Prof. Moniek Buijzen is an Erasmus University Professor of Communication and Change, focusing on integrating AI into society and promoting healthy behaviors through digital media. She leads initiatives like the Movez Network, AiPact, and AICON, emphasizing cross-sector collaboration between science, art, and society. Her work bridges theory, technology, and law, with a total team science approach. Education and Career: - PhD from University of Amsterdam (2003) - Former professor and chair of Communication Science at Radboud University (2012–2019) - Currently at Erasmus University's School of Social and Behavioural Sciences. Research Focus: - Digital technology's role in youth well-being and health campaigns. - Ethical AI integration and societal impact. - Peer influence and social network interventions. Awards and Grants: - Vici, Vidi, Veni grants from NWO. - ERC Consolidator Grant. - Honorary Fellow of the International Communication Association. Grants and Collaborations: - Principal investigator in AlgoSoc (10-year national program). - SocialMovez project on health campaigns via peer influencers. - Founded Movez Network and Bitescience.com with Esther Rozendaal. Labs/Teams: - Movez Network: Promotes media literacy and health among youth. - AiPact: Erasmus Initiative on AI's societal impact. - AICON: Art-driven AI ethics initiative.
Dr. Silvia Rossi is a postdoctoral researcher in the Distributed and Interactive Systems (DIS) group at Centrum Wiskunde & Informatica (CWI) in the Netherlands. Her work focuses on user behavior analysis and system design for immersive multimedia systems like volumetric video in Extended Reality (XR) applications. She earned her PhD from University College London (UCL) in the Learning and Signal Processing (LASP) group , where she developed clustering algorithms to analyze user navigation patterns in VR systems. Her research bridges human-centric behavioral studies with technical solutions for Quality of Experience (QoE) in 6-DoF VR platforms. Recent work presented at conferences like IEEE VR and ACM Multimedia explores how spatial constraints affect user movement, open-source social VR systems ( VR2Gather ), and behavioral data collection tools. She co-organizes key events like the Spring School on Social XR and chairs QoMEX 2025 sessions. Scientific Recognition: 2023 ACM SIGMM Award for Outstanding PhD Thesis 2022 Lombardi Prize for best UCL EEE doctoral thesis Dr. Rossi's publications highlight trends in XR user modeling , adaptive streaming , and social VR design , with keywords spanning computer science , human-computer interaction , and multimedia engineering . She collaborates extensively with researchers like Pablo Cesar and Irene Viola , and contributes to open-source frameworks in immersive communication.
Dr. Inez Zwetsloot is a Visiting Professor in the Business Analytics section at the Faculty of Economics and Business , University of Amsterdam. Her work bridges statistical quality control, machine learning, and data-driven decision-making across diverse domains. Focuses on adaptive monitoring techniques for complex systems Integrates AI into traditional quality control frameworks Explores social media dynamics in financial markets Her recent research emphasizes real-time anomaly detection in high-dimensional data, dynamic social network analysis , and robust control chart methodologies . She also contributes to open data practices and ethical AI implementation in quality control systems. Dr. Zwetsloot's work demonstrates cross-disciplinary impact through applications in manufacturing, healthcare monitoring, and sustainable infrastructure systems. Her articles highlight methodological innovations in LSTM predictive modeling , EWMA dispersion control , and energy-efficient predictive maintenance .
K. Psarakis is a researcher in the field of Data-Intensive Systems, focusing on cloud computing, stream processing, and distributed dataflows. Their work bridges theoretical and practical challenges in cloud-native applications and scalable systems. Institution: Affiliated with Data-Intensive Systems Research Focus: Cloud transaction management, autoscaling, geospatial data platforms, and fault tolerance Research Trends Recent publications like Styx and CheckMate highlight innovations in transactional stateful functions and checkpointing protocols. Psarakis also contributes to geospatial data federation (e.g., Topio ) and schema matching techniques ( Valentine ). Collaborations Collaborates with researchers such as G. C. Christodoulou, M. Fragkoulis, and A. Katsifodimos on projects involving open-source platforms and cloud-native systems.
Boris Koldehofe is a Professor of Computer Networks at the University of Groningen's Faculty of Science and Engineering, where he leads research in distributed systems and network technologies. He also maintains significant academic connections as an Adjunct Professor at TU Darmstadt (as part of the DFG Collaborative Research Centre 1053 MAKI) and recently joined TU Ilmenau as Professor heading the Distributed Systems and Operating Systems Group. His educational background includes a Habilitation in Communications and Distributed Systems from Technische Universität Darmstadt (2019), a Ph.D. from Chalmers University of Technology (2005), and a Diplom in Informatik from Universität des Saarlandes (1999). Throughout his career, he has held positions at prestigious institutions including Technische Universität Darmstadt, Universität Stuttgart, EPFL, and Ruprecht-Karls-Universität Heidelberg. Koldehofe's research focuses on networked and distributed systems with particular emphasis on middleware, event-based systems, software-defined networking, and the emerging field of in-network computing. His work has evolved significantly toward energy-efficient cognitive computing, especially through the exploration of memristor-based technologies for network functions. His research addresses critical challenges in distributed systems performance, privacy, and adaptability in increasingly complex network environments. His recent publications demonstrate a clear trajectory toward energy-efficient network computing, with a significant portion of his work in the last three years focusing on memristor applications for cognitive network functions, in-network data stream processing, and privacy-preserving analytics. His research bridges theoretical distributed systems concepts with practical networking implementations, particularly leveraging programmable data planes and novel hardware architectures. 2019 ACM Service Recognition Award for organizing the 13th ACM Conference on Distributed and Event-Based Systems 2017 Best Research Paper at ACM USENIX Middleware Conference 2015 Ausgezeichneter Ort Land der Ideen (Excellent innovation with CRC MAKI) As an academic advisor, Koldehofe has supervised several doctoral students including Manisha Luthra (awarded KUVS Dissertation Award for 'Network-centric Complex Event Processing') and Saad Saleh (who successfully defended his PhD on memristor-based computing architectures). His research has been supported by numerous grants including DFG-funded projects like 'DynSDN', industry collaborations with Deutsche Telekom, and participation in the CogniGron research center focused on cognitive systems and materials. He leads the Distributed Systems Group at University of Groningen and collaborates extensively with research teams at TU Ilmenau and TU Darmstadt through the MAKI research center.
Michael Biehl is a Full Professor of Machine Learning, Theory, and Applications at the University of Groningen, affiliated with the Bernoulli Institute's Intelligent Systems Group. He holds an honorary position as Professor of Machine Learning at the University of Birmingham. His research focuses on machine learning theory, neural networks, and their applications in biomedical data analysis, statistical physics, and computational science. Education: Not explicitly detailed in texts but inferred through his academic roles and research output. Research Interests: Machine Learning algorithms and their theoretical foundations Neural Networks, including activation function analysis and network dynamics Biomedical data analysis, particularly using metabolomics and imaging data Statistical physics of learning processes Interpretable AI models for clinical decision support Recent Trends in Articles: Biehl’s recent work emphasizes explainable AI in healthcare, concept drift adaptation, and applications in neuroimaging and endocrinology. His studies often integrate machine learning with biomedical datasets to develop diagnostic tools for conditions like adrenal disorders and movement disorders. Awards: Distinguished Visiting Fellow (2014) Best Presentation Award (2016) sbv IMPROVER Challenge Awards (2013) Honorary Professorship at University of Birmingham (2021) Grants/Advising: Active in supervising PhD projects and teaching neural networks. His grants likely support interdisciplinary research in AI and healthcare, though specific grants are not detailed here. Labs/Teams: Leads the Intelligent Systems Group at Groningen and collaborates with the Centre for Systems Modelling and Quantitative Biomedicine at Birmingham.
Kanishkan Vadivel is a Researcher in the Electronic Systems group at Eindhoven University of Technology (TU/e), specializing in energy-efficient hardware architectures and compiler-based code-generation techniques. He holds a Master’s degree in Embedded Systems from TU/e (2017) and a Bachelor’s from Coimbatore Institute of Technology (India). Prior to academia, he worked in embedded systems at Tata Engineering and Arm Ltd. Research Interests : His work focuses on computation-in-memory architectures using resistive devices, optimal code generation for CGRA (Coarse-Grained Reconfigurable Architecture), and high-performance computing. Key projects include the MNEMOSENE initiative and development of the CIM-SIM simulator for computation-in-memory systems. Awards : HiPEAC collaboration grant (2019) Advising & Grants : His research is supported by grants focused on neuromorphic processors and edge-AI hardware. He collaborates on projects like NEUROKIT2E for embedded deep learning systems. Labs/Teams : Active member of TU/e’s Electronic Systems Center and Efficient Stream Processing Lab, contributing to neuromorphic and energy-efficient computing initiatives.
Jolanda van Medevoort is a researcher at Wageningen University & Research in the Biorefinery & Fibre Technology department. Her work focuses on phosphorus recovery from side-streams in horticulture, circular nutrient systems, and sustainable greenhouse hydroponics. Project Leader: REWARDING (2023-2024) Collaborations: HVC, SusPhos, Innovatie Glastuinbouw Nederland Research Interests span sustainable resource management, biorefinery processes, and chemical engineering applications in agriculture. She actively explores technologies for nutrient recycling and desalination in controlled-environment systems. Publications emphasize circular economy frameworks, phosphorus valorization, and innovative water treatment methods. Her recent works (2024-2025) include studies on struvite recovery, hydroponic nutrient cycling, and seawater-derived hydrogen systems.
Thales Costa Bertaglia is a post-doctoral researcher at Maastricht University’s Institute of Data Science, Faculty of Science and Engineering. After defending his PhD in 2024, he focuses on computational approaches to platform governance, legal compliance, and the creator economy. Education PhD, Maastricht University (2024) – Thesis: Decoding digital influence: Computational insights into monetisation, controversy, and compliance in the creator economy Research Interests Bertaglia’s research integrates computational social science and legal informatics to study influencer marketing, disclosure compliance, and content moderation across social-media platforms. He develops synthetic datasets and quantitative methods to assess regulatory adherence on Instagram, YouTube, and TikTok, with a growing emphasis on child and family influencers. His recent work explores generative-AI techniques (e.g., ChatGPT) to create realistic synthetic Instagram data for auditing sponsored-content detection systems, bridging machine-learning innovation with legal accountability. Scientific Awards Grant for the Web (2020) – Mozilla & Creative Commons initiative recognising research on monetisation and micro-transactions in the creator economy. Outreach & Collaboration Bertaglia actively disseminates findings through international conferences and workshops. He co-organised the 2020 Maastricht edition of the Summer Institutes in Computational Social Science (SICCS) and has delivered invited talks on legal compliance in content moderation and influencer marketing. Labs & Teams He is embedded in the interdisciplinary ecosystem of the Institute of Data Science , collaborating closely with the Law & Tech research cluster and external partners such as the Dutch Ministry of Justice and security researchers across Europe.
Martyn Drury is a Professor at Utrecht University's Faculty of Geosciences, Department of Structural Geology and Electron Microscopy. His research focuses on understanding nano-scale processes governing Earth dynamics through advanced electron microscopy and micro-beam analysis techniques. Scanning Electron Microscopy (SEM) Transmission Electron Microscopy (TEM) Microstructural Analysis of Minerals, Rocks, and Ice Sheets Mechanical Strength and Transport Properties High-Pressure Geology Impact Geophysics His work addresses reservoir compaction, surface subsidence, and seismicity through projects like DeepNL (NWO-funded) and contributions to the EPOS Multi-scale Laboratories framework. Key publications span ice core analysis, fault rock mechanics, and salt deformation. Queen Elizabeth II Fellowship (1992) NWO PIONIER Fellowship (1995) Current research integrates 4D imaging, cathodoluminescence mapping, and computational modeling to unravel deformation mechanisms in geological materials.
Nardo van der Meer serves as Full Professor at Tilburg University's TIAS School for Business and Society and CEO of Catharina Hospital Eindhoven—a 600-bed non-academic teaching hospital founded in 1843 with 4,000+ employees and €490M annual turnover. His dual leadership roles bridge academic healthcare management and operational hospital administration across the Netherlands. His educational foundation includes medical licensure and an International MBA from Erasmus School of Management Rotterdam (2009). Career progression began at Amsterdam's Academic Medical Center (2001 faculty appointment), followed by ICU directorship at Amphia Hospital (2004), and executive roles including board chair for medical affairs and interim ICU director at Maasstad Hospital. Research centers on Health Care Management through complex systems analysis, with specialized focus on conflict theory and negotiation frameworks for healthcare leadership. He develops teaching programs for healthcare professionals to drive organizational change, emphasizing practical application in Dutch hospital systems. Recent publications (2020-2023) reveal three dominant research streams: (1) Critical care economics and resource allocation, (2) Cardiac/anesthesiology outcomes including pandemic-era adaptations, and (3) Decision-making frameworks for complex conditions like aortic stenosis. Over 80% of his work involves Dutch multi-center collaborations addressing systemic healthcare challenges. Scientific Awards: No specific awards documented in source materials He mentors Ph.D. candidates through scientific projects coordinated with Catharina Hospital Eindhoven, Technical University Eindhoven, Amphia Hospital Breda, and Dartmouth College. Grant activities focus on healthcare leadership development programs and editorial initiatives including founding editorship of A&I journal for anesthesiologists. His operational leadership spans hospital-wide teams including the Catharina Hospital executive board and Dutch healthcare networks. He coordinates teaching programs for healthcare professionals across multiple institutions while maintaining clinical insights from his background as a cardiac anesthesiologist-intensivist (practiced until 2020).
Lia Hemerik is an Associate Professor in Mathematical and Statistical Methods at Wageningen University & Research. She holds dual master's degrees in Biology (1985) and Mathematics (1987) from Leiden University, followed by a PhD in 1991 on 'Studies on larval parasitoids of Drosophila: from individuals to populations.' Her research integrates mathematical modeling with ecological applications, focusing on survival analysis, population dynamics, and biological control. Key areas include food web stability, invasive species, sustainable agriculture, and conservation of endangered species. She has contributed to pioneering studies, such as investigating magnetic alignment in cattle and analyzing the impact of climate change on forest recovery. Her work also extends to educational outreach, including authoring a Dutch booklet on ecological tipping points and developing teaching materials for high school students on statistics and ecology. Hemerik actively engages in interdisciplinary projects, combining ecological modeling with policy-relevant questions like ecosystem service valuation and soil biodiversity assessment. Her academic roles include teaching advanced courses in mathematical methods, ecological modeling, and soil biology. She has advised numerous research projects and contributed to international collaborations on pest risk assessment and Arctic ecosystem resilience. Beyond academia, she advocates for environmental stewardship through initiatives like Homeward Bound and promotes public engagement in nature conservation.
Dr. Aarnout van Delden is an Associate Professor in Dynamics Meteorology at Utrecht University's Faculty of Science. His research focuses on atmospheric dynamics, climate science, and the interplay between data science and complex environmental systems. He is affiliated with the Marine and Atmospheric Research group and contributes to sustainability initiatives like the 'Pathways to Sustainability' program focusing on water, climate, and future deltas. Research Interests : - Northern Annular Mode dynamics and its connections to meridional mass/vorticity transfer - Mid-Pliocene climate analogs and high-CO₂ scenarios - Tropical precipitation anomalies and teleconnections - Urban meteorology leveraging smartphone data for temperature monitoring - Stratospheric-tropospheric interactions and sudden stratospheric warmings - Gulf Stream influences on Atlantic storms and extreme precipitation Recent Work Trends : Recent publications emphasize climate dynamics across timescales, from historical reconstructions of the Pliocene era to future projections under elevated CO₂ scenarios. His work bridges theoretical atmospheric physics with applied data science methods, including innovative use of smartphone sensors for urban climate studies. Professional Activities : - Visiting researcher at NASA Goddard Institute for Space Studies (2017) - Invited speaker on topics like Northern Annular Mode predictability and Buys Ballot's legacy in dynamical meteorology - Active in international collaborations and climate variability studies Key Contributions : Pioneered smartphone-based temperature measurement techniques in urban environments and advanced understanding of mid-latitude atmospheric circulation patterns through potential vorticity analysis.
Sherif Eissa is a PhD Candidate in the Electronic Systems group at the Department of Electrical Engineering, Eindhoven University of Technology (TU/e). His research focuses on neuromorphic computing for efficient real-time AI through hardware design, under the supervision of Prof. Henk Corporaal and Prof. Sander Stuijk. He is part of the national research project efficientdeeplearning.nl . Education: Bachelor of Information Engineering (cum laude), German University in Cairo (2016), with thesis at the Institute for Microelectronics Stuttgart (IMS) and University of Stuttgart. Master of Information Technology and Embedded Systems (cum laude), University of Stuttgart (2019), with thesis at Bosch Research Campus, Renningen. Research Interests: Machine Learning, Hardware Design, Data Encoding, Parallel Data Processing, Memory Structures, and Sparsity Utilization for Low-Power Edge AI. Awards: Best Achieving Student in overall grades (Bachelor's Degree). Best Achieving Student in overall grades (Master's Degree). Advising and Projects: Supervised 3 research works. Principal project: Efficient Deep Learning Platforms (eDLP) (2018–2023), focusing on Deep Learning Method, Energy Efficiency, and Hardware Platforms. Labs and Teams: Member of the Efficient Stream Processing Lab and the Electronic Systems group at TU/e.
Jacopo Urbani is an Associate Professor at Vrije Universiteit Amsterdam, affiliated with the Faculty of Science, Computer Systems department, and the Network Institute. His research focuses on Knowledge Graphs, Stream Reasoning, and Distributed Computing. He explores scalable reasoning techniques for large-scale datasets, integrating semantic technologies with real-time data processing. His work emphasizes practical applications of logic-based systems, including existential rules, probabilistic reasoning, and trigger graphs for efficient knowledge base materialization. Recent contributions address challenges in handling dynamic data streams and enhancing the scalability of semantic web technologies. Urbani has published extensively in top venues like the Semantic Web Conference (ESWC) and the International Conference on Principles of Knowledge Representation and Reasoning (KR). Notable projects include the VLog rule engine for knowledge graphs and the Tab2Know platform for extracting structured data from scientific tables. He supervises PhD theses in areas like stream reasoning and knowledge graph embeddings. His research also involves collaborative efforts with institutions worldwide, addressing topics such as data compression, distributed computing architectures, and hybrid reasoning systems.
