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Haneen FarahView profile

Associate Professor

• road infrastructure design
• road user behavior
• traffic safety
• +7 more

Dr. Haneen Farah is an Associate Professor in the Department of Transport & Planning at Delft University of Technology and co-director of the Traffic and Transportation Safety Lab. She also serves as head of the Traffic Systems Engineering section. Her research focuses on road infrastructure design, road user behavior, and traffic safety, integrating transportation engineering, human factors, and econometrics. Prior to TU Delft, she was a postdoc at KTH Royal Institute of Technology and earned her M.Sc. and Ph.D. in Transportation Engineering from the Technion-Israel Institute of Technology. Her work includes national/international projects like SAMEN (mixed automated/human traffic implications), AfroSAFE (road safety in Africa), and XCARCITY (sustainable city mobility). She teaches undergraduate and graduate courses on road design and traffic safety, including online programs for low/middle-income countries. Farah supervises multiple PhD and Master students in her research areas, contributing to over 50 peer-reviewed publications. Key research themes include infrastructure design for automated vehicles, driver behavior modeling, cyclist safety, and policy implementation of the Safe System approach. Her interdisciplinary approach bridges engineering and psychology to enhance traffic safety and efficiency through advanced analytics and simulation models.

Anna GrigolonView profile

Assistant Professor

• Sustainable Urban Mobility
• Transportation Planning and Modeling
• Accessibility Modeling
• +10 more

Anna Grigolon is an Assistant Professor at the University of Twente , Netherlands, affiliated with the Transport Engineering and Management Research Group . Her research focuses on sustainable urban mobility , user-centric transport solutions , and travel behavior analysis using tools like discrete choice modeling , spatial analysis , and social psychology theories . Research Interests : Sustainable Urban Mobility Accessibility Modeling Travel Behavior Discrete Choice and Latent Class Modeling Spatial Analysis and GIS Shared Micromobility and Mobility Hubs Equity in Transport Planning Article Trends : Anna’s recent work (2025–2024) emphasizes mobility justice , 15-minute city transitions, and equity in transport access , particularly for marginalized communities like São Paulo favelas. She integrates digital tools (e.g., serious games, kiosks) and space-time metrics to evaluate mobility solutions. Projects : She currently leads the SmartHubs project and contributes to DREAMS and R-map , focusing on smart, equitable mobility systems in Europe and Saudi Arabia.

Edwin van der HeideView profile

Lecturer

• Sound Art
• Interactive Installations
• Spatial Composition
• +3 more

Edwin van der Heide is a part-time Lecturer and researcher at Leiden University, affiliated with the Leiden Institute of Advanced Computer Science (LIACS) and the Academy for Creative and Performing Arts (ACPA). His work bridges sound, space, and interaction through installations, performances, and environments. Key roles include: Co-head of ArtScience Interfaculty (Royal Conservatoire & Royal Academy of Art, The Hague) until 2016 Edgard Varèse Guest Professor at TU Berlin (2009) Invited artist at Le Fresnoy (France) and HKB Bern University of the Arts (2019) Research Interests: Spatial sound composition, audience interaction, interdisciplinary art, and the intersection of technology with auditory perception. Notable projects include Whispering Wind (permanent installation at Leiden University) and Spiral of Time (MACBA, Barcelona). Recent Articles & Exhibitions (2023–2024): Focus on large-scale installations like Pneumatic Sound Field and Spiral of Time , emphasizing public engagement and spatial acoustics. Awards: Witteveen+Bos Art+Technology Award (2009), Best Paper Award for BAI (摆) (2018). Grants & Labs: Collaborations with institutions like NCCA (Russia), MAXXI (Italy), and involvement in projects like Evolving Spark Network (global sound art initiatives).

Pascal MettesView profile

Assistant Professor

• Hyperbolic Deep Learning
• Computer Vision
• Vision-Language Models
• +3 more

Pascal Mettes is a tenured Assistant Professor at the University of Amsterdam within the Informatics Institute, specializing in Artificial Intelligence. He leads groundbreaking research in hyperbolic deep learning, a field he has significantly advanced through theoretical developments and practical applications in computer vision and multimodal learning. His research focuses on three primary domains: hyperbolic vision-language models that address the hierarchical nature of language-vision relationships; hierarchical deep learning using hyperbolic embeddings that naturally accommodate exponential growth patterns; and robust deep learning in hyperbolic space that improves out-of-distribution detection and network resilience. Mettes has established himself as a leading figure in this emerging field through numerous publications at top-tier conferences including CVPR, ICCV, ICML, NeurIPS, and ICLR. His recent work demonstrates how hyperbolic geometry provides natural solutions to fundamental limitations in modern deep learning, particularly regarding hierarchical data structures that cannot be adequately represented in Euclidean space. The publication trends show increasing impact and recognition in the computer vision and machine learning communities, with multiple papers receiving oral presentations and best paper nominations. Best paper nomination ESWC25 for 'Designing Hierarchies for Optimal Hyperbolic Embedding' Finalist MM 2023 Best Open-Source Software Competition (for HypLL) Multiple reviewer awards across major conferences including CVPR, ICLR, ECCV, ICML, and NeurIPS MM 2016 Best Doctoral Student Award TRECVID 2015 Winner Multimedia Event Detection Benchmark Mettes actively mentors eight PhD students working on hyperbolic learning and related topics, while also securing significant research funding including ELLIs PhD Award, NWO ClickNL, Google Perception Academic Funding, and Data Science Centre PhD Grants. He serves in prominent academic roles as Program Chair for International Conference on Multimedia Retrieval 2026 and has organized multiple workshops on hyperbolic learning at major conferences. His leadership in establishing hyperbolic deep learning as a recognized research direction is evident through his survey paper in IJCV 2024 and the development of the HypLL library for hyperbolic learning.

E.I. FriedView profile

Associate Professor

• Clinical psychology
• Psychiatry
• Epidemiology
• +6 more

Dr. Eiko Fried is an Associate Professor at Leiden University's Faculty of Social and Behavioural Sciences, where he works at the intersection of clinical psychology, psychiatry, epidemiology, methodology, and complexity science. His research focuses on improving psychological science through open science practices and innovative measurement approaches. PhD in clinical psychology, Free University of Berlin Postdoctoral training at KU Leuven and University of Amsterdam Promoted to Associate Professor at Leiden University in 2021 Key research areas include: Psychopathology measurement and classification Network analysis in mental health research Ecological momentary assessment (EMA) methodology Open science advocacy and implementation Dynamic systems modeling in psychology Transdiagnostic approaches to mental disorders Recent publications demonstrate expertise in: Symptom network analysis across disorders Improving depression measurement standards Transdiagnostic assessment protocols Mental health data integration challenges Psychological theory construction Methodological innovations in clinical research

Asier MonevaView profile

Researcher

• Criminology
• Cybercrime
• Environmental Criminology
• +4 more

Dr. Asier Moneva is a Postdoctoral Researcher at the Netherlands Institute for the Study of Crime and Law Enforcement (NSCR) and The Hague University of Applied Sciences , specializing in cybercrime , environmental criminology , and situational crime prevention . His work focuses on offender decision-making in cyberspace, cybercrime victimization patterns, and the application of data science to crime analysis. Education : PhD in Criminology (2020), Master in Crime Analysis and Prevention (cum laude, 2017) from Miguel Hernández University. Current Role : Analyzing cybercrime patterns through environmental criminology frameworks and data science methodologies. Moneva's research examines longitudinal offending patterns in cybercrime, particularly through analyses of web defacement archives ( Zone-H data) and hacker behavior. His studies reveal extreme concentration of cybercrime among chronic offenders, with 2.9% of hackers responsible for 68.5% of defacements. He also investigates repeat victimization dynamics in digital environments and the effectiveness of warning banners as deterrents. Recent publications focus on ransomware payment decisions by SMEs, stolen data markets on Telegram, and the intersection of familial relationships with cybercrime involvement. His work combines quasi-experimental designs , crime scripting , and conjunctive analysis to develop prevention strategies.

• Cognitive Neuroscience
• Decision Making
• Noradrenergic System
• +3 more

Professor Sander Nieuwenhuis (Leiden University) specializes in Cognitive Neuroscience of Decision Making through behavioral, EEG, and pharmacological approaches. His work bridges prefrontal cortex function and noradrenergic system mechanisms in human cognition. Studied cognitive psychology (Groningen) and earned PhD (Amsterdam, 2001) International experience: Cambridge University (visiting research), Princeton University (postdoc) Research focuses on noradrenaline's role in attention, decision-making, and cognitive control via: Locus coeruleus-norepinephrine system dynamics Phasic vs. tonic alertness effects Cognitive task performance under neuromodulator deficiency Neuroprotective pathways in Alzheimer's models Recent publications analyze DBH deficiency (Jepma et al., 2011) and attentional blink mechanisms (Nieuwenhuis et al., 2005). His Temporal Attention Lab integrates fMRI, genetics, and computational modeling . Teaching leadership includes: Chair of Research Master Program Committee Coordinator of Scientific Writing courses

Adele BardazziView profile

Assistant Professor

• Comparative Literature
• Contemporary Poetry
• Literary Theory
• +8 more

Dr. Adele Bardazzi is an Assistant Professor at Utrecht University’s Department of Languages, Literature and Communication, affiliated with the Humanities Institute for Cultural Inquiry. She holds an Honorary Research Fellowship at the University of Oxford and has held prestigious fellowships including the Irish Research Council Postdoctoral Fellowship (Trinity College Dublin) and junior fellowships at Queen’s College and Christ Church, Oxford. Her research focuses on poetic form, mourning, queer theory, and intermediality, with a specialization in Italian modern and contemporary poetry. Education: DPhil in Medieval and Modern Languages from University of Oxford (2018), BA in English and Italian from Royal Holloway, University of London. She has held visiting fellowships at institutions worldwide, including CNRS, USC, NYU, and the University of Toronto. Research Interests: Bardazzi explores intersections of form and interpretation in poetry, with emphasis on lyric theory, mourning poetics, and textile-based metaphors. She co-founded the Weaving Media Research Network, Non solo muse, and Italian Poetry Today. Her work bridges literature with feminist theory, queer studies, and environmental humanities. Key Publications: Her monograph Eugenio Montale: A Poetics of Mourning (2022) redefines Montale’s legacy through mourning theory. Upcoming works include A Textile Poetics of Entanglements (Brill, 2025) and edited volumes on global elegy and intermedial craft. Her research frequently appears in journals like Journal of World Literature and Italica . Awards: Recognized for innovative scholarship, including a special mention at the Premio Nazionale Editoriale di Poesia (2023) and fellowships from the Irish Research Council and Trinity College Dublin. Teaching & Leadership: Teaches courses on literary analysis, creative writing, and Italian literature. Leads interdisciplinary initiatives like the Interdisciplinary Italy Summer School. Her work integrates pedagogy with cutting-edge research on gender, authority, and transnational literary practices. Labs/Networks: Co-creator of the Gender & Authority Network (2016-2019), fostering global dialogues on feminist theory and intersectional authority. Active in collaborative projects linking textile arts with poetic creation through her Weaving Media Research Network.

Andreas WeberView profile

Associate Professor

• Science and Technology Studies
• History of Science
• Digital Humanities
• +4 more

Andreas Weber is an Associate Professor at the University of Twente's Digital Society Institute , specializing in the Knowledge, Transformation & Society (KiTeS) research group . His work examines the long-term historical and global relationship between Science, Technology, and Society , with particular focus on colonial histories of natural history, chemistry, and sustainability , as well as computational technologies for contextualizing digitized archives . He leads the HAICu project (2023–2029) on digital cultural heritage and coordinates STS PhD training for the Netherlands Graduate Research School (2019–2024). MA & PhD in History (2005 & 2012), Leiden University Assistant Professor (2017–2023), University of Twente Andreas' research integrates digital humanities with colonial science history , emphasizing global histories of minerals , digital humanism , and AI's societal context . His 15 most recent publications (2016–2025) explore topics like colonial bias in natural history collections , FAIR data implementation , and semantic annotation of handwritten archives , spanning disciplines from history of science to computer science and museum studies . He has received 7 scientific awards , including multiple Best Teacher Awards (2020–2023) and the IEEE eScience Best Poster Award (2018). Andreas supervises PhD and postdoctoral projects while engaging in media commentary on colonial heritage issues and co-organizing international conferences like Hydrogen Pasts and Futures (2024).

Giulio DagninoView profile

Associate Professor

• Medical Robotics
• Endovascular Robotics
• Computer Vision
• +5 more

Giulio Dagnino is Associate Professor of Robotics and Mechatronics at the University of Twente and concurrently holds an appointment at the Digital Society Institute. His research integrates medical robotics, real-time perception and haptics to create MR-compatible platforms for endovascular surgery, earning an h-index of 17 and 971+ citations. Education & Career: PhD (details not specified in source) leading to faculty appointment at University of Twente. Promoted to Associate Professor with cross-appointments in Robotics & Mechatronics and Digital Society Institute. Research Interests: Prof. Dagnino’s core interest is medical robotic systems that can operate safely inside an MRI scanner. His work spans haptic guidance, real-time computer vision, soft robotic actuation, synthetic data generation and surgical simulation. By combining ferrofluid actuation, electromagnetic tracking and deep-learning-based scene understanding, he aims to reduce ionizing radiation exposure, enhance navigation accuracy and shorten procedure times for minimally invasive endovascular interventions. Publications Trend: Across 44 outputs (2010-2025) the portfolio reveals a clear evolution from early vision-based microsurgery and fracture-robot systems (2010-2016) toward holistic endovascular platforms integrating MR guidance, haptics and autonomy. Recent 2024-25 papers cluster around (i) synthetic data & scene understanding for surgical AI, (ii) MR-safe robot design and tracking, and (iii) translational studies bringing CathBot and related platforms closer to clinical use. Scientific Awards: Best Design Award – Hamlyn Symposium 2019 (with team) Best Innovation Award – ICRA 2018 Best Paper Award – CURAC 2019 IEEE ICRA Best Paper Award in Medical Robotics – 2016 Grants & Projects: Although explicit grant numbers are not listed, the continuous outputs, patents, multi-institutional collaborations (UK, Germany, Estonia, Canada) and press releases imply sustained funding from EU, Dutch and UK research councils as well as industrial partnerships. Labs & Teams: He leads activities within the Robotics and Mechatronics group at University of Twente, collaborates closely with the Digital Society Institute, and maintains international partnerships visible in co-authored papers with Imperial College London, University of Leeds, and several European hospitals.

• machine learning
• robotics
• machine vision
• +9 more

Dr. Hamidreza Mohades Kasaei is an Associate Professor in the Department of Artificial Intelligence at the University of Groningen, Netherlands. He holds positions in both the Faculty of Science and Engineering and the Faculty of Medical Sciences/UMCG, focusing on Robotics and image-guided minimally-invasive surgery. His work bridges theoretical advances in machine learning with practical robotic applications. Dr. Kasaei's research focuses on developing algorithms for adaptive perception systems through interactive environment exploration and open-ended learning. His specific interests include 3D object perception, grasp affordance detection, object manipulation, and active perception. He has evaluated his research on various robotic platforms including PR2, UR5e, Kinova, Franka robotic arms, and humanoid robots. His work enables robots to learn from past experiences and intelligently interact with non-expert human users using data-efficient techniques. Analysis of his recent publications reveals strong trends toward increasingly sophisticated manipulation capabilities, particularly in dual-arm coordination and handling dense clutter. There's a clear progression toward integrating language models with robotic control systems, as seen in works like 'Lifelong Robot Library Learning' and 'Towards Open-World Grasping with Large Vision-Language Models.' His research consistently addresses real-world challenges in agricultural robotics, assistive technologies, and service robotics applications. Gratama Science Award (2022) Google Research Scholar Award in Machine Learning (2023) Outstanding Associate Editor for IEEE Robotics and Automation Letters (2023) Dr. Kasaei has successfully supervised multiple PhD students including Zhenxing Zhang (thesis on 'Generative Adversarial Networks for Diverse and Explainable Text-to-Image Generation') and Hamed Ayoobi (thesis on 'Explain What You See: Argumentation-Based Learning and Robotic Vision'). His research is supported by significant grants including the Google Research Scholar Award for 'Continual Robot Learning in Human-centered Environments' and various conference organization roles including workshops at RSS 2023 and NeurIPS 2022. He leads the Lifelong Interactive Robot Learning Lab (IRL-Lab), which focuses on six key research directions: Perception and Perceptual Learning, Object Grasping and Manipulation, Lifelong Interactive Robot Learning, Dual-Arm Manipulation, Dynamic Robot Motion Planning, and Exploiting Multimodality. The lab develops cutting-edge approaches for robots to learn in open-ended fashion through interaction with non-expert human users, with applications in assistive robotics for people with disabilities.

Raymond H. CuijpersView profile

Associate Professor

• Cognitive Robotics
• Human-Robot Interaction
• Socially Assistive Robotics
• +5 more

Raymond H. Cuijpers is an Associate Professor at Eindhoven University of Technology in the Human Technology Interaction group. His research focuses on Cognitive Robotics , Human-Robot Interaction , and Artificial Intelligence for cognitive agents, with applications in healthcare robotics and aging population support. PhD in Physics of Man from Utrecht University (2000) Postdoctoral research at Erasmus MC Rotterdam and Radboud University Nijmegen Key research areas include: Developing socially intelligent robots with proper social cue interpretation Hybrid AI approaches for real-world complexity handling Visual-haptic perception integration in human motor control Service robots for COPD patient assistance (KSERA project) Rescue robotics and tele-operation applications Recent research output (2025) includes studies on: Personalization in human-robot communication Optimal lighting for elderly visual perception Human-robot bonding mechanisms Interactive sensorized platforms for homecare (GUARDIAN) Audiovisual temporal integration in virtual environments He coordinates large-scale European projects like GUARDIAN and previously KSERA, contributes to sustainable development goals through healthcare robotics, and serves on editorial boards of leading journals including International Journal of Social Robotics . His work spans both technical robotics development and human-centric interaction studies.

• Multimedia Modeling
• Machine Learning
• Computer Vision
• +7 more

Dr. Stevan Rudinac is a Researcher at the University of Amsterdam's Faculty of Economics and Business , Section Business Analytics . His work focuses on interactive learning systems and multimodal data analysis, particularly in urban contexts and multimedia modeling. Education: PhD in Multimedia and Information Retrieval from Delft University of Technology (2013). Research Interests: Stevan specializes in multimedia modeling , hypergraph learning , and interactive video search . He develops frameworks for scalable analysis of social networks, urban imagery, and large multimodal datasets, bridging machine learning with practical applications in city planning and financial social media. Recent Trends: His 2024-2025 publications highlight large language model optimization , diffusion model evaluation , and dynamic graph embedding for meme stocks. Collaborative projects include the CASTLE 2024 dataset and Exquisitor , a system for 100 million image exploration. Labs & Teams: He contributes to the Business Analytics group at UvA, collaborating with Prof. Marcel Worring and Dr. Björn Þór Jónsson. He co-organized the UrbanMM'21 workshop and participates in ACM Multimedia and MMM conferences.

• Computational Neuroscience
• Neural Networks
• Deep Learning
• +4 more

Prof. Sander M. Bohte holds a part-time appointment as a Professor of Computational Neuroscience at the Swammerdam Institute for Life Sciences (SILS), University of Amsterdam, and is a researcher at the CWI Machine Learning group. His research focuses on computational models of neural information processing, emphasizing spiking neural networks, predictive coding, and reinforcement learning. He bridges computational neuroscience and machine learning, exploring how biological insights can improve neural network designs and vice versa. Key collaborations include work with Cyriel Pennartz (UvA), Pieter Roelfsema (NIN), and Steven Scholte (B&C). His applied research spans scientific machine learning applications in finance and genomics. He actively supervises MSc thesis students, prioritizing those from UvA, with projects ranging from biologically inspired neural architectures to efficient spiking network simulations. Research highlights include developing biologically plausible learning rules for deep networks, predictive coding models for sensory data, and spiking network models for working memory tasks. His work also addresses challenges in temporal dynamics and scalable neural computation, leveraging both theoretical and applied perspectives.

• Distributed Systems
• Data Mining
• Machine Learning
• +5 more

Karl Aberer is a full Professor for Distributed Information Systems at École polytechnique fédérale de Lausanne (EPFL) since 2000. From 2005 to 2012, he led the Swiss National Research Center for Mobile Information and Communication Systems (NCCR-MICS). Currently serving as Vice-President of EPFL responsible for information systems, he contributes to academic leadership while maintaining an active research profile. His research spans Distributed Systems Data Mining Machine Learning Social Computing Web Science Graph Neural Networks with recent work focusing on multimodal learning, federated unlearning, and social media analysis. He serves on the editorial boards of the VLDB Journal ACM Transactions on Autonomous and Adaptive Systems World Wide Web Journal and contributes to PeerJ Computer Science.