Dr. Jeewanie Jayasinghe Arachchige is a Lecturer in the Department of Computer Science at Vrije Universiteit Amsterdam, Faculty of Science. She teaches undergraduate courses including Bachelor Project Computer Science, Professional Development, and Software Engineering Processes for the academic year 2024–2025. Her research focuses on process mining , healthcare informatics , and data security . She applies process mining to analyze healthcare pathways and subpopulation treatment variations, develops explainable AI frameworks for predictive analytics, and examines data governance in emerging architectures like Data Lakehouses. Her work intersects legal informatics, particularly formalizing Sri Lankan civil court processes using ontology engineering. Recent publications highlight trends in balancing simplicity and complexity in process modeling, Industry 4.0 healthcare applications, and cybersecurity in model-driven web development. She has contributed to over 20 peer-reviewed articles since 2006, spanning topics from service-oriented architectures to value network analysis. Her teaching and research emphasize practical applications of IT in healthcare, legal systems, and enterprise environments. No ancillary activities are currently recorded.
Massimo Mischi is a Full Professor at the Faculty of Electrical Engineering of the Eindhoven University of Technology (TU/e) and chairs the Signal Processing Systems (SPS) Division , the largest division at TU/e with over 250 researchers. He founded the Biomedical Diagnostics (BM/d) Lab in 2012, which now includes 180 researchers and clinical/industrial advisors, focusing on biomedical signal processing for diagnostics and monitoring.
Herman Bruyninckx is a Part-Time Full Professor at Eindhoven University of Technology (TU/e) in the Mechanical Engineering department, specifically within the Control Systems Technology group and EAISI High Tech Systems initiative. He also serves as a professor (Hoogleraar) at KU Leuven in Belgium. Academic focus on robotics, control systems, and multi-agent coordination Active research in model predictive control , semantic mapping , and dynamic constraint algorithms Recent publications address industrial automation , agro-food robotics , and haptic technology Research Highlights : Developed hybrid decision-making frameworks for multi-agent navigation Innovated swing-free control methods for robotic pick-and-place operations Formulated constrained dynamics algorithms with LQR-Gauss principle integration Created ExoTen-Glove for haptic feedback in virtual environments Collaborative Projects : Coordinated with researchers like René van de Molengraft , Elena Torta , and Koen de Vos Contributed to NWO/TTW FlexCRAFT project for cognitive robotics in agro-food technology
Mila N. Koeva is a Vice Dean Research and senior Associate Professor at the University of Twente's Faculty of Geo-Information Science and Earth Observation (ITC), Department of Urban and Regional Planning and Geo-Information Management. Her research focuses on 3D modeling and Digital Twins for land management and urban planning, integrating geospatial technologies, UAV data, and AI/ML methods. PhD in architectural photogrammetry MSc in Engineering (Geodesy) Research Themes: Digital Twinning for urban ecosystems AI-driven cadastral boundary extraction 3D modeling with LiDAR and satellite data Global partnerships in Rwanda, Kenya, and Ethiopia Interoperability standards for local digital twins Scientific Contributions: Geospatial World Innovation Award 2021 Copernicus Masters Competition (3rd place 2016) Editorial roles in Photogrammetric Records and MDPI journals Keynote speaker at 3D GeoInfo, GI Forum, and FIG events Her educational impact includes developing courses, lecturing, and supervising students whose work has received top awards in The Netherlands and international competitions.
Nima Monshizadeh Naini is a Professor in the Faculty of Science and Engineering at the University of Groningen. He holds the position of Chair of the IEM Program Committee and serves on the boards of ENTEG and YSEN. His academic journey includes a PhD in Control Systems from the University of Groningen (2013, Cum Laude), followed by postdoctoral research at the University of Cambridge (2016-2017) and the University of Groningen (2014). He has been an Assistant Professor since 2018 and was awarded the NWO Open Competition Grant in 2021. His research focuses on Cyber-Physical Human Systems (CPHS) , addressing two core areas: (1) Coordination of self-interested users in power systems and traffic networks using dynamic information design and game-theoretic mechanisms; and (2) Privacy-aware control and optimization with tailored encryption methods for dynamic systems. Applications include energy markets, microgrids, and smart grids. He has published extensively in top venues like IEEE CDC and Automatica, with key topics including privacy-preserving algorithms, distributed control, and optimal intervention design. His work contributes to UN Sustainable Development Goals related to affordable energy and responsible consumption. Education: PhD in Control Systems, University of Groningen (2013) Research Associate, University of Cambridge (2016-2017) Postdoctoral Researcher, University of Groningen (2014) Awards: Cum Laude distinction for PhD thesis (2013) NWO Open Competition Grant (2021) Advising & Grants: Supervised 5 PhD students Editorial roles in IEEE journals and conference proceedings Labs/Teams: Leading the Cyber-physical systems group within the Smart Manufacturing Systems institute.
Fabian Ferrari is an Assistant Professor in Cultural AI at Utrecht University, working in the Department of Media and Culture Studies within the Humanities faculty. He is affiliated with the Centre for Digital Humanities and is a member of the focus area Governing the Digital Society . Previously, he served as a Postdoctoral Researcher (2022-2024) in the same focus area and was a Visiting Scholar (2021-2022) at the Milieux Institute for Arts, Culture and Technology in Montréal. Dr. Ferrari's research focuses on the intersection of artificial intelligence, digital platforms, and society. His work examines AI governance, algorithmic power, digital labor, and the infrastructural geographies of AI systems. He investigates how public investments in AI infrastructure can reconcile competitiveness with public value creation, particularly through his upcoming NWO-funded Veni project Conditional Computing: Reimagining the Governance of Public AI Infrastructure , which begins in January 2026. His publication record demonstrates significant scholarly impact, with articles in top journals including Nature Machine Intelligence , Cultural Studies , New Media & Society , Big Data & Society , and Competition & Change . He has also co-edited the open-access book Digital Work in the Planetary Market published by MIT Press. Ferrari's work is frequently cited and has influenced policy discussions, as evidenced by multiple policy citations across his publications. NWO Veni grant for research on public AI infrastructure Dr. Ferrari's research collaborations span multiple institutions and international teams. He has frequently co-authored with scholars including Mark Graham, José van Dijck, and Anne Helmond. His work bridges technical, social, and policy dimensions of AI systems, with particular attention to labor implications and governance frameworks. He is actively engaged in both academic and public discourse on AI's societal implications, contributing to progressive policy visions for generative AI.
Andrea Continella is an Associate Professor at the Faculty of Electrical Engineering, Mathematics and Computer Science of the University of Twente, where he contributes to the International Secure Systems Lab (iSecLab). His research focuses on systems security, particularly embedded firmware security, Android app security, malware detection, and program analysis techniques for vulnerability discovery. Ph.D. in Computer Science and Engineering, Politecnico di Milano (cum laude) Postdoctoral Researcher, Computer Science Department, UC Santa Barbara Visiting Researcher, School of Computer Science, University of Sydney Key research contributions include: Developing automated analysis techniques for embedded firmware (KARONTE, ShieldFS) Creating privacy leak detection mechanisms for mobile applications Designing ransomware defense systems using self-healing filesystems Advancing IoT security through misconfiguration detection (S3 buckets) and protocol analysis Pioneering semi-supervised methods for network traffic fingerprinting (FlowPrint) Scientific awards: Dutch Cyber Security Best Research Paper Award 2024 Runner-up USENIX Security Distinguished Reviewer Award 2024 Professional activities: Keynote speaker on firmware security (2024) Member of IPN Cyber Security Special Interest Group Oral presentations on automated vulnerability research (2023)
George Vosselman is a Full Professor at the University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC), specializing in Geo-Information Extraction with Sensor Systems. Educated with honours at Delft University of Technology (1986) and PhD in Photogrammetry from Rheinische Friedrich Wilhelms University of Bonn (1991), he has held academic roles at the University of Stuttgart, University of Washington, and Delft University of Technology (1993–2004). Since 2004, he has been a key figure at ITC, serving as department head (2012–2018, 2023–). Education: Delft University of Technology (BSc with honours, 1986), Rheinische Friedrich Wilhelms University of Bonn (PhD with honours, 1991) His research focuses on leveraging sensor technology advancements for large-scale geo-information production. Key expertise includes quality analysis of laser altimetry data, point cloud segmentation/classification, 3D building/road modeling, and model-driven imagery analysis. He has published over 220 papers and co-edited the textbook Airborne and Terrestrial Laser Scanning (2010). Recent work integrates deep learning with geospatial data, addressing semantic segmentation, visual question answering, and drone-based mapping. Recent publications (2025–2023) highlight trends in deep learning for remote sensing , including multimodal question answering benchmarks (HRVQA), vectorized building extraction (RoIPoly), latent diffusion for road modeling (LDPoly), and drone obstacle avoidance systems. His work bridges photogrammetry , computer vision , and robotic mapping , with applications in urban planning, disaster management, and informal settlement monitoring. Scientific Awards : Hansa Luftbild (1993), ISPRS Otto von Gruber (2000), Schwidefsky Medal (2012), Karl Kraus Medal (2012), ASPRS Fairchild Award (2015), ISPRS Fellow (2020) As an educator, Vosselman has taught photogrammetry, remote sensing, and laser scanning at Delft University of Technology and globally. He chaired the ITC Examination Board (2015–2023) and modernized geo-information education in Asia/Africa. His software for point cloud processing is commercialized in Europe, and he currently leads ISPRS working groups on point cloud methodologies. Labs/teams include the Earth Observation Science Chair Group at ITC, collaborating on UAV-based datasets (UAVid, UAVPal) and indoor laser scanning systems. Recent activities (2025) involve invited talks on pulse matching limitations in laser scanning and deep learning for point cloud classification.
Anuj Pathania serves as an Assistant Professor in the Parallel Computing Systems (PCS) group within the Informatics Institute at the University of Amsterdam's Faculty of Science. His research pioneers sustainable computing systems operating under severe power, thermal, and reliability constraints, with significant contributions to energy-efficient hardware design and embedded systems. Education: PhD in Computer Science (2018), Karlsruhe Institute of Technology MSc in Computer Science (2012), National University of Singapore B.Tech in Computer Science (2009), Maharaja Agrasen Institute of Technology Pathania's research centers on low-power design and sustainable systems for constrained environments, with particular expertise in thermal management of 3D-stacked architectures and energy-efficient machine learning inference . His work bridges electronic design automation with real-world reliability challenges, developing novel power budgeting techniques like T-TSP that incorporate transient temperature effects ignored by conventional methods. Current projects include EU-funded initiatives on energy labeling for digital services, addressing ecological impacts through technological, behavioral, and legal frameworks. His publication trajectory reveals a strategic evolution toward zero-waste computing , with recent work (2023-2025) focusing on hardware-software co-design for edge AI, energy modeling across computing continua, and parameter-efficient neural adaptation. Key themes include thermal-aware scheduling for S-NUCA many-cores, cooperative processor utilization in heterogeneous systems, and sustainability metrics for digital services. Scientific Recognition: Best Paper Award Nomination at IEEE Computer Society Annual Symposium on VLSI 2023 for 3D-TTP power budgeting technique Pathania actively mentors 4 PhD students (Ehsan Aghapour, Saeedeh Baneshi, Sudam Wasala, Yixian Shen) and has successfully supervised 5 Master's theses (including Cum Laude defenses by Joris op ten Berg and Jurre Wolff). His research is supported by major grants including Energy Labels for Ecologically Sustainable Digital Services (2023-2024) and Towards Zero-Waste Computing (2021-2025), developing simulation frameworks like HotSniper and CoMeT for thermal analysis. The PCS group maintains strong industry collaborations with ARM and NVIDIA, particularly through tools like ARM-CO-UP for heterogeneous processor utilization.
Cagatay Catal is a Lecturer at the Information Technology Department of Wageningen University & Research in the Netherlands. Previously, he served as Associate Professor at Istanbul Kultur University's Department of Computer Engineering (2012–2017), including three years as Department Head (2014–2017). Prior to academia, he worked for 8 years at TÜBİTAK's Information Technologies Institute as Senior Researcher & Project Manager (2002–2012), contributing to large-scale software systems. He holds a BSc/MSc from Istanbul Technical University and a PhD from Yildiz Technical University, all in Computer Engineering. His research focuses on machine learning applications in software engineering, software quality assurance, testing methodologies, and architecture design. He actively reviews for funding bodies like the European Union's EUROSTARS program, Canada's Research Council, and Turkey's Research Council. Catal leads projects such as INREF Smart-In-Ag (SMART farming in Indonesia), VIRAL (ICT in agricultural education), and malware detection in software systems. His work bridges academic research with practical software development challenges in diverse sectors like healthcare and education.
Prof. Dr. Ben Wagner is a Professor of Media, Technology & Society at Inholland University, Director of TU Delft's AI Futures Lab on Rights and Justice, and Professor of Human Rights & Technology at IT:U. His work bridges social sciences, technology, and human rights, focusing on digital governance, AI ethics, and societal impacts of technological change. He holds a PhD from the European University Institute (2013) and has led institutions like the Center for Internet & Human Rights (Viadrina) and the Sustainable Computing Lab (WU Wien). Key initiatives include Inholland's Digital Rights Research Team (DRRT), Sustainable Media Lab (SML), and contributions to the European Cloud for Heritage OpEn Science (ECHOES). His research emphasizes designing accountable tech systems, digital rights frameworks, and sustainable digital infrastructures. Recent work addresses gaps between legal/ethical guidelines and public sector data practices, AI governance across nations, and audit mechanisms for platform transparency. Awards include the 2023 Best Paper Award at HICSS for AI governance research and a 2013 Best Student Paper at Internet Science. Collaborations span academia, governments, and industries to shape equitable tech policies. Active in advisory roles for ENISA, Patterns Journal, and the UKRI Trustworthy Systems Hub.
Marc C.W. Geilen is an Associate Professor at the Electronic Systems group , Eindhoven University of Technology. He leads the Model-Based Design Lab and contributes to the CompSOC Lab and High Tech Systems Center . His work focuses on model-based design methods, design automation, and optimization for real-time and embedded systems. Research Keywords: Cyber-Physical Systems, Real-Time Systems, Embedded Systems, Performance Analysis, Design Automation Key Collaborations: EU ECSEL TRANSACT project, SAM-FMS project, Arrowhead Tools initiative His recent publications address weakly-hard timing constraints in server-based systems, hybrid performance modeling for cyber-physical systems, and neural network optimization for communication. Article trends span Real-Time Scheduling , Trustworthy Modeling , Neural Network Efficiency , and Resource Allocation in distributed environments. Scientific Awards : Partial-Order Reduction for Performance Analysis (2018) Teaching activities include courses in Computational Modeling , Embedded Signal Processing , and Discrete Mathematics . He collaborates across projects like TRANSACT, SAM-FMS, and Arrowhead Tools, focusing on flexible manufacturing and cloud-to-edge transitions.
Marcel A.M. Hendrix is an Assistant Professor in the Department of Electrical Engineering at Eindhoven University of Technology (TU/e), specializing in high-precision power electronics and analog circuitry. He is affiliated with the Electromechanics and Power Electronics group and the Power Electronics Lab. Currently employed at Signify, he holds a part-time role at TU/e since 1998. His work integrates design automation, cloud computing, and IC development with system simulation and modeling. Education: MSc in Electronic Circuit Design from TU/e (1981) Research Focus: Hendrix’s research emphasizes hybrid switched-capacitor power conversion, discrete-time control techniques, and large-scale computing. His contributions include advancements in LED driver efficiency and grid-connected converter optimization. He is a key contributor to NGSPICE, an open-source circuit simulator. Advising & Grants: Supervised 33 academic works, including F.N. Hooge ’s thesis on sinus/cosinus generators. Recipient of 4417 citations across 120+ publications. Labs & Teams: Active in the Power Electronics Lab and collaborates on projects involving sustainable energy systems aligned with UN SDG goals.
Prof. Alfred Stein is a Full Professor in Spatial Statistics and Image Analysis at the Department of Earth Observation Science, Faculty ITC, University of Twente. He earned his MSc in Mathematics and Information Science from Eindhoven University of Technology and a PhD in Spatial Statistics from Wageningen University. His career spans roles at Wageningen University (1988–2002), ITC (2002–present), including leadership positions as department head, vice-rector research, and portfolio holder for education. Education: MSc (Eindhoven University of Technology), PhD (Wageningen University) Leadership: Department Head (Earth Observation Science), Vice-Rector Research (2008–2012), Portfolio Holder Education (2012–) His research focuses on Spatial and Spatio-Temporal Statistics , emphasizing Bayesian inference , data quality , image analysis , and fuzzy techniques . Key application domains include agriculture, health, urban land use, coastal systems, hazards, and wildlife. He has mentored over 30 PhD students since 1998, with 11 currently under supervision. Recent research trends highlight AI-driven remote sensing for glacier mapping, urban livability, and disease modeling. Publications span Deep Learning for SAR tomography, Bayesian hierarchical models for health data, and multitemporal SAR analysis for environmental monitoring. Awards include the Best Paper Award (2019) and ISARA Founder's Award (2020) . Scientific Awards Best Paper Award (2019) ISARA Founder's Award (2020) As Editor-in-Chief of Spatial Statistics and associate editor for multiple journals, he leads academic discourse. Collaborations include the University of Cape Town and University of Pretoria as Honorary Professor. His work contributes to UN Sustainable Development Goals, particularly in climate action and sustainable cities.
Sezer Karaoglu is a Lecturer and part-time postdoctoral researcher at the Computer Vision Group, Informatics Institute, University of Amsterdam. He is also the CTO and Co-Founder of 3DUniversum, a technology spin-off of the University of Amsterdam that provides state-of-the-art 2D/3D computer vision solutions. Additionally, he has co-founded other startups including Scanm and 3DHealthScan. Dr. Karaoglu received his PhD from the Computer Vision Group, Informatics Institute, University of Amsterdam, with research funded by the COMMIT project. His educational background includes a double master's degree: an optics, image and vision master's degree from University Jean Monnet in France and a media technology master's degree from Gjovik University College in Norway. He completed his undergraduate studies with honors at Istanbul Technical University in Telecommunication Engineering. His research focuses on Artificial Intelligence and 3D Computer Vision, with specific interests in SLAM, re-localization, 3D reconstruction, 3D object detection and segmentation, synthetic media, generative AI, deep fake creation and detection, and VR/AR technologies. His work has significant applications in healthcare, particularly in using deepfake technology for therapy for victims of sexual violence-related PTSD and moral injury, as documented in a Frontiers in Psychiatry article. Analyzing his recent publications reveals a strong trend toward neural scene reconstruction, intrinsic image decomposition, and the application of diffusion models to computer vision problems. His research increasingly integrates 3D scene understanding with language models, as evidenced by his work on language-to-3D scene generation. The applications span from healthcare (deeptherapy.ai) to media authenticity (deepfake detection) and industrial applications. ICT.OPEN Poster Award (3rd Position), Oct'13 Pascal VOC'12 Classification challenge, 2nd Position, Sep'12 Pascal VOC'12 Detection challenge, 3rd Position, Sep'12 Best project award at Nokia and CIMET project competition Outstanding reviewer at CVPR'21 PROVADA Future Startup Battle winner Best Dutch AI startup by Valuer Dr. Karaoglu has supervised numerous PhD, Master's, and Bachelor's students, demonstrating his commitment to academic mentorship. His research has attracted significant media attention, with features on Dutch national TV programs including NPO, VPRO, RTL, and international outlets like BBC News. He has received research funding through the COMMIT project during his PhD studies and has successfully translated his research into commercial applications through his startups. His work on deepfake technology has been applied in innovative therapeutic contexts through DeepTherapy.ai, showing the real-world impact of his research. Dr. Karaoglu leads research efforts at the Computer Vision Group Amsterdam and through his company 3DUniversum, which has developed applications like weScan, DeepTherapy, and FairFake.ai. His team collaborates with various institutions including the Netherlands Film Academy for grief therapy applications using deepfake technology. The DeepTherapy project represents a particularly impactful application of his work, using deepfake technology to help victims of sexual violence confront perpetrators in therapeutic settings.
