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Prof. Jacco van Ossenbruggen is a Full Professor in Intelligent Information Systems at Vrije Universiteit Amsterdam (VU), affiliated with the Network Institute. He serves on the Management Board of ODISSEI, a national research infrastructure for social sciences and economics. His academic background includes a PhD in Computer Science (2001) from VU’s Faculty of Science, focusing on hypermedia processing. Research Interests: His work centers on cultural AI, FAIR data principles, ontology engineering, and semantic web technologies. Key areas include inclusive cultural heritage metadata, bias mitigation in AI systems, and knowledge discovery via linked data. Recent projects involve leveraging large language models (LLMs) for metadata enrichment and ontology construction. Key Contributions: He leads initiatives like the Cultural AI Lab, exploring AI applications for cultural heritage. His research bridges technical innovations (e.g., semantic integration of restricted-access data) with societal impacts (e.g., ethical AI frameworks for public-sector applications). Developed frameworks for evaluating entity alignment in knowledge graphs Pioneered FAIR-aligned data management plans for scientific communities Designed tools like Alter Heritage for collaborative metadata curation Grants & Projects: Principal Investigator of the ODISSEI Portal project (2020–2024), advancing open data infrastructures. Active in funding initiatives promoting reproducible research and ethical data practices. Labs/Teams: Cultural AI Lab at VU, focusing on AI-driven solutions for cultural heritage preservation and accessibility.

• Cultural Heritage
• Digital Libraries
• Ontology Engineering
• +7 more

Himanshu Verma is an Assistant Professor at the Knowledge and Intelligence Design Group within the Faculty of Industrial Design Engineering at Delft University of Technology. His research focuses on Human-AI Collaboration, Cognitive Empathy, and designing AI systems attuned to human needs. Prior to TU Delft, he held postdoctoral roles at the University of Fribourg, EPFL, and HES-SO Valais-Wallis, Switzerland. Education: PhD in Computer Science (EPFL, Switzerland), focusing on collaborative group interactions and shared environments. Postdoctoral research in Human-Computer Interaction and Ubiquitous Computing. Research Interests: Empathy-Centric Design for inclusive technologies. Social Signal Processing in human-AI interactions. Health, well-being, and accessibility in AI systems. Key Projects: Co-leads the PERISCOPE (H2020) research project. Designs tools like EmpathiCH and COCTEAU for empathy-driven decision-making. Teaching: Design Analytics (2023–2024). Empirical Design Research (2024). Labs & Teams: Active in the Knowledge and Intelligence Design Group, focusing on AI ethics, hybrid workspaces, and empathetic systems.

• Human-AI Collaboration
• Cognitive Empathy
• Health and Well-being
• +5 more

Paris Avgeriou is a Professor of Software Engineering at the University of Groningen, affiliated with the Faculty of Science and Engineering and the Bernoulli Institute. He leads the Software Engineering and Architecture research group and serves as Editor-in-Chief of the Journal of Systems and Software . His expertise spans technical debt management, software architecture, self-adaptive systems, and embedded systems design. Avgeriou holds an office at Nijenborgh 9, Groningen, and actively advises academic institutions and funding bodies globally. Research Interests: Avgeriou's work focuses on advancing software architecture principles, technical debt lifecycle management, and the integration of AI in software engineering. His research emphasizes practical solutions for improving software quality, maintainability, and system dependability, particularly in embedded and self-adaptive contexts. Recent Contributions: Recent studies include frameworks for benefit-cost-risk decision-making in self-adaptive systems, automated technical debt management using ML, and tools for tracing architecture-related debt. He collaborates internationally, contributing to standards like the Copenhagen Manifesto for human-centered AI in software engineering. Grants & Awards: While no specific awards are listed, his editorial role and frequent conference contributions reflect recognition in the field. He chairs conference tracks and oversees workshops, fostering early-career researchers and artifact evaluation. Labs & Teams: His group is part of the Bernoulli Institute, working on platforms like SDK4ED for embedded systems and tools such as DebtViz for technical debt monitoring. The team explores intersections between systems engineering and software architecture in complex systems-of-systems.

• Software Engineering
• Technical Debt Management
• Software Architecture
• +3 more

Raquel Fernández is a Full Professor of Computational Linguistics and Dialogue Systems at the Institute for Logic, Language & Computation (ILLC), University of Amsterdam. She serves as Vice-Director for Research at ILLC and is a board member of the ELLIS Amsterdam Unit. Her research focuses on interdisciplinary approaches at the intersection of computational linguistics, cognitive science, and artificial intelligence, with emphasis on dialogue modeling, multimodal processing, and language grounding in visual/social contexts. Her work is supported by prestigious grants including the European Research Council (ERC Consolidator Grant 819455) and multiple Dutch Research Council (NWO) awards (VENI, VIDI, Aspasia). She has received scientific recognition such as the Outstanding Paper Award at EMNLP and Best Data Award at GenBench Workshop. Her recent publications analyze multimodal dialogue systems, visual storytelling evaluation consistency, and co-speech gesture modeling, reflecting trends in Linguistic-Cognitive Integration , Multimodal AI , and Contextual NLP . She leads the Dialogue Modelling Group and has been actively involved in academic leadership as co-president of SemDial, VP-Elect for SIGDAT, and ethics chair for major conferences like COLM. Scientific Awards ERC Consolidator Grant 819455 NWO VENI/VIDI/Aspasia grants Outstanding Paper Award at EMNLP 2023 Best Data Award at GenBench Workshop Elected ELLIS Fellow 2023

• Natural Language Processing (NLP)
• Dialogue Systems
• Computational Linguistics
• +7 more

Dr. Saskia Peels-Matthey is a Senior Lecturer in Classics at the University of Groningen's Faculty of Arts, specializing in Ancient Greek religion, literature, and epigraphy. She holds MA degrees in English, Classics, and Linguistics from Leiden and Utrecht Universities, and a PhD in Classics from Utrecht University (2014). Her research integrates cognitive linguistics, digital humanities, and classical studies, notably through her NWO Veni project 'Polytheism as Language' exploring Greek divine semantics. She co-leads the open-access Collection of Greek Ritual Norms (CGRN) database and develops computational tools like AGILe lemmatizer. A board member of the Anchoring Innovation program, she also supervises interdisciplinary PhD projects blending classics with computational methods and climate communication. Her work spans semantic analysis of religious terms (e.g., hosios, hagnos), ritual innovations in inscriptions, and computational modeling of ancient Greek language evolution. Notable collaborations include organizing conferences on Artemis mythology and interdisciplinary workshops on ancient poetry's cognitive impact. She actively engages in public outreach through media appearances explaining classical studies' modern relevance.

• Ancient Greek religion
• Ancient Greek literature
• Greek epigraphy
• +4 more

Dr. Irfan Ahmad serves as an Associate Professor in the Department of Information and Computer Science at King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia, where he teaches undergraduate and graduate courses in Computer Science and Software Engineering while conducting research and advising graduate students. His academic service includes committee roles on graduate studies, program development, and competitions. His research expertise centers on Pattern Recognition with specialized focus on Document Image Analysis , Handwriting Recognition , and Machine-Printed Text Recognition . He actively explores Machine Learning applications including Deep Learning and Natural Language Processing , with significant contributions across Artificial Intelligence, Computer Vision, Data Mining, Neural Networks, and Computational Linguistics as evidenced by his PeerJ subject area specializations. Recent publications reveal a strategic emphasis on adaptive deep learning architectures for document analysis, particularly generative methods for handwritten text recognition and knowledge distillation techniques. His editorial work on feature extraction and multilingual fake news detection further demonstrates applied research bridging theoretical machine learning with real-world language processing challenges. As an active Academic Editor for PeerJ Computer Science with 1,205 contribution points, Dr. Ahmad provides substantial service to the scholarly community through manuscript evaluation and editorial oversight across emerging technologies in data science and artificial intelligence.

• Pattern Recognition
• Document Image Analysis
• Handwriting Recognition
• +7 more

Maya Daneva is an Associate Professor at the University of Twente's Digital Society Institute and part of the Semantics, Cybersecurity & Services research group. With over 200 research outputs, her work focuses on Requirements Engineering , Cybersecurity , and Agile Methodologies , particularly in digital transformation and enterprise systems. Academic Role: Associate Professor in Computer Science Institution: University of Twente Her research spans Model-Driven Engineering , security risk mitigation, and quality requirements prioritization, often employing empirical studies and systematic reviews. Recent articles explore phishing detection ontologies (2025), secure data storage architectures (2024), and digital consulting service modeling (2024). Scientific Awards: CBI 2021 Best Paper Award for work on digital IT consulting platforms EMMSAD 2025 Best Paper Award for phishing attack modeling She actively organizes academic events, serves on editorial boards (e.g., Empirical Software Engineering ), and contributes to conference peer-review, reflecting her leadership in the field.

• Requirements Engineering
• Cybersecurity
• Software Engineering
• +3 more

Afra Alishahi is a Full Professor at Tilburg University's Department of Cognitive Science and Artificial Intelligence within the Tilburg School of Humanities and Digital Sciences. Her research focuses on computational models of human language acquisition and grounded language learning, leveraging neural models to explore how language processing and acquisition occur. She has held roles including Assistant Professor at Tilburg University (since 2011) and Postdoctoral Fellow at Saarland University (2008-2011). Her work bridges computational linguistics, cognitive science, and artificial intelligence, with contributions to understanding language learning mechanisms through models that integrate visual, auditory, and linguistic data. Education: PhD (university unspecified), with prior academic roles in Iran and Germany. Awards: CoNLL 2017 Best Paper Award, 2023 Outstanding Paper Award, NWO Aspasia Grant (2015), and NWO Natural Artificial Intelligence Grant (2015). Her research has been supported by grants such as the Dutch National Research Agenda-funded project on interpreting deep learning models for text and sound. Research Interests: Grounded language learning, interaction effects in language acquisition, and neural model interpretability. Key areas include multi-modal learning (e.g., linking speech to visual scenes), computational modeling of child language learning, and probing neural networks for linguistic knowledge. She co-organized workshops like BlackboxNLP (2018-2020) and has authored over 60 publications, including influential works on phonology encoding in neural models and gender disambiguation in machine translation. Teaching: Courses include Cognitive Models of Language Learning , Computational Linguistics , and Language, Cognition & Computation . She advises master's theses and leads projects in data science and AI. Lab/Team: Leads research on computational modeling, collaboration with interdisciplinary teams (e.g., with Grzegorz Chrupała, Afsaneh Fazly), and involvement in initiatives like the Interpreting Deep Learning Models for Text and Sound project.

• Computational Linguistics
• Language Acquisition
• Neural Models of Language
• +5 more

Sal Hagen is a postdoctoral researcher at the Institute for Logic, Language and Computation (ILLC) at the University of Amsterdam, working within the Natural Language Processing & Digital Humanities group. His research focuses on the intersection of computational methods and cultural analysis, particularly examining online communities, political discourse, and meme culture. His educational background includes a Research Master's in Media Studies from the University of Amsterdam, for which he received the prestigious 2018 Internet Thesis Prize in the Internet & Social Sciences or Humanities category for his work "Here I Am, Praying to an Egyptian Frog: Exploring Political Fluidity on 4chan/pol/". He also won the Audience Award for his presentation at the ceremony. Hagen's research interests center on understanding the dynamics of online communities, with particular expertise in 4chan and related platforms. His work combines qualitative and quantitative approaches to analyze political discourse, far-right movements, and the evolution of memes across digital spaces. He examines how anonymity, platform architecture, and cultural context shape online interactions and political expression. His publication record demonstrates a consistent focus on tracing political movements through digital footprints, with particular attention to the interplay between platform-specific cultures and broader political trends. Hagen's work often bridges computational social science with cultural studies, creating methodologies that capture both the quantitative patterns and qualitative meanings of online discourse. Scientific Awards: 2018 Internet Thesis Prize (Internet & Social Sciences or Humanities category) Audience Award for presentation at Internet Thesis Prize ceremony Hagen has secured significant research funding, including an NWO PhD grant for humanities research running from 2019-2024. He has been involved in multiple research projects including the CAT4SMR project (2024), OILab (2017-present), and the ERC-funded ODYCCEUS project (2018-2019). As part of OILab (Online Intelligence Lab), Hagen contributes to research on online political subcultures, while his work on the CAT4SMR project focuses on stabilizing and developing tools for social media data collection and analysis. He is also the developer of the 4CAT Capture and Analysis Toolkit, which provides transparent and traceable methods for social media research.

• Digital Humanities
• Social Media Analysis
• Online Communities
• +5 more

Rianne Conijn is an assistant professor in the Human-Technology Interaction group at Eindhoven University of Technology (TU/e), Netherlands. Her research bridges data-driven methodologies (machine learning, statistical modeling) with human-centered design to enhance learning analytics, explainable AI, and writing process analysis. She holds a joint PhD (cum laude) from Antwerp University and Tilburg University, and an MSc (cum laude) in Human-Technology Interaction from TU/e. Academic Background: MSc (2015, TU/e, cum laude), PhD (2020, Antwerp University & Tilburg University, cum laude). Research Focus: Learning analytics, keystroke logging, explainable AI for education, data dashboards, and self-regulated learning dynamics. Teaching: Courses in Advanced Research Methods, Human-AI Interaction, Behavioral Research Methods, and AI ethics in education. Her recent publications explore parallel language planning in writing, longitudinal self-regulated learning strategies, and generalizability of academic performance prediction models. She leads an NWO Veni project on Human-Centered AI in education, emphasizing tailored explanations for student-AI collaboration. Scientific awards include cum laude distinctions for her MSc and PhD, and the NWO Veni grant. Collaborative work spans institutions in the Netherlands, Norway, and the U.S., with applications in intelligent tutoring systems and ethical AI deployment in exams. Key trends across her work: integration of machine learning with educational theory, leveraging keystroke data for cognitive process insights, and prioritizing actionable, explainable AI systems for student support. Publications span journals like the Journal of Experimental Psychology: General , Computers and Education , and IEEE Transactions on Learning Technologies . Scientific Awards: NWO Veni grant for Human-Centered AI in education Cum laude for MSc and PhD Grants & Collaborations: National Science Foundation grants (2016868, 2302644) for biometric feedback in writing UK Research and Innovation grant (ES/W011832/1) for real-time AI scaffolding TU/e Boost! Program grant for self-regulated learning analysis Labs & Teams: EAISI Foundational (Eindhoven AI Systems Institute) Human Technology Interaction group at TU/e Collaboration with Norwegian Reading National Center (University of Stavanger) Project teams for Waterproof ITS and ProWrite grants

• Learning Analytics
• Human-Technology Interaction
• Artificial Intelligence
• +6 more

Dr. Jasmijn van Gorp is a Senior Lecturer in the Department of Media and Culture Studies at Utrecht University's Faculty of Humanities. She specializes in Digital Humanities , Audiovisual Heritage , and Digital Culture with a focus on Television History and Eastern European Media . As co-founder of the CLARIAH Media Suite, she develops digital research infrastructure for audiovisual heritage in the Netherlands. PhD in Social Sciences from the University of Antwerp (Belgium) MA in Communication Sciences from KU Leuven (Belgium) Her research examines digital methods for film and television studies , metadata in digital archives , and AI-generated analysis of broadcast schedules . She leads projects like Re-Frame (2021-2025) and AI TaDa , exploring the reuse of audiovisual archives in journalism and algorithmic metadata generation. Recent work includes tutorials on Data Visualization and Flow Analysis using the Media Suite. She advocates for critical digital tool literacy in education and co-authored the Digital Skills learning trajectory for Utrecht's BA programs. Her teaching includes Digital Television History and Programming and Curation at BA and MA levels, supervising theses in film and television studies. As workpackage leader for CLARIAH-PLUS WP5 , she integrates computer vision , automatic speech recognition , and linked data into sustainable tools for cross-media research. She trains researchers via the Media Suite Learn initiative and collaborates on digital infrastructure projects with institutions like NISV and CLARIAH.

• Digital Humanities
• Media and Diaspora
• Media History
• +5 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).

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

Kasper Welbers is an Associate Professor at the Department of Communication Science, Faculty of Social Sciences, Vrije Universiteit Amsterdam. He holds additional appointments at the Network Institute and the Communication Choices, Content and Consequences (CCCC) research group. He is co-Director of The Societal Analytics Lab, Vice Chair of the Computational Methods Division at the International Communication Association (ICA), and a scientific representative of the OPINION COST Action network. His research focuses on computational communication science, journalism, and political communication, particularly exploring how news spreads and the role of gatekeepers in media systems. He develops open-source tools for research and advocates for reproducible computational methods. Education and Academic Background: While formal education details are not explicitly provided, his academic trajectory is evident through his faculty role and publications. Research Interests: Welbers combines methodological innovations with substantive research on news diffusion, media gatekeeping, and computational text analysis. His work addresses topics like dark platforms' agenda-setting roles, automated content analysis techniques, and the impact of platform policies on data donation studies. He emphasizes ethical research practices and open-source infrastructure development. Grants and Awards: He received the Faculty of Social Sciences Dissertation Award (2017) and Teacher Talent Award (2019), highlighting both research and pedagogical excellence. Labs and Collaborations: His work is anchored in The Societal Analytics Lab, fostering interdisciplinary research on societal challenges through computational methods. Collaborations span global networks like the OPINION COST Action, addressing cross-cultural media dynamics. Teaching: He teaches courses such as Computational Analysis of Digital Communication and contributes to curriculum development in AI ethics and data science for societal issues.

• Computational Communication Science
• Political Communication
• Journalism Studies
• +7 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.

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

Hendrik Jan Hoogeboom is an Associate Professor in the Department of Computer Science at Leiden University, affiliated with the Leiden Institute of Advanced Computer Science (LIACS) and the Theory research cluster. Research Interests: His work lies at the intersection of theoretical computer science and computational biology. He specializes in formal languages , algorithms , logic & automata (including tree-walking automata), and infinitary languages . A major theme is modeling natural computation, such as gene assembly in ciliates using graph polynomials and delta-matroids, and molecular computing paradigms like reaction systems and spiking neural P systems. Publication Trends: His recent publications (2017–2024) show a sustained focus on reaction systems and graph polynomials. He has developed formal models to analyze DNA rearrangements, explored the algebraic structure of gene assembly, and investigated the computational power of various natural computing models, often using combinatorial and algebraic tools from graph theory. Scientific Recognition: While specific awards are not listed, his extensive publication record in premier journals like Theoretical Computer Science , European Journal of Combinatorics , and Fundamenta Informaticae signifies high recognition in his field. Teaching and Mentorship: He has supervised several PhD students, including Robert Brijder, Jun Wang, and Rudy van Vliet. He teaches core courses such as Data Structures , Algorithms , Automata Theory , and Complexity , and has led seminars on topics like combinatorial game theory and SAT solvers. Laboratories and Teams: He is a key member of the Theory research cluster at LIACS, focusing on fundamental aspects of computer science. His work is deeply collaborative, especially with colleagues like Robert Brijder and W.A. Kosters.

• Theoretical Computer Science
• Formal Languages
• Algorithms
• +13 more