycling, driven by interdisciplinary collaborations that amplify real-world relevance. Recent publications highlight the intersection of management accounting with digitalization, sustainability, and cross-cultural management. Key areas include financial automation , sustainability assurance processes , and environmental costing models , reflecting her commitment to advancing policy and ethical practices. Sophie serves on the editorial boards of Accounting, Auditing & Accountability Journal and Social & Environmental Accountability Journal . She contributes to professional governance as an independent non-executive board member and audit committee chair at Europabank , jury chair for proficiency exams, and panel member for the Belgian Awards for Sustainability Reports .

• Requirements Engineering
• Optimization
• Software Engineering
• +۳ مورد دیگر

Joseph Gillain is affiliated with the Faculty of Economics, Management, Communication, and Politics, holding a Doctorate in Economics and Business Management. His research focuses on requirements engineering, optimization, and decision-making systems. He has led projects integrating machine learning for automated decision-making and methodologies for knowledge capitalization in business contexts. Education: Doctor of Economics and Business Management (2017), Master in Management (2010). His research interests include requirements optimization, software engineering, and the application of machine learning in business processes. Recent work emphasizes improving requirements elicitation quality and adaptive service systems. Projects include POC AI4DKC and DKC: Decision Knowledge Capital, addressing automation, consumer behavior analysis, and intuitive interfaces.

Guy De Tréمشاهده پروفایل

دانشیار

• Computational Intelligence
• Data Quality
• Decision Support Systems
• +۷ مورد دیگر

Guy De Tré is an Associate Professor at the Department of Telecommunications and Information Processing within Ghent University's Faculty of Engineering and Architecture. He leads the Database, Document and Content Management (DDCM) research group and focuses on computational intelligence in information systems, with expertise in bi-polarity handling, uncertainty modeling, and multi-valued logic systems. Primary Affiliation: Ghent University Research Focus: Data quality, fuzzy querying, spatio-temporal modeling Key Contributions: Foundational work in possibilistic databases and explainable AI His research combines theoretical and applied approaches to information management systems. Theoretical work includes: Bipolarity and uncertainty handling in databases Multi-valued logic frameworks Interval B-tree indexing for possibilistic data Applied research spans: NoSQL database optimization Decision support systems Contextualized machine learning 3D/4D modeling for geological resources Recent publications show increasing focus on explainable AI, with multiple works on contextualized support vector machine classification and orthographic similarity measures for graph-based data representations. His work bridges database theory with practical applications in data quality assessment, medical informatics, and cultural heritage projects like the Byzantine Book Epigrams database. Research Group: Leads the DDCM group at Ghent University, specializing in: Database management innovation Content modeling techniques Fuzzy logic implementations Temporal data indexing Intelligent information systems

Leticia Arco Garciaمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Complex Networks
• Deep Learning
• +۵ مورد دیگر

Leticia Arco Garcia is a postdoctoral researcher at Vrije Universiteit Brussel working in the Department of Informatics and Applied Informatics with affiliations at Federated Labs AI and Robotics. Her research spans computational linguistics, complex network analysis, and more recently, interdisciplinary applications in archaeobotany. Her research interests focus on Natural Language Processing , Complex Networks , and Deep Learning methodologies. Early work centered on community detection in complex networks and customer behavior analysis, while recent publications demonstrate expansion into archaeobotanical applications using morphometric analysis of phytoliths. She employs advanced computational techniques including LSTM networks, case-based reasoning, and multi-objective optimization across diverse domains from smart power grids to electronic money systems. Analysis of her 15 most recent publications reveals an interdisciplinary trajectory moving from pure computer science applications toward biological/archaeological domains. The earliest works focus on network construction and community detection, while more recent papers apply similar analytical frameworks to botanical specimens, indicating methodological transfer between fields. Her work consistently applies computational rigor to complex data structures across diverse application areas. Her scientific contributions include: Development of novel network construction methodologies for large purchasing collections Advancements in overlapping community detection using rough clustering Application of deep learning to sentiment analysis and customer behavior prediction Recent innovative work applying morphometric analysis to archaeobotanical specimens Dr. Garcia actively presents her research at international conferences including INTERSPEECH and specialized meetings on phytolith research. Her collaborative network spans multiple institutions, with co-authorship on interdisciplinary projects connecting computer science with archaeology and plant science. While specific grant information isn't detailed in the available text, her consistent publication output across multiple domains suggests successful research funding.

Dries Benoitمشاهده پروفایل

دانشیار

• Bayesian Statistics
• Marketing Modeling
• Customer Relationship Management
• +۵ مورد دیگر

Dries Benoit is an Associate Professor in Data Analytics at Ghent University, specializing in Bayesian Statistics and its applications in business engineering. He teaches advanced courses in Bayesian Statistics, Statistical Modeling & Datamining, and Pricing & Revenue Management. Additionally, he serves as a visiting professor at Université de Namur and IESEG School of Management, where he contributes cross-institutional expertise in statistical modeling. Primary Affiliation : Ghent University Secondary Affiliations : Université de Namur, IESEG School of Management Research Focus : Dries Benoit's work bridges methodological advancements in Bayesian statistics with real-world applications across business domains. Core areas include marketing modeling, customer relationship management (CRM), learning analytics, and operations research. His interdisciplinary collaborations extend to medicine, energy, and education sectors, leveraging data science to solve complex problems in churn prediction, demand forecasting, and multimodal analysis. Publications & Research Trends : His recent publications highlight: Machine learning techniques for question difficulty estimation Uncertainty quantification in industrial AI Transformer-based models for ordinal regression Churn prediction in business-to-business contexts Deep learning applications in cultural analytics Ensemble methods for robust classification These works emphasize interpretable modeling, cross-domain adaptability, and balancing technical precision with business strategy applications.

• Robotics
• Computer Vision
• Robot Learning
• +۳ مورد دیگر

Renaud Detry is an Associate Professor at KU Leuven, Belgium, with dual appointments in the Department of Electrical Engineering (ESAT) and the Department of Mechanical Engineering. He is a member of the Leuven.AI Institute and the ELLIS Society, and serves as an associate editor for IEEE Transactions on Robotics and conference series like IROS and ICRA. His research focuses on robot learning, computer vision, and their applications in manufacturing, agriculture, healthcare, space robotics, and planetary exploration. He holds a Ph.D. and has prior roles as an Assistant Professor at UCLouvain and Group Lead at NASA JPL. His work includes projects like the robotic construction system for shotcrete digitization (RoBétArmé) and space robotics for Mars Sample Return. He advises students such as Louis Hanut, Yurui Du, and Pinhao Song, and collaborates with institutions like ULiege and KTH. His recent publications emphasize adaptive robotic frameworks, uncertainty-aware learning, and multi-task diffusion policies. Notable awards include a Best Presentation Award at the ECCV 2022 Workshops. His grants include leadership in projects like Neurobotics (2022–2026) and Learning Partially-factorized Manipulation Tasks (2021–2023). He maintains active roles in academic networks, including the Council of the Faculty of Engineering Science and departmental councils. His lab focuses on bridging perception, learning, and control for real-world robotic applications in challenging environments.

Mohayad Omerمشاهده پروفایل

پژوهشگر

• Robotics
• Control Systems
• Mechanical Engineering
• +۳ مورد دیگر

Mohayad Omer is a Researcher in the Faculty of Engineering at Vrije Universiteit Brussel (VUB), Belgium, holding a PhD in Engineering Technology. His research focuses on robotics and control systems for non-prehensile object manipulation, with current leadership of the FWO-funded project 'FWOSB178: Safe control for non-prehensile object transportation using a heterogeneous robot team' (2024-2028). He completed his Master's degree in 2023 at VUB with the thesis 'Constrained Control For Dynamic Non-prehensile Object Transportation: Modeling, Control, and Optimization of a Franka Emika Panda Robot for Non-Sliding and Non-Prehensile Object Transportation' under supervisors Merckaert, K. and Van de Perre, G. His research fingerprint identifies core expertise in Robotics (80%), Gravitation modeling (94%), Friction dynamics (73%), and Cone-based manipulation (100%). His work bridges mechanical engineering and control theory to develop safe transportation methods without object grasping, emphasizing real-world applications in industrial automation. Recent publications demonstrate specialization in constraint control for flexible manipulators and non-prehensile transportation, addressing dynamic challenges in heterogeneous robot teams. 1st Place Award in the Real-World Challenge - IEEE MRS 2024 1st place in IEEE MRS, Virtual challenge (August 2024) Omer serves as principal investigator for the €250,000 FWO project FWOSB178, developing control strategies for multi-robot object transportation. While no current advisees are documented, his 2023 Master's thesis supervision suggests mentoring experience. He actively contributes to academic discourse through conference presentations at the 43rd Benelux Meeting on Systems and Control (2024) and the IEEE RAS Summer School on Multi-Robot Systems (2024). His research operates within VUB's robotics group, collaborating with Bram Vanderborght and Greet Van de Perre on advanced manipulation techniques. Current activities include developing optimization frameworks for Franka Emika Panda robots and participating in the 44th Benelux Meeting on Systems and Control (2025).

• Reinforcement Learning
• HIV/AIDS
• Epidemiology
• +۶ مورد دیگر

Pieter Libin is a Professor at the Vrije Universiteit Brussel (VUB) in the Department of Informatics and Applied Informatics, part of the College of Engineering and Informatics. He leads the Federated Labs AI and Robotics and specializes in applying reinforcement learning to interdisciplinary challenges in public health, virology, and chemical engineering. Research Interests : Libin’s work spans reinforcement learning, HIV/AIDS dynamics, epidemiological modeling, and AI-driven solutions for healthcare and chemical processes. His research often bridges computational methods with real-world applications, including pandemic response strategies, drug resistance prediction, and automated laboratory optimization. Recent Trends in Articles : Recent work focuses on applying RL to optimize liquid chromatography methods, model infectious disease spread (e.g., SARS-CoV-2), and develop fair machine learning frameworks. He also explores genomic diversity in viruses like Zika and HIV to inform public health policies. Prizes : ALA best paper award (2018) FWO SB doctoral grant (2016) ICTAI Best student paper award (2018) Grants & Projects : Active projects include FWO-funded initiatives on fairness in RL, pandemic modeling, and chromatography automation. He collaborates internationally on topics like HIV epidemiology and vaccine allocation strategies. Labs/Teams : Leads the Federated Labs AI and Robotics, focusing on AI applications in health and engineering. Involved in interdisciplinary teams combining computer science, virology, and public health.

• Computer Vision
• Deep Learning
• Kalman Filters
• +۳ مورد دیگر

Leandro Di Bella is a Researcher affiliated with the Department of Electronics and Informatics at the Faculty of Engineering, Vrije Universiteit Brussel (VUB), Belgium. His doctoral research focuses on advanced computer vision techniques, particularly in Kalman filters, deep learning integration, and 3D object detection. He has contributed to innovative solutions for monocular vehicle pose estimation and multi-object tracking, emphasizing temporal consistency and real-time applications. Research interests prominently feature computer vision applications in autonomous systems, attention mechanisms in neural networks, and sensor fusion technologies. Recent work includes developing the DeepKalPose and LAM3D frameworks, addressing challenges in pose estimation and 3D detection through hybrid deep learning approaches. His publications demonstrate expertise in merging classical filtering methods (e.g., Kalman filters) with modern deep learning architectures. Peer review activities include roles at prominent events like the British Machine Vision Conference and IEEE International Conferences on Image Processing. Collaborations span international institutions, focusing on multimedia signal processing and AI-driven vision systems. His research bridges theoretical advancements with practical implementations in autonomous navigation and robotics.

• Mechatronic Simulation
• Virtual Sensing
• Flexible Multibody Simulation
• +۳ مورد دیگر

Frank Naets is a Senior Lecturer at the Department of Mechanical Engineering , part of the Faculty of Engineering Sciences at KU Leuven . He contributes to the Mechatronic System Dynamics (LMSD) research group and is affiliated with divisions including the Dynamics Division, DYNA Subdivision, and Leuven.AM – KU Leuven Institute for Additive Manufacturing. His roles span teaching, research coordination, and membership in academic councils like the Faculty Council of Engineering Sciences and Departmental Council of Mechanical Engineering. Research Areas: Mechatronic Simulation, Virtual Sensing, Flexible Multibody Dynamics, Nonlinear Model Order Reduction His research focuses on system-level modeling of mechatronic systems, integrating virtual sensing and digital twin technologies for force estimation, vibration analysis, and structural monitoring. Key applications include electric vehicle drivetrains , hydrogen fuel cells , and rotary machinery . Recent projects highlight his expertise in sensor placement algorithms , Kalman-based state estimation , and experimental validation of material properties. He supervises students like Alessandro Zucchini and Raffaele De Gregoriis while collaborating on international conferences such as ECCOMAS Multibody 2025 and NVHH 2025.

• Game Theory
• Formal Methods
• Controller Synthesis
• +۳ مورد دیگر

Thomas Brihaye is a Professor in the Mathematics Department at the University of Mons (UMONS) in Belgium and is affiliated with the Complexys Institute, a research center focused on complex systems. His academic position involves both teaching responsibilities and advanced research in theoretical computer science and applied mathematics. His primary research explores game theory and its applications across multiple domains including formal methods , controller synthesis , and urban planning . He investigates mathematical frameworks for decision-making in complex systems, with recent emphasis on renewable energy optimization, cybersecurity protocols, and stochastic process modeling. Key methodological approaches include Markov decision processes, timed automata, and equilibrium analysis in adversarial environments. Analysis of Brihaye's publications reveals consistent focus on: Theoretical foundations of game theory and computational complexity Applications in energy systems (renewable communities, grid management) Formal verification methods for security and system reliability Stochastic modeling and probabilistic systems His work bridges theoretical computer science with practical challenges in sustainability and infrastructure. Brihaye actively contributes to academic dissemination through: Regular presentations at international conferences (LATIN, RP, CONCUR, FORMATS) Educational outreach programs ('Mathipulations' workshops and public lectures) Interdisciplinary collaborations on urban systems and cognitive psychology projects