Find Academic Supervisors

Claudia FecarottiView profile

Assistant Professor

• Reliability Engineering
• Maintenance Modelling and Optimization
• Infrastructure Asset Management
• +6 more

Claudia Fecarotti is an Assistant Professor in Resilient Asset Management and Maintenance at Eindhoven University of Technology (TU/e), Netherlands, since January 2019. She is affiliated with the Operations, Planning, Accounting and Control Group (OPAC) within the Department of Industrial Engineering and Innovation Sciences, as well as EAISI and the 4TU Centre for Resilience Engineering. Prior to TU/e, she was a Research Associate at the University of Nottingham's Resilience Engineering Research Group (RERG), where she earned her PhD in Reliability Engineering and Infrastructure Asset Management in 2018. Education: BSc in Civil Engineering, University of Palermo, Italy MSc in Transportation Systems and Infrastructures, University of Palermo, Italy PhD in Reliability Engineering and Infrastructure Asset Management, University of Nottingham, UK Her research focuses on reliability engineering, maintenance modeling and optimization, and infrastructure asset management. She develops methodologies for planning, operating, and maintaining complex safety-critical systems (railways, fuel cells, offshore oil/gas, agricultural robots) to enhance performance and reduce costs. Her work bridges academic rigor with industrial relevance. Recent research trends include condition-based maintenance for multi-component systems, intervention planning for interconnected infrastructures, and digital tools for railway and modular construction systems. Her work aligns with UN Sustainable Development Goals for resilient infrastructure and sustainable cities. Scientific Awards: IMechE’s Best Young Researcher Award 2013 IMechE’s Donald Julius Groen Prize 2017 She is actively involved in projects like Modular prefabricated construction (2024–2027) and serves on the editorial board of the Journal of Infrastructure Systems (ASCE). Her expertise spans Petri nets, fault tolerance, and systems performance optimization.

Gautham Ramana MoorthyView profile

Researcher

• Digital Twin Technology
• Prefabricated Construction
• Logistics Optimization
• +11 more

Gautham Ramana Moorthy is a Doctoral Candidate at Eindhoven University of Technology (TU/e), affiliated with the OPaC group within the Department of Industrial Engineering and Innovation Sciences. His research focuses on integrating digital twin technology into prefabricated construction logistics to enhance sustainability and efficiency. Education: Master's in Industrial Engineering with Agile Management from École Centrale de Nantes; Bachelor's in Mechanical Engineering from SRM Institute of Science and Technology Research interests include: Optimization of logistics and supply chains in modular construction Digital twin applications for real-time data and predictive modeling Sustainable and data-driven construction management solutions Lean manufacturing principles for waste reduction Non-destructive quality control in cable production His current work contributes to the UN Sustainable Development Goals (SDGs), particularly in advancing sustainable industrial practices. He participates in projects like "Modular Prefabricated Construction IENW/BSK-2023/261229," collaborating with cross-disciplinary teams to develop circular asset management frameworks. His expertise spans process planning, asset management, and resource consumption optimization in industrial systems. He has contributed to research outputs such as a peer-reviewed conference paper analyzing digital twin-driven asset management in modular construction, reflecting his focus on bridging technology and operational efficiency.

Jacques de SwartView profile

Professor

• Bayesian Statistics
• Responsible AI
• Strategic Decision Making
• +5 more

Prof. Jacques de Swart is a Professor of Applied Mathematics at Nyenrode Business University, where he is part of the Faculty Research Center for Accounting, Auditing & Control. He holds a unique part-time role, dedicating one day per week to academia while serving as a Partner at PwC’s Consulting practice for the remaining four days. His expertise bridges mathematical rigor with business applications, focusing on audit processes, Bayesian statistics, and strategic decision-making aligned with ESG principles. Prof. de Swart’s academic journey includes a Mathematics degree from Utrecht University, with studies at La Sapienza University in Rome. He completed his PhD in Computational Science at the University of Amsterdam under the Centre for Mathematics and Computer Science (CWI). Later, he earned an MBA from Rotterdam School of Management, Erasmus University. His research interests revolve around Bayesian statistical methods, responsible AI integration, and strategic decision-making frameworks that prioritize environmental, social, and governance (ESG) considerations. He actively develops and teaches modules in machine learning, statistics, and programming, emphasizing their practical applications in auditing and business analytics. His publications highlight the application of Bayesian approaches to audit sampling and transparency, advocating for open-source tools to bridge auditors and statisticians. Recent work explores strategic decision-making frameworks that align business goals with sustainability and ethical practices. Earlier contributions include foundational research on computational methods for orbit calculations and Fekete point configurations. Prof. de Swart supervises students in their master’s thesis projects, fostering the next generation of analytical thinkers. His work reflects ongoing engagement with industry partnerships and data-driven innovation. He also chairs the Steering Group for Statistical Audit and the Watersportpark Ouderkerkerplas Foundation, advocating for accessibility in water sports for people with disabilities.

Mischa BeckersView profile

Lecturer

• Data Science
• Chemometrics
• Natural Language Processing
• +5 more

Mischa Beckers is a Data Science Lecturer affiliated with the ICT programme at HZ University of Applied Sciences. He holds a PhD from Radboud University Nijmegen (1997), where his research focused on chemometrics in structural analysis of biomacromolecules. His career includes roles at Kluwer Academic Publishers as an Electronic Publishing Specialist, focusing on Natural Language Processing and text mining, before joining HZ in 2005. At HZ, he has served as lecturer, lecturer-researcher, ICT research group project leader, and program coordinator, emphasizing curriculum development and accreditation. His work integrates data-driven decision-making into education and research, collaborating across disciplines and sectors. Research interests span data science applications in energy and water sectors, such as circular maintenance strategies and sewer system optimization (e.g., Riobase project). He leads the ICT research group, driving practical solutions for industry challenges through projects like Hybrid Force and sustainable maintenance practices. No specific grants or advising details are documented here. Labs/Teams: ICT Research Group at HZ University of Applied Sciences.

Evgeny PidkoView profile

Professor

• Inorganic Chemistry and Catalysis
• Computational Chemistry
• Reaction Mechanisms
• +7 more

Prof. Dr. Evgeny Pidko is a Full Professor and Chair of Inorganic Systems Engineering at the Department of Chemical Engineering, Faculty of Applied Sciences, Delft University of Technology (TU Delft), the Netherlands. He leads the Inorganic Systems Engineering (ISE) research group, focusing on theory-guided catalyst development and operando modeling in catalysis. He previously served as an Assistant Professor at Eindhoven University of Technology (2011–2017) before joining TU Delft as an Associate Professor in 2017 and being promoted to Full Professor in 2020. B.Sc./M.Sc.: Chemistry, Higher Chemical College of the Russian Academy of Sciences, Moscow Ph.D.: Computational Chemistry and Catalysis, Eindhoven University of Technology (2008), under Prof. Rutger van Santen His research integrates computational chemistry, theoretical modeling, and experimental approaches to unravel reaction mechanisms in complex chemical systems. Key areas include heterogeneous and homogeneous catalysis , inorganic functional materials , and sustainable chemical technologies . He emphasizes operando modeling to bridge theory and experiment, aiming to develop general-purpose strategies for catalyst design. His work spans CO2 hydrogenation, methane conversion, biomass upgrading, and plastic waste valorization. The recent publications reflect a strong trend toward data- and theory-driven catalyst design , molecular-level understanding of catalytic deactivation , and integration of computational screening with experimental workflows . His group actively explores non-critical metal catalysts (e.g., Mn, Fe, Co) to replace precious metals, supporting greener industrial processes. Projects like the ERC-funded DeLiCAT highlight his focus on the 'life and death' of catalysts, aiming to delay deactivation and improve efficiency. NWO-VENI Grant (2010) ERC Consolidator Grant (2016) Pidko plays an active role in the scientific community, serving on the advisory boards of ChemCatChem and Catalysis Science & Technology , and on the editorial boards of Kinetics and Catalysis and Mendeleev Communications . He advises on national science policy through roles in NWO committees and the Nationaal Platform Plastics Recycling. He supervises research students and contributes to MSc education in Heterogeneous Catalysis and Inorganic Materials . His lab, the EPiCs-Group , collaborates widely and maintains a strong focus on computational-experimental synergy.

Orest IftimeView profile

Associate Professor

• Applied Mathematics
• Control Theory
• Systems and Control
• +3 more

Orest Iftime is an Associate Professor in Applied Mathematics at the University of Groningen, affiliated with the Department of Economics, Econometrics, and Finance under the Faculty of Economics and Business. He holds a PhD from the University of Twente (2002) and has held academic positions since 2004, including roles at Delft University of Technology and the University of Groningen. His research focuses on control theory, systems and control engineering, optimization, and model reduction. Education: PhD (2002) and MSc/BSc from 'Al. I. Cuza' University, Iasi, Romania Awards: IEEE Outstanding Reviewer (2012), NWO Grants (2011–2022), Automatica Reviewer Award (2008) Research interests include moment matching, sliding mode control, PDE control, and robust control systems. Over 60 publications across conferences like CDC and ECC, and journals like Automatica. Active in teaching courses like Matrix Analysis, Stochastic Models, and Mathematics for Economics. Grants: Multiple NWO projects (2008–2022) Professional Experience: Postdoc (2002–2004), Lecturer/Researcher roles across institutions

Ielka van der SluisView profile

Senior Lecturer

• Human Communication
• Information Presentation
• Human-Computer Interaction
• +3 more

Dr. Ielka van der Sluis is a Senior Lecturer at the Department of Communication and Information Science, Faculty of Arts at the University of Groningen since 2011. She holds a PhD in Computational Linguistics from Tilburg University (2005) and has held research positions at Trinity College Dublin (2008–2011), the University of Aberdeen (UK), and the University of Twente. Her research focuses on human communication, multimodal interaction, natural language generation, and affective computing. She is a member of the Center for Language and Cognition Groningen and has contributed to projects like TUNA (EPSRC-funded), the OLIVE EC project, and the PAT framework for multimodal instruction analysis. Her work bridges computational linguistics and human-computer interaction, emphasizing the design and evaluation of multimodal systems. She has explored topics such as cross-linguistic referring expression generation, affective text impact, and procedural instruction design. Key contributions include developing the PAT annotation model for multimodal instructions and investigating cross-cultural assessment of automated referring expressions in virtual environments. Her research history spans over two decades, with impactful contributions to the understanding of text-picture alignment in procedural instructions, action categorization in multimedia, and user-centric evaluation frameworks. She collaborates internationally, particularly in computational linguistics and next-generation localization technologies.

Kenny MeestersView profile

Lecturer

• Crisis Information Management
• Cybersecurity in Crisis Response
• Decision-Making in Crises
• +3 more

Kenny Meesters is a Lecturer and Researcher at Tilburg University's Department of Information Systems and Operations Management within the Tilburg School of Economics and Management (TiSEM). His work focuses on crisis information management, cybersecurity in disaster response, and the role of information systems in enhancing societal resilience during crises. He holds a background in Business Engineering with master’s degrees in Information Management and Strategic Management from Tilburg University. Education: Master’s in Information Management, Tilburg University Master’s in Strategic Management, Tilburg University Background in Business Engineering Research Interests: Kenny investigates how information systems bridge gaps between communities, volunteers, and formal responders during crises. His work emphasizes cybersecurity challenges, decision-making tools, and the paradox between information system flexibility and rigidity in crisis contexts. Key Contributions: He has published extensively on topics like crisis exercise design (via Delphi studies), information awareness models, and cybersecurity in crisis response. His 2025 paper in Safety Science offers expert-derived recommendations for tabletop crisis exercises. Awards: Teaching Best Teacher BSc & Premaster Programs (2021) Excellent Teacher (Academic Competences course, 2022) External Roles: Board Member, Fire Fighters without Borders (2023–present) Consultancy at Seginus (2022–present) UNDAC Member, United Nations (2021–present) Education Roles at Avans University of Applied Sciences and Campus Vesta

Eric PauwelsView profile

Researcher

• Operations Research
• Transportation Systems
• Machine Learning
• +3 more

Eric Pauwels is a Scientific Staff Member at Centrum Wiskunde & Informatica (CWI) in Amsterdam, The Netherlands, affiliated with the Intelligent and Autonomous Systems department. His research spans interdisciplinary domains including transportation systems, energy markets, and behavioral economics. Key Research Areas: Transportation demand modeling, machine learning applications in mobility, reinforcement learning for cooperative systems, and energy systems optimization. Active Projects: ALIGN4energy (aligning citizen behavior with systems), Energy Intranets (NEAT project), and industrial collaborations like Impactstudie Noord/Zuidlijn. Scientific Contributions: 2005 ERCIM Best Working Group Prize recipient, with expertise in discrete choice modeling, wavelet analysis, and production scheduling optimization. Publications: Recent work focuses on bicycle-train integration, electric vehicle bidding frameworks, and CKLS financial process analysis. Contact: Email Eric.Pauwels@cwi.nl , Phone +31 20 592 4225 (Room M358).

Syed Hassan ShahView profile

Adjunct Professor

• Wireless Networks
• Cyber-Physical Systems
• Smart Cities
• +7 more

Dr. Syed Hassan Shah is a distinguished adjunct faculty member at California State University, Fullerton's Department of Computer Science, where he teaches graduate-level courses. Concurrently, he serves as a Wi-Fi connectivity subject matter expert and Product Director for Short Range Technologies at Quectel Inc., and previously held roles as Product Manager for Mobile & Compute Connectivity at Qualcomm Inc., focusing on Mi-Fi, CPE, and UWB technologies. Ph.D. in Computer Science & Engineering, Kyungpook National University, South Korea (2013-2017) BS in Computer Science, Kohat University of Science & Technology, Pakistan (2007-2012) Dr. Shah's research spans interdisciplinary domains in Wireless Communications , Cyber-Physical Systems , and Smart Cities , with significant contributions to Vehicular Networks , Internet of Things , and Future Internet Architectures . His recent publications demonstrate expertise in Neural Networks , Optimization Theory , and Security & Privacy applications. Scientific recognition includes: Qualcomm Innovation Award (2016) IEEE Senior Member (2018) ACM Distinguished Speaker (2018) Best Research Contribution Award (Brain Korea, 2016) Multiple travel grants from ACM and IEEE KNU Honors Scholarship (2013) Dr. Shah actively contributes to academic governance as: Editorial Board Member for 60+ special issues in top-ranked journals TPC Member for 100+ international conferences including IEEE Globecom and ACM MobiHoc IEEE Vehicular Technology Society Board appointee (2018-2019)

Juseong LeeView profile

Assistant Professor

• Predictive Maintenance
• Industrial Engineering
• Artificial Intelligence
• +5 more

Juseong Lee is an Assistant Professor at the Eindhoven University of Technology (TU/e), affiliated with the Department of Industrial Engineering and Innovation Sciences. His research focuses on integrating data-driven models and artificial intelligence into industrial processes, with a specific emphasis on predictive maintenance approaches for engineering systems. PhD in Aerospace Engineering from Delft University of Technology (2022) MSc and BSc in Aerospace Engineering from Korea Advanced Institute of Science and Technology (2018, 2016) His work employs methodologies such as digital twins, multi-objective optimization, and deep learning to enable real-time decision-making in business contexts. He aims to improve the reliability, efficiency, and sustainability of Industry 4.0 systems through his research. Recent publications highlight his expertise in predictive maintenance, with applications to aircraft systems, landing gear brakes, and turbofan engines. Key techniques include Gaussian process learning, adaptive sampling, deep reinforcement learning, and stochastic Petri nets. These studies often involve collaborations with researchers like Mihaela Mitici. Lee's research is supported by the European Union's Horizon 2020 program (Grant No. 769288). He teaches courses on quality and reliability engineering, maintenance optimization, and service logistics.

Zoran KapelanView profile

Professor

• Urban Water Infrastructure
• Hydroinformatics
• Water Distribution Systems
• +4 more

Professor Zoran Kapelan serves as Chair of Urban Water Infrastructure within the Department of Water Management at Delft University of Technology's Faculty of Civil Engineering and Geosciences. With over 30 years of experience in water engineering, he joined TU Delft in 2018 after leading the Water and Environment Group at the University of Exeter for 19 years, following a decade in international consultancy. His research spans smart water systems, hydroinformatics, and sustainable urban water infrastructure management. Key focus areas include AI-driven solutions for drinking water distribution (leakage detection, pressure management), sewer systems optimization (blockage prediction, sustainable drainage), asset management, and flood risk assessment. He pioneers methodologies integrating artificial intelligence, real-time control, and decision-making under uncertainty to address climate change adaptation and circular economy principles in water systems. Recent publications (2024-2025) reveal strong trends in deep learning applications for infrastructure monitoring (sewer crack detection, floating litter quantification), resource recovery assessment frameworks, and advanced modeling of non-Newtonian fluid dynamics in wastewater systems. His work increasingly emphasizes circular economy metrics, environmental risk assessment of novel materials, and co-developed sustainable solutions through serious gaming approaches. Editor, Journal of Water Resources Planning and Management (ASCE) Associate Editor, Water Resources Research Member, IWA Digital Water Steering Committee Member, External Scientific Advisory Council of KWR Prof. Kapelan has secured over €10 million in research funding across 50+ EU, RCUK, and industry grants. His supervision portfolio includes 40+ PhD students and 25+ postdocs, with significant industry impact through commercialized technologies like AI-based pipe burst detection systems deployed by United Utilities serving 7 million customers. He coordinates TU Delft's Urban Drainage and Water Management course while contributing to asset management and water transport curricula. The Urban Water Infrastructure group under his leadership maintains strong industry partnerships with water utilities globally, focusing on translating research into operational solutions for real-time monitoring, predictive maintenance, and climate-resilient infrastructure design.

Hadi HajibeygiView profile

Professor

• Multiphase Flow in Porous Media
• Multiscale Modeling and Simulation
• Subsurface Hydrogen Storage
• +8 more

Hadi Hajibeygi is a Professor of Geo-Energy Solid and Fluid Mechanics at Delft University of Technology, leading subsurface storage research and multiscale modeling initiatives. He serves as the Subsurface Storage Theme Lead (2016–present) and Energi Simulation Chair holder (2022–present), with a focus on underground hydrogen storage, CO2 sequestration, and geothermal energy systems. His research integrates multiphase flow in porous media , multiscale simulation , and geomechanical stability , supported by NWO-Vidi and Interpore awards. He leads the DARSim and ADMIRE projects, developing frameworks like Adaptive Dynamic Multiscale Integration and pEDFM-U for fractured reservoirs. Key awards include: Interpore Award for Porous Media Research (2021) NWO-Vidi Laureate (2019) Interpore Rosette (2017) ETH Zurich PhD Medal (2012) TU Delft Innovative Teaching Talent (2018) His teaching portfolio spans Dynamics of Solids and Fluids , Numerical Methods for Subsurface Simulation , and Multiscale Modeling , while advising a team of postdocs and PhD candidates on projects spanning induced seismicity, microbial interactions, and fractured reservoir mechanics.

• Process Mining
• Process Modelling
• Conceptual Modelling
• +5 more

Jan Martijn van der Werf serves as Associate Professor in Process Science at Utrecht University's Faculty of Science, Department of Information and Computer Science. Since September 2022, he has held the position of Programme Director for the Bachelor Information Sciences, overseeing curriculum development and academic operations for both Business Informatics and Information Sciences programs. Education: Dual PhD in Computer Science from Eindhoven University of Technology and Humboldt Universität zu Berlin (Thesis: 'Compositional Design and Verification of Component-based Information Systems') Research Focus: Van der Werf's work centers on process mining and behavioral modeling in software architectures, with emphasis on the interplay between data and processes. His expertise spans Conceptual Modelling of Information Systems , Enterprise Architecture , and Service-Oriented Architecture , addressing challenges in process discovery, verification, and practical implementation within complex organizational contexts. Current research explores the human dimensions of process mining adoption and AI-driven event log extraction. Publication Trends: Recent work (2023-2024) reveals increasing focus on methodological rigor in process discovery, human factors in process mining initiatives, and formal verification techniques for Petri nets. His publications bridge theoretical foundations with practical applications, particularly in event log extraction using large language models and visualization of complex process chronologies from heterogeneous data sources. Academic Contributions: Van der Werf teaches core courses in Process Modelling and Software Architecture , actively participates in academic workshops (including the 2020 'Information System Modeling' workshop), and supervises graduate research. His Scopus profile indicates 77 research outputs and supervision of 3 students, reflecting sustained scholarly engagement in process science and information systems.

Yingqian ZhangView profile

Associate Professor

• Artificial Intelligence
• Machine Learning
• Deep Reinforcement Learning
• +7 more

Yingqian Zhang is an Associate Professor in the Information Systems group at the Industrial Engineering and Innovation Sciences department of Eindhoven University of Technology (TU/e). She is affiliated with the Eindhoven Artificial Intelligence Systems Institute (EAISI), specifically with the EAISI High Tech Systems and EAISI Foundational groups. Her research focuses on applying Artificial Intelligence to solve complex decision-making problems across various domains including logistics, transportation, manufacturing, and e-commerce. Dr. Zhang received her PhD in Computer Science from the University of Manchester, UK. Prior to joining TU/e, she served as an Assistant Professor in the Econometrics Institute at Erasmus University Rotterdam and as a postdoc researcher in the Algorithmics group at TU Delft. She was also a visiting professor at the Institute for Advanced Computer Studies at University of Maryland, College Park, USA. Her research expertise lies at the intersection of Artificial Intelligence and optimization, with particular focus on machine learning, deep reinforcement learning, and trustworthy data-driven optimization. Dr. Zhang develops socially aware algorithms that can optimize decisions in data-rich environments. Her work bridges the gap between theoretical AI advancements and practical applications in industrial settings, addressing real-world challenges through innovative algorithmic solutions. She is particularly interested in how AI can support human decision-making while maintaining transparency and trustworthiness. Dr. Zhang's recent publications reveal a strong trend toward applying graph neural networks and reinforcement learning to complex scheduling and optimization problems. Her work demonstrates increasing sophistication in handling stochastic elements in decision-making processes, with applications spanning healthcare diagnostics, logistics, transportation, and manufacturing. She has made significant contributions to the field of neural combinatorial optimization, particularly for job shop scheduling problems and vehicle routing. Dr. Zhang has received several prestigious awards recognizing her contributions to the field: Winner of the MLVRP2023 GECCO competition (2023) Best Paper Award from Omega-International Journal of Management Science (2017) Best Industrial Paper Award (2020) Best Student Paper Award (2019) Best Student Paper Award of ICAART 2022 (2022) As a dedicated mentor, Dr. Zhang supervises numerous PhD students including Mohsen Abbaspour Onari, Abdo Abouelrous, Luca Begnardi, Xia Jiang, Chengpeng Hu, Minshuo Li, Robbert Reijnen, Jesse van Remmerden, Bart von Meijenfeldt, Ya Song, and Igor Smit. Her research is supported by various grants, including the LEO (Learning and Explaining Optimization) project co-funded by Holland High Tech | TKI HSTM via the PPP allowance scheme for public-private partnerships. Dr. Zhang actively contributes to the academic community as the Chair of the Benelux Association for Artificial Intelligence (BNVKI) and as a member of the Technical Board for the European Big Data Value Association (BDVA). She serves as an associate editor for the "Annals of Mathematics and Artificial Intelligence" journal and participates in the technical Program Committee for major AI conferences such as IJCAI, AAAI, AAMAS, and ECAI. She is also on the executive committee of the Data Science meets Optimisation (DSO) working group of EURO to promote collaboration between AI and Operations Research communities.