Hugo Sanjurjo-González is an Associate Professor at the Department of Computing, Electronics and Communication Technologies within the Faculty of Engineering at the University of Deusto. He holds a PhD in Intelligent Systems from the University of León with international distinction and Summa Cum Laude honors. Specializes in Natural Language Processing, Corpus Linguistics, and Computational Linguistics Develops software for multilingual corpus processing and linguistic data analysis Active in ontology-based writing assistance tools and semantic annotation Research Highlights: Focuses on integrating Deep Learning with NLP techniques, particularly Large Language Models (LLMs), to enhance linguistic data processing. Has contributed to multiple digital humanities projects involving theater corpora, parliamentary discourse, and culinary translations. Recent Publications: Special Issue HAIS 2021, PhrasIS benchmark, Content-based Authorship Identification Framework, and Theater Corpus Tools. Scientific Recognition: Mariano Rodríguez Award for Young Researchers Multiple prototype competition awards Professional memberships in academic societies Ongoing research grants in AI and language technology
Klaus Tochtermann serves as a Professor at the Institute of Human-Centred Computing within the Faculty of Computer Science at Graz University of Technology. His research spans multiple dimensions of web technologies and knowledge management systems, with particular focus on the Semantic Web and Linked Open Data ecosystems. His research interests center on Semantic Web technologies , Linked Open Data applications , and knowledge management systems . Tochtermann explores how semantic technologies can transform information retrieval, knowledge organization, and collaborative processes in digital environments. His work investigates the economic implications of data value chains within the Web of Data ecosystem and develops methodologies for harvesting and integrating distributed knowledge resources. Analysis of his publication trends reveals consistent contributions to Semantic Web standards, with increasing focus on practical applications of Linked Data in enterprise and academic contexts since 2008. His work bridges theoretical computer science with real-world implementation challenges in knowledge-intensive domains. Stipendiat der Max Kade Foundation (1996) Tochtermann has led numerous significant research projects including EU-funded initiatives like MATURE (Continuous social learning in knowledge networks), ICT_ENSURE (European ICT environmental sustainability research), and FIT-IT Lasso (Lookup & Alignment Service with Semantic Open data). His project portfolio demonstrates strong collaboration with European research institutions and industry partners, addressing critical challenges in knowledge networking and semantic technologies. He actively contributes to academic discourse through conference organization, including I-Know 2009, and maintains engagement with practical applications through press contributions such as 'Bibliotheksgespräche - Future Internet und die Bibliotheskwelt'.
Georgios Meditskos is an Assistant Professor at the Department of Informatics, Aristotle University of Thessaloniki , where he has worked since 2021. Previously, he was a postdoctoral researcher at the Information Technologies Institute (ITI), CERTH (2012–2021) and a lecturer at multiple Greek institutions. Education: PhD (2009), MSc (2007), and BSc (2004) in Informatics from Aristotle University of Thessaloniki. His research focuses on Symbolic AI and Semantic Web technologies, including: Knowledge representation and reasoning (RDF/OWL, rule-based ontology reasoning) Combination of Description Logic and rule paradigms for scalable reasoning Semantic Web services (discovery, composition) Context-based multi-sensor reasoning and data fusion in pervasive environments His publications (over 100) span topics like: Rule-based OWL reasoning systems (e.g., O-DEVICE, DLEJena) Semantic data fusion for healthcare monitoring Hybrid frameworks combining ontologies with production rules Contact details: Office: New Building of School of Sciences, Office 4.18, Aristotle University of Thessaloniki Email: gmeditsk@csd.auth.gr Phone: +30 2310998896
Halil Kilicoglu is an Associate Professor at the School of Information Sciences (iSchool), University of Illinois at Urbana-Champaign. He holds affiliate appointments at the National Center for Supercomputing Applications , Division of Nutritional Sciences , Personalized Nutrition Initiative , and Center for Health Informatics . His research bridges Natural Language Processing , Biomedical Informatics , and Scientific Reproducibility . Education: PhD in Computer Science (2012), Concordia University Previous Role: Staff Scientist, U.S. National Library of Medicine (NIH) Research Focus: Kilicoglu develops advanced NLP and machine learning techniques to extract and organize knowledge from biomedical texts. His work enhances clinical trial transparency , drug repurposing , literature-based discovery , and scientific communication . Current projects include automated assessment of randomized controlled trials and knowledge graph construction for biomedical domains. Recent Article Trends: His publications emphasize transformer models , retrieval-augmented generation , and multi-label classification applied to citation integrity , diet-microbiome associations , and clinical trial reporting . Scientific Awards: TrustNLP 2023 Best Paper SemEval 2021 Best System Paper IMIA Yearbook Best Paper (2020, 2017) AMIA Distinguished Paper (2016, 2007) Students: Mentors PhD candidates in information science and informatics , including Janina Sarol, Lan Jiang, Mengfei Lan, Shufan Ming, Gibong Hong, Evan Guerra, and Joe Menke. Labs & Teams: Leads a lab at the iSchool focused on biomedical text mining , collaborating with institutions like NIH and SpringerNature. Projects include SemRep extension , MENAGERIE tool , and COMBINI initiative .
Prof. Dr. Otthein Herzog is a Research Professor at Universitaet Bremen (since 2009), Affiliate Research Professor at George Mason University (1998–2024), and Professor of Artificial Intelligence at Tongji University (2015– ). He leads the Artificial Intelligence Research Group and contributes to interdisciplinary clusters including LogDynamics Research Cluster for Dynamics in Logistics International Graduate School for Dynamics in Logistics CIUC - China Intelligent Urbanization Co-Creation Center His research focuses on Multi-agent systems for autonomous processes Knowledge acquisition with LLMs Mobile/wearable computing for logistics and AAL Image/video analysis for content-driven archiving Integration of deep learning with digital twins Urban planning with small language models Recent work explores sociotechnical modeling of cities through digital twins and AI-driven logistics. Scientific honors include 2024 Chinese Government Friendship Award Magnolia Silver Award (2021) Honorary Professor at Tongji University (2021) Fellow of acatech, GI, and CAE Key projects: EU WearIT@Work (2004–2009) DFG CRC on Autonomous Logistics (2004–2015) MTRC Mobile Technologies Research Center (2004–2010) He serves on boards of UNESCO IKCEST, Shanghai Research Institute for Intelligent Autonomous Systems, and Fraunhofer FIT.
Niklas Torstensson is a Senior Lecturer in Cognitive Science at the Department of Information Technology, School of Informatics, University of Skövde. His research focuses on interaction and communication patterns between humans and between humans and technology. He maintains active membership in the GAME Research Group and iLab (Interaction Lab), contributing to interdisciplinary work at the intersection of cognitive science, game design, and human-computer interaction. His primary research interests include cognitive aspects of human-computer interaction, game-based interventions for education and safety, computational linguistics, and applied linguistics. Torstensson has developed significant expertise in designing games to increase children's awareness of online risks, particularly related to sexual grooming. His work bridges theoretical cognitive science with practical applications for child protection in digital environments. Analyzing his publication history reveals a clear trajectory from foundational linguistic research in the early 2000s toward increasingly applied game-based interventions for child safety. His recent work demonstrates sophisticated integration of cognitive science principles with game design to address serious societal issues, particularly online safety for children. The KidCOG project represents the culmination of this evolution, combining his expertise in linguistics, cognition, and game design to create educational interventions. Torstensson serves as course coordinator for multiple bachelor's level courses and leads the KidCOG research project, which secured 3 million SEK in funding from the Sten A Olsson Foundation. This project investigates sexual grooming processes and children's social media usage to develop preventive strategies through computer games. His grant acquisition demonstrates both the significance of his research focus and his ability to secure substantial external funding. Within the GAME Research Group and iLab (Interaction Lab), Torstensson contributes to collaborative projects examining how digital technologies shape human interaction and cognition. His work with these research groups emphasizes practical applications of cognitive science principles, particularly in developing interventions that protect vulnerable populations while maintaining engaging user experiences.
Olga Nádvorníková is a lecturer and researcher at Charles University in Prague, specializing in corpus-based contrastive linguistics and translation studies. She serves as the coordinator of the French section of the multilingual corpus InterCorp, which has been annotated using Universal Dependencies. Her research focuses on non-finite verb forms (e.g., converbs) across Czech, French, English, and Polish, analyzing how structural language differences affect syntactic complexity and sentence segmentation in translation. She also explores stylistic traditions in literary texts, such as lexical variability in verbs introducing direct speech. Recent seminars: Co-verbs in French, Polish, and Czech (May 2024) Sentence segmentation changes in translations (May 2024) Spatial semantics via multilingual corpora (May 2024) Contrastive syntactic complexity analysis (May 2024)
Tilia Ellendorff is a researcher at the University of Zurich , affiliated with the Department of Computational Linguistics under the Faculty of Arts and Social Sciences . She contributes to the Text Crunching Center (TCC) by developing solutions for text analytics, information extraction, and natural language processing . Her work bridges computational methods with biomedical and health-related domains, as evidenced by her involvement in the Digital Society Initiative (DSI) Community Health. Fields of Interest: Natural Language Processing, Biomedical Informatics, Text Mining, Information Extraction, Computational Linguistics, Machine Learning Her research focuses on creating annotated corpora, optimizing language models for clinical and biomedical texts, and advancing text mining tools for tasks like entity recognition and causal network extraction. She has contributed to collaborative initiatives such as BioCreative V and SMM4H, emphasizing hybrid approaches and multi-task learning. Contact: ellendorff@cl.uzh.ch
Dr. Johannes Graën is a Researcher at the University of Zurich , affiliated with the Department of Computational Linguistics under the Faculty of Arts and Social Sciences . He leads the Language Technology group within the Linguistic Research Infrastructure, focusing on corpus linguistics, computer-assisted language learning (CALL), and games with a purpose (GWAP). Primary Affiliation: University of Zurich Role: Researcher and Educator His research emphasizes corpus linguistics , NLP tools for education , and language learning games . He develops web-based infrastructures like the LiRI Corpus Platform and SwissBERT, a multilingual language model tailored for Swiss languages. His work often intersects with machine translation , word alignment , and multilingual resource exploitation . The trends in his publications highlight multimodal corpus analysis , CALL applications , and parallel corpora modeling . He has contributed to tools like Multilingwis and SPARCLING, which enhance the accessibility and annotation of multilingual datasets.
Dr Alistair Baron is a Senior Lecturer at Lancaster University's School of Computing and Communications, with dual expertise in Natural Language Processing (NLP) and Cyber Security. He applies computational linguistics to counter online deception, focusing on fake profiles, social engineering, and forensic applications. His work bridges linguistic analysis with security solutions, including multi-lingual text processing, spelling variation normalisation, and crisis management decision-support systems. Ph.D. Computer Science (Lancaster University, UK) B.Sc. (Hons) Computer Science (Lancaster University, UK) Research interests span robust NLP tool development for cyber-security, with emphasis on: Deception detection in digital personas Spelling variation in historical and online texts Machine learning for forensic investigations Semantic tagging using historical thesauri GIS-Integrated textual analysis Online child protection systems His recent publications demonstrate interdisciplinary focus, combining NLP with security applications (2016-2023). Key projects include insider threat detection, semantic annotation of historical texts, and penetration testing standardisation research. Awards include the Faculty of Science and Technology Research Fellowship and FHEA teaching accreditation.
Dr. Scott Piao is a Senior Lecturer (Associate Professor) in Computer Science at the School of Computing and Communications, Lancaster University. He holds a PhD from Lancaster University and a Postgraduate Certificate in Academic Practice. With extensive experience in academia, he has previously worked at Sheffield University (2000-2002) and Manchester University (2006-2009) as a Research Associate in Natural Language Processing. His educational background includes: PhD in Computer Science from Lancaster University PGCert (Postgraduate Certificate Academic Practice) Dr. Piao's research focuses on Natural Language Processing, Text Mining, Social Computing, and Data Science. He develops algorithms and tools for automatically analyzing information hidden in language data and applying these techniques in various information systems. His current research emphasizes Large Language Models (LLMs) and generative AI models for automatic analysis of semantic information in language data. Over his career, he has worked on seven major projects funded by EPSRC, ESRC, AHRC, and EU, demonstrating his expertise and recognition in the field. Dr. Piao has served as an Area Chair for the LREC-COLING 2024 Conference and is currently an Area Chair for the COLING 2025 Conference. His extensive service includes participation on program committees for forty-seven leading international conferences covering Natural Language Processing, Social Computing, Big Data, and Corpus Linguistics. His advising includes several PhD students working in Data Science: Mansour Almansour (SCC - Data Science, UCREL) Israa Alsiyat (SCC - Data Science) Ratchakrit Arreerard (SCC - Data Science) Dr. Piao is actively involved in several research groups, including the Data Science Institute - Foundations, SCC (Data Science), and UCREL (University Centre for Computer Corpus Research on Language). He also serves as Director of the BJTU Scheme and Director of the Computer Science Programme at Lancaster University College at Beijing Jiaotong University.
Dr. Faegheh Hasibi is an Assistant Professor of Data Science at the Institute of Computing and Information Sciences (iCIS) at Radboud University in Nijmegen, The Netherlands. Her research focuses on integrating Information Retrieval and Natural Language Processing to advance conversational AI and semantic search systems. Education: PhD in Computer and Information Science from the Norwegian University of Science and Technology (NTNU) Research Interests: Information Retrieval Natural Language Processing Conversational AI Semantic Search Entity Linking Knowledge Graphs Her work specifically explores knowledge-grounded conversational search, entity retrieval, and leveraging knowledge graphs for semantic tasks. Recent publications demonstrate a strong emphasis on entity linking methodologies, conversational personalization, and scalable semantic search techniques. Her work consistently appears in top-tier venues including SIGIR, COLING, CIKM, and DESIRES. Research Grants: NWA-ORC grant for "LESSEN: Low Resource Chat-based Conversational Intelligence" (€4.6M, 2022) Netherlands eScience Center grant for "REL 2.0: Multi-lingual Entity Linking Toolkit" (€140K in-kind, 2021) Radboud-Glasgow collaboration fund for "Task-centric Personal Knowledge Graph Construction" (£18.5K, 2022) She leads research within the Institute of Computing and Information Sciences (iCIS) and collaborates on projects like LESSEN and Radboud Entity Linker (REL).
Jakob Ambsdorf is a PhD Fellow at the Department of Computer Science , University of Copenhagen, affiliated with the Pioneer AI (P1AI) research group. His work focuses on medical image analysis, particularly in fetal ultrasound and brain MRI data, leveraging AI and machine learning techniques for anomaly detection and image quality assessment. Recent research includes unsupervised detection of fetal brain anomalies using denoising diffusion models and learning semantic image quality from noisy ranking annotations. Key collaborations involve researchers from institutions like the University of Copenhagen and international partners in medical imaging.
Prof. Dr. Ulf Leser serves as Professor and Deputy Director at the Institute of Computer Science within Humboldt University of Berlin's Faculty of Mathematics and Natural Sciences. His work bridges computer science and life sciences through bioinformatics and knowledge management systems, with significant contributions to scientific workflow optimization and biomedical text mining. His research spans multiple high-impact areas: Bioinformatics and precision oncology tool development (e.g., OncoTagger for cancer gene curation) Scientific workflow systems with focus on carbon-aware execution and energy efficiency Biomedical natural language processing for relation extraction and knowledge base curation Advanced time series analysis methods (e.g., ClaSP for segmentation) Environmental monitoring through satellite data analysis He actively develops infrastructure for reproducible scientific computing while addressing sustainability challenges in HPC environments. Recent publications (2023-2026) reveal three dominant trends: (1) Integration of explainable AI in healthcare assessment systems, (2) Sustainable computing approaches for scientific workflows including carbon-aware scheduling, and (3) Advancement of biomedical text mining through knowledge-augmented language models. His work consistently targets real-world applications in precision medicine and environmental science. Prof. Leser currently supervises students including Michael Piechotta (Diplom in Bioinformatics, defense scheduled September 2025). As Deputy Director and Faculty Council member, he shapes institutional research strategy while leading projects at the intersection of computer science and life sciences. His group maintains active collaborations with biomedical research institutions and contributes to community standards in scientific workflow systems.
Yen-Chia Hsu is an Assistant Professor at the Informatics Institute, University of Amsterdam, where they teach courses in Information Visualization and Data Science. Previously, they served as a Postdoctoral Researcher at the Department of Sustainable Design Engineering, Faculty of Industrial Design Engineering, TU Delft, and as a Project Scientist in the CREATE Lab at Carnegie Mellon University (CMU). Their academic journey reflects a unique interdisciplinary background bridging computer science and architectural design. Dr. Hsu earned their Ph.D. degree in Robotics in 2018 from the Robotics Institute at CMU, where they conducted research on using technology to empower local citizens and communities. Prior to that, they received their Master's degree in tangible interaction design in 2012 from the School of Architecture at CMU, where they studied and built prototypes of interactive robots and wearable devices. Before CMU, they earned a dual Bachelor's degree in both architecture and computer science in 2010 at National Cheng Kung University, Taiwan. Dr. Hsu is a computer scientist with an architectural design background whose research focuses on Community-Empowered Artificial Intelligence (AI) , where they co-design, implement, deploy, and evaluate interactive AI systems that empower communities, especially in addressing environmental and social issues. Their work spans both social and technical aspects of community engagement with technology. On the social side, they have proposed an alternative framework called Community Citizen Science (CCS) , which extends traditional citizen science methods to a hyper-local scale, emphasizing continued community engagement after technology interventions. On the technical side, they investigate human feedback in AI pipelines and algorithms that enable machine learning models to incorporate different types of human input. Dr. Hsu's scholarly output demonstrates a consistent focus on applying computer vision, machine learning, and data science to environmental monitoring and community empowerment. Their recent work shows an evolution from developing specific tools for pollution monitoring toward more comprehensive frameworks for community engagement with AI systems. A notable trend is the increasing emphasis on empathy-centered design and policy implications of community-driven data collection systems. Their research bridges the gap between technical innovation and social impact, particularly in the domains of air quality monitoring and environmental justice. Outstanding Student Academic Achievement (2005, 2006, 2007) from Department of Architecture, National Cheng Kung University, Taiwan Third Prize, National Country House Design Competition (2008) from Ministry of the Interior, Taiwan Best New Artist, The National Golden Award for Architecture (2009), Taiwan Webby People's Voice Award, Best Use of Video or Moving Image (2014) Best Paper Honorable Mention Award (Top 5%) at ACM CHI Conference (2017) Best Paper Honorable Mention Award (Top 2.5%) at ACM IUI Conference (2019) Prize for Community Collaboration, The Constellation Prize (2020) Dr. Hsu has been actively involved in numerous research projects that bridge academia and community action. Their work on the Smell Pittsburgh platform, which allows citizens to report pollution odors to regulators, has been particularly influential in environmental advocacy. They have collaborated with organizations including ACCAN, PennEnvironment, GASP, Sierra Club, ROCIS, Blue Lens, LLC, PennFuture, Clean Water Action, and Clean Air Council. Their research has received support from the Heinz Endowments and has been featured in TIME, Pittsburgh Post-Gazette, PC Magazine, and other media outlets. Dr. Hsu also maintains an active open-source presence, with several tools and datasets released to support community-driven environmental monitoring. Dr. Hsu leads projects that focus on developing tools for community engagement at scale, including COCTEAU, an empathy-based tool for decision-making, and Project RISE, which recognizes industrial smoke emissions. Their work connects with the Multimedia Analytics Lab Amsterdam, where they contribute to data science education and research. Their approach emphasizes co-creation with communities rather than top-down technology deployment, positioning them at the forefront of human-centered AI research with real-world social impact.
