Find Academic Supervisors

Roel C.G.M. LoonenView profile

Associate Professor

• Building Performance Simulation
• Energy Engineering
• Adaptive Facades
• +7 more

Roel C.G.M. Loonen is an Associate Professor at the Unit Building Physics and Services within the Department of the Built Environment at Eindhoven University of Technology (TU/e), Netherlands. He holds joint appointments with EAISI High Tech Systems and EIRES Research groups, focusing on building performance simulation and energy systems. His work bridges academic research with practical applications through collaborations with SMEs in the building industry. Loonen received his BSc and MSc (cum laude) in Building Services from Eindhoven University of Technology, followed by a PhD in 2018 with a dissertation on 'Approaches for computational performance optimization of innovative adaptive facade concepts.' His educational background has positioned him as a leading expert in building performance simulation and sustainable building technologies. His research interests center on developing and applying modeling and simulation strategies to support decision-making for designing buildings that combine high indoor quality with minimal environmental impact. Key areas include adaptive facades, building-integrated renewable energy systems, and energy-efficient building envelopes. He specializes in creating and validating new building performance simulation models to advance innovative building technologies. His recent publications demonstrate a strong focus on practical applications of building performance simulation, with emphasis on residential energy efficiency, photovoltaic systems, and occupant-centered approaches to building design. The work shows increasing integration of machine learning techniques with traditional building simulation methods, particularly for sensitivity analysis and optimization of building performance. REHVA Young Scientist Award (2021) Best PhD supervisor award from Department of the Built Environment, TU/e (2018) First prize - REHVA International student competition (2011) Smart daylight control for optimal building performance (NWO Take-off award, 2018) Best paper award (2021) Loonen actively supervises PhD and Master's students, evidenced by his Best PhD Supervisor Award in 2018. He manages multiple research projects including Sustainable Summer Comfort (2024-2027), Modeling Innovative Use Scenarios for Future Domestic Comfort (2023-2026), and Just Prepare (2022-2026), with funding from sources including the Dutch Research Council (NWO). His professional service includes being a board member of the Dutch-Flemish IBPSA affiliate and co-chair of IBPSA World's website committee, plus reviewing for 35 academic journals. He leads research within the Building Performance group, focusing on creating practical tools and methodologies that bridge the gap between theoretical building performance models and real-world implementation in the construction industry. His work particularly emphasizes the integration of occupant behavior and practices into building performance models, recognizing that human factors are critical to achieving sustainable building performance in practice.

• Artificial Intelligence
• Natural Language Processing
• Human-AI Interaction
• +4 more

Khiet P. Truong is an Associate Professor affiliated with the Digital Society Institute and the Human Media Interaction group. Their research focuses on the intersection of artificial intelligence, robotics, and human-computer interaction, with particular emphasis on speech emotion recognition, conversational agents for children, and multimodal interaction analysis. Recent work includes exploring how robots can restore trust through apologies, benchmarking Dutch automatic speech recognition systems, and developing child-friendly interfaces for cultural heritage archives. Truong has also investigated physiological signals like laughter and stress markers in speech across diverse contexts. Scientific Awards : Best Functional Design Award (2019) Research Trends : Analysis of speech patterns, emotion recognition, robot-human dialogue, and multimodal behavioral cues dominate their recent publications. Key subfields include Dutch language processing, laughter classification, trust indicators in child-robot interactions, and healthcare applications of speech technology. Academic Activities : Chair of the 26th ACM International Conference on Multimodal Interaction (2024) Examiner roles for PhD defenses and research evaluations (2024–2023) Contributions to workshops on emotion representation and social signal processing

Roel LoonenView profile

Associate Professor

• Adaptive facades
• Building-integrated renewable energy
• Energy efficiency in buildings
• +3 more

Roel Loonen is an Associate Professor at the Unit Building Physics and Services within Eindhoven University of Technology's Department of the Built Environment. Since October 2024, he has joined the EIRES Management Team, leading the Energy Transition in the Built Environment focus area alongside Lenneke Kuijer. His work emphasizes integrating energy efficiency with occupant comfort through advanced building simulation techniques. Academic Affiliation: Eindhoven University of Technology Management Role: EIRES Management Team Research Focus: Adaptive facades, building-integrated renewable energy, and occupant behavior modeling Loonen’s research explores modeling and simulation strategies for buildings that reconcile high indoor quality with minimal environmental impact. Key projects include collaborations with eyrise on solar shading glass and TNO on the ZIEZO project, which experiments with insulated glazing units that combine solar shading with bifacial photovoltaics at the SolarBEAT facility. His work spans computational methods for urban irradiation, occupant-facade interaction frameworks, and multi-domain thermal comfort modeling. The ZIEZO project exemplifies his approach to energy-efficient design by redirecting reflected light to enhance photovoltaic output while maintaining daylight comfort. His publications address challenges in adaptive façade systems, PV integration, and sensitivity analysis for heating demand. Loonen advocates for interdisciplinary collaboration to bridge technical innovation with societal implementation needs. Loonen’s educational contributions include co-teaching the interdepartmental master course Sustainable Energy Technology and developing interactive simulation-based teaching tools. He emphasizes connecting energy-related research to practical implementation through stakeholder engagement with municipalities, building companies, and grid operators. Key facilities involved in his research include SolarBEAT (for testing solar technologies) and TU/e’s simulation laboratories. His work addresses urban energy transitions by combining building physics with grid interactions, occupant behavior, and scalable PV system optimization.

Tiziano De MatteisView profile

Assistant Professor

• Parallel and Distributed Computing
• High-Performance Computing
• Energy Efficiency in Computing
• +4 more

Tiziano De Matteis is an Assistant Professor in the @Large Research group at Vrije Universiteit Amsterdam's Faculty of Science, Department of Computer Systems. He also holds an affiliation with the Network Institute. His research focuses on overcoming post-Moore architecture challenges through parallel and distributed computing, high-performance systems, energy efficiency, and FPGA applications. Previously, he was a PostDoc at ETH Zurich's SPCL Group and earned his MSc/PhD from the University of Pisa. Education PhD in Computer Science, University of Pisa MSc in Computer Science, University of Pisa Research Interests Post-Moore architectures for distributed ecosystems Energy-aware parallel computing High-level abstractions for parallel software development FPGA-based hardware acceleration Data stream processing and distributed systems Recent Research Trends Recent work emphasizes: Data center risk analysis and sustainability Optimizing microservices and distributed scheduling LLM model offloading to NVMe storage Python-based data-centric programming productivity GPU interconnect performance in supercomputing Grants & Projects Participates in the EU-funded 'Extreme and Sustainable Graph Processing' project (2023-2025), exploring scalable graph algorithms and energy-efficient computing systems. Teaching Accelerator-Centric Computing Ecosystems Computer Organization Distributed Systems Systems Seminar

• Deep Learning
• Neural Networks
• Artificial Intelligence
• +9 more

Elena Mocanu is an Assistant Professor in the Department of Datamanagement & Biometrics and a faculty member of the Digital Society Institute. Her research focuses on advancing neural network architectures, particularly through dynamic sparse training techniques to enhance computational efficiency and model performance. Key areas include deep reinforcement learning applications in building energy optimization, federated learning for collaborative data environments, and sparse connectivity models that reduce resource usage without sacrificing accuracy. She has contributed to frameworks like the Digital Twin for autonomous driving and energy systems, emphasizing sustainability and scalability. Her work bridges theoretical advancements and practical implementations, addressing challenges in energy-efficient AI, robust noise filtering in reinforcement learning, and feature selection for medical imaging tasks. She actively organizes conferences such as ICLR workshops on sparsity in neural networks and IJCAI events, fostering interdisciplinary collaboration in artificial intelligence. Awards : Best Paper Award at AAMAS 2022 Workshop, ICML 2022 Outstanding Reviewer Award Conference Leadership : Organized ICLR 2023 Sparsity Workshop, EPIA 2023/2022 Conferences Research highlights include scalable training methods inspired by network science, energy optimization in smart buildings, and sparse ensembling techniques that achieve efficiency gains without overhead. Her contributions span foundational machine learning theory to applied domains like smart grids and autonomous systems.

• Civil Engineering
• Infrastructure Maintenance
• Climate Change Adaptation
• +3 more

Irina Stipanovic is an Assistant Professor specializing in Market Dynamics, focusing on infrastructure maintenance, climate change adaptation, and railway systems. Her research integrates advanced technologies like Digital Twins and machine learning to enhance decision-making in civil engineering contexts. Her work addresses critical challenges in infrastructure management, including risk-based maintenance scheduling, structural health monitoring, and flood resilience. She explores innovative methods such as entity-embedding neural networks and vision-based 3D inspections to improve predictive maintenance and asset lifecycle management. Key themes in her research include: Railway earthwork maintenance under climate change Multi-objective decision models for infrastructure prioritization Integration of Structural Health Monitoring (SHM) into Digital Twin platforms Resilience planning for critical infrastructure against floods and other hazards She has contributed to EU initiatives on standardization of Digital Twin applications and has published extensively on railway, tunnel, and bridge management. Her work emphasizes data-driven approaches to sustainable infrastructure solutions.

• Human-Computer Interaction
• Collaborative and Social Computing
• Computer Supported Cooperative Work
• +7 more

Dr. Ioanna Lykourentzou is an Associate Professor in the Software Technology for Learning and Teaching department at Utrecht University's Faculty of Science. She leads the Collaborative Technologies Lab and coordinates the Computing Science Master's and Information Sciences Honors Bachelor's programs. Additionally, she serves as a Fair Data and Software fellow within the Open Science Team of the Faculty of Science and as a member of the Ethics Review Board for the Faculties of Science and Geosciences. Her research focuses on collaborative and crowd systems, developing methods that help people work together, coordinate efforts, and innovate at scale, both online and in physical spaces. Her interdisciplinary approach combines computational science (machine learning, agent-based modeling, mathematical optimization) with social sciences (personality testing, team building). Her expertise spans Human-Computer Interaction, Algorithms, Agent-Based Modelling, Telecollaboration, Creativity, and Innovation. Her recent publications (2021-2025) demonstrate a strong focus on human-AI interaction, generative models, and applications in cultural heritage and education. She examines how technology can facilitate collaboration, with particular attention to team formation, personality factors, and digital nudging techniques. Her work bridges theoretical research with practical applications in digital humanities, cultural heritage, and computing education. Dr. Lykourentzou has received significant recognition for her research, with multiple publications garnering substantial citations and reader attention across platforms like Mendeley and social media. Her work on personality-based team formation (2016) has been particularly influential with over 90 citations. Prior to joining Utrecht University, she worked as a Senior Researcher at the Luxembourg Institute of Science and Technology (LIST), where she coordinated the European H2020 project CROSSCULT. She has also collaborated with the Human-Computer Interaction Institute of Carnegie Mellon University as a visiting researcher and with INRIA Nancy-Grand Est and the Public Research Center Henri Tudor as a postdoctoral fellow.

• Scientific Visualization
• Computer Graphics
• Flow Estimation and Interpolation
• +7 more

Dr. Steffen Frey is an Assistant Professor in the Scientific Visualization and Computer Graphics group within the Bernoulli Institute at the University of Groningen's Faculty of Science and Engineering. He also maintains an affiliation with the Faculty of Medical Sciences/UMCG in the Robotics and image-guided minimally-invasive surgery (ROBOTICS) research group. His work bridges computer science with practical applications in medical and geoscientific domains. His research interests focus on scientific visualization, computer graphics, and interactive visualization techniques. Dr. Frey specializes in developing novel methods for flow estimation, temporal interpolation, parameter sensitivity analysis, and visualization of complex scientific data, particularly in porous media and fluid dynamics. His work often involves creating scalable solutions for big data visualization problems and applying visualization techniques to medical applications such as bone cement simulation. Analysis of his recent publications reveals a strong focus on machine learning approaches to scientific visualization, particularly in temporal interpolation and ensemble data analysis. His work combines traditional computer graphics techniques with modern deep learning methods to solve challenging visualization problems in scientific domains. The research demonstrates increasing sophistication in handling complex multi-dimensional datasets while maintaining interactive performance. 2019 IEEE Scientific Visualization Contest Winner Dr. Frey actively collaborates with researchers internationally, as evidenced by his co-authorship with scientists from various institutions worldwide. His work contributes to multiple Sustainable Development Goals, particularly those related to clean water and sanitation through his porous media flow research. He has supervised multiple students through research projects and thesis work, though specific names are not listed in the provided materials.

• Computational polymer physics
• Soft matter
• Nanoscale materials design
• +7 more

Andrea Giuntoli is an Assistant Professor at the Micromechanics group within the Faculty of Science and Engineering at the University of Groningen . He holds a PhD in Computational Soft Matter and Polymer Physics from the University of Pisa (2018), followed by postdoctoral work at NIST (2018-2019) and Northwestern University (2019-2021) under the ChiMaD project (part of the Material Genome Initiative). His research focuses on theoretical and computational modeling of nanoscale building blocks for advanced polymer composites , particularly in controlling mechanical properties, impact resistance, and self-healing through polymer architecture and graphene dispersion. He has secured significant grants including a VENI grant (2022) and an NWO-XS grant (2022). Key research trends from his recent publications (2021-2025) include machine learning-optimized coarse-graining , energy renormalization methods , impact-resistant coatings , graphene-polymer interfaces , and self-healing polymer glasses . His work bridges materials science , computational physics , and applied polymer engineering . Scientific Awards: VENI Grant (2022) NWO-XS Grant (2022) He actively collaborates across institutions (USA, Netherlands) and disciplines, with research impacts in medical devices , advanced materials , and surface science . His lab at the Zernike Institute for Advanced Materials integrates multi-scale modeling with experimental validation to enhance polymer composite performance.

Lisanne HavingaView profile

Assistant Professor

• Sustainable Building Renovation
• Machine Learning for Building Performance
• Energy Systems
• +3 more

Lisanne Havinga is an Assistant Professor at the Department of Built Environment, Eindhoven University of Technology (TU/e), specializing in sustainable housing renovation and building performance simulation. She actively contributes to the Renovation Explorer project, a decision-making tool leveraging machine learning and dynamic modeling to optimize energy efficiency in residential buildings.

Wilfried van SarkView profile

Professor

• Solar Energy
• Smart Grids
• Photovoltaics
• +5 more

Wilfried van Sark is a Professor of Solar Energy Integration at the Copernicus Institute of Sustainable Development, Utrecht University. He specializes in photovoltaics, smart grids, and renewable energy systems. With over 35 years of experience, his research focuses on solar energy integration, including building-integrated photovoltaics, offshore floating PV systems, and smart grid technologies. Education: M.Sc. in Experimental Physics (1985), Utrecht University Ph.D. in III-V Solar Cell Development (Nijmegen University) Research Interests: Photovoltaic module performance and life cycle analysis Solar forecasting and energy yield optimization Offshore and floating solar systems Smart grid integration and electric mobility Publications & Roles: Over 200 peer-reviewed publications and four co-edited books Associate Editor of Solar Energy and Frontiers in Energy Research Member of IEEE, ISES, and organizing committees for global PV conferences Key Contributions: Pioneered research on offshore floating PV systems Developed spectral shifting processes for next-gen photovoltaics Advocated for data-driven solar energy policy and grid management

Erik SchlangenView profile

Professor

• Civil Engineering
• Materials Science
• Self-Healing Materials
• +6 more

Erik Schlangen is a Professor in the Chair of Experimental Micromechanics at the Delft University of Technology , affiliated with the Faculty of Civil Engineering and Geosciences and the Department of Materials, Mechanics, Management & Design (3MD) . He leads the Materials and Environment section, focusing on experimental techniques for material characterization and computational modeling. Guest Professor at Southeast University, Nanjing, China (2015–present) Director at Sekans b.v. (2025–2027) His research spans self-healing materials , 3D printing of concrete , micromechanics , and computational modeling . He pioneered self-healing asphalt using induction heating and holds an ERC Advanced Grant for the MAGICON project on self-healing infrastructure. Recent publications analyze filament stitching for 3D-printed composites , piezoelectric sensors for fatigue monitoring, and machine learning for cement microstructure generation . His work emphasizes sustainability and durability in construction materials, with applications to concrete and asphalt. Scientific Awards ERC Advanced Grant (MAGICON) Editorial Roles Editor-in-Chief (Europe) of Advances in Concrete Construction Editor of Construction and Building Materials (10 years) Editorial Board of Cement & Concrete Composites

Davide Dell'AnnaView profile

Assistant Professor

• Human-centered Artificial Intelligence
• Human-AI Collaboration
• Social and Responsible AI
• +3 more

Davide Dell'Anna is an Assistant Professor in the Responsible AI group of the Department of Information and Computing Sciences at Utrecht University. He is a member of the Hybrid Intelligence Centre, a 10-year program funded by the Dutch Ministry of Education, Culture and Science through NWO. His academic journey includes a Ph.D. from Utrecht University (2021), a Master's degree from the University of Turin (2016), and prior postdoctoral positions at Delft University of Technology (2021-2023) and within the Hybrid Intelligence Centre (2023-2024). Dr. Dell'Anna's research focuses on developing methodologies and solutions for Artificial Intelligence systems to cooperate synergistically and proactively with humans. His work specifically emphasizes automated and data-driven mechanisms that account for human intentionality and expertise to ensure AI behaviors are aligned with human norms and values. His research spans multiple domains including healthcare, social computing, and transportation, with applications in dementia therapy, epidemic simulation, and human-robot interaction. His scholarly output demonstrates a consistent focus on Human-centered AI, Norm-aware Systems, and Hybrid Intelligence. His recent publications explore quality models for Hybrid Intelligence teams, social norm-aware robot architectures, consent mechanisms for responsible autonomy, and replication practices in Requirements Engineering. His work bridges theoretical foundations with practical applications, particularly in healthcare contexts. Distinguished PC Member award - AAMAS 2025 (recognizing 35 out of 684 PC members, 5.1%) "Quality Champion" PC award - ECAI 2023 (recognizing 58 out of 700 eligible PC members, 8.3%) Outstanding PC member award - AAMAS 2023 (recognizing 16 out of 436 PC members, 3.7%) Dr. Dell'Anna actively supervises students and has mentored numerous Master's students including Karpínski, van Lindonk, Willems, and Brigola. He has secured competitive research funding including an NWO Open Competition Domain Science - XS Grant (€50,000) for developing human-like norm-aware cognitive robots. He serves as Associate Editor for CEUR-WS and co-chairs major international workshops including COINE@AAMAS 2025 and HHAI 2025, demonstrating significant leadership in the AI research community.

Veronika CheplyginaView profile

Associate Professor

• Machine Learning
• Medical Imaging
• Artificial Intelligence Ethics
• +3 more

Veronika Cheplygina is an Associate Professor at the IT University of Copenhagen, specializing in machine learning applications for medical imaging and improving reproducibility in AI research. Formerly affiliated with Eindhoven University of Technology, her work critiques current practices in ML deployment, focusing on dataset quality, algorithmic fairness, and ethical AI. She leads the DASYA research group and advocates for open science, mentoring initiatives, and inclusive academic environments. Her research bridges theoretical advancements with practical clinical applications, addressing issues like spurious correlations in medical imaging models and the impact of dataset biases on model performance. Key research interests include: Evaluating robustness of medical AI systems Addressing dataset shortcomings and transferability Mitigating biases in algorithmic decision-making Improving validation practices in machine learning Promoting transparency in AI development Her recent work highlights how algorithms may exploit artifacts in medical images (e.g., scanner settings) rather than clinically relevant features, emphasizing the need for rigorous validation frameworks. She actively participates in interdisciplinary collaborations, including the Danish Reproducibility Network, to foster peer support and methodological rigor.

Vasilis SouliosView profile

Researcher

• Building Renovation
• Energy Efficiency
• Sustainable Building Envelopes
• +3 more

Vasilis Soulios is a post-doc researcher in Building Performance at Eindhoven University of Technology (TU/e), specializing in energy-efficient building renovation. His work focuses on optimizing internal insulation techniques through hydrophobization of masonry walls, addressing climate adaptation and energy transition challenges. He holds a PhD in Civil Engineering from AAU Copenhagen, with prior roles including EU Project Manager for green energy initiatives. Academic Background: PhD from AAU Copenhagen (2017-2021), part of the RIBuild Horizon 2020 project, collaborating with 10 European partners. Previously at KU Leuven as a Research Engineer. Currently involved in the 'Renovation Explorer' project to strategize sustainable building renovations in the Netherlands. Research Interests: Sustainable building envelopes, internal insulation optimization, hygrothermal performance, and integration of renewable energy sources. His work aligns with UN SDGs for climate action and sustainable cities. Key Projects: Renovatieverkenner (2022-2026), MMIP Integrale Energietransitie Bestaande Bouw (2019-2025). Outputs include guidelines for historic building insulation and dynamic modeling frameworks for renovation strategies.