Michalis Vazirgiannis is a Professor at LIX, École Polytechnique (France) leading the Data Science and Mining (DaSciM) group. With academic backgrounds in Physics (Athens University), AI (Heriot-Watt University), and Informatics (Athens University), he has conducted research at Fraunhofer, Max Planck MPI, and INRIA/FUTURS while teaching at institutions across Greece, France, China, and Spain. His research spans Machine/Deep Learning for Graphs (GNNs, graph kernels, embeddings) Text Mining & NLP (Graph-of-Words, biomedical text analysis) Combinatorial Optimization for pandemic forecasting and energy systems Event/Anomaly Detection in time series and sensory data Industrial collaborations with Airbus, Google, Tencent, and BNP . He has supervised 29 completed PhD theses, published over 250 papers, and received prestigious awards including Marie Curie and Tencent Rhino-Bird Fellowships. His team leads the ANR-HELAS Chair (2020-2025) focusing on heterogeneous data deep learning.
Gemma Boleda is an ICREA Research Professor at Universitat Pompeu Fabra in Barcelona, Spain, where she co-directs the Computational Linguistics and Linguistic Theory (COLT) research group. Her research focuses on understanding how humans convey meaning through language, investigating the formal properties that support communication, and exploring how languages are shaped by cognitive and communicative factors. Her primary interests include lexical semantics, cross-linguistic variation, and the integration of linguistic theory with computational methods. She employs interdisciplinary approaches combining linguistics, artificial intelligence, and cognitive science, utilizing large-scale data analysis to study universal patterns and variations across languages. Boleda's publications demonstrate a consistent focus on computational semantics, lexical variation, and language evolution. Her recent work explores the intersection of symbolic and neural approaches to language processing, lexical creativity across development and evolution, and computational models of semantic phenomena like colexification and polysemy. She teaches Computational Semantics in the Master's in Theoretical and Applied Linguistics program and has secured significant research funding including ERC Starting Grants. Her work has contributed valuable linguistic resources such as the ManyNames dataset and Database of Catalan Adjectives.
Piotr Przybyła is a tenure-track Assistant Professor at Universitat Pompeu Fabra in Barcelona, Spain, where he researches in the TALN (Natural Language Processing) Research Group. He maintains a significant affiliation with the Linguistic Engineering Group at the Institute of Computer Science, Polish Academy of Sciences (ICS PAS) in Warsaw, Poland, where he completed his PhD in Computer Science. Previously, he worked as a research fellow at the National Centre for Text Mining (NaCTeM) at the University of Manchester. Przybyła's research focuses primarily on Natural Language Processing with particular emphasis on misinformation detection, adversarial attacks on text classifiers, text simplification, and Polish language processing. His work bridges theoretical NLP with practical applications for credibility assessment and language understanding. He has developed innovative approaches for testing the robustness of text classifiers against adversarial examples and has made significant contributions to Polish language resources and processing tools. His recent publications demonstrate a strong trajectory in examining the robustness of NLP systems, particularly in the context of misinformation detection and credibility assessment. His work spans from foundational research on language model behavior to practical applications in Polish language processing and text simplification. The ERINIA project, funded by a prestigious Marie Skłodowska-Curie Postdoctoral Fellowship, represents a significant contribution to understanding how misinformation detection systems can be made more robust against adversarial attacks. Marie Skłodowska-Curie Postdoctoral Fellowship for the ERINIA project Computing grant of 10,000 hours on the Athena supercomputer for accelerating work in the ERINIA project Przybyła actively contributes to the NLP community through conference organization, shared tasks (such as coordinating the InCrediblAE shared task for CheckThat! 2024), and developing open-source tools like Plainifier for multi-word lexical simplification. His work demonstrates a commitment to both advancing NLP research methodology and addressing practical challenges in misinformation detection and language understanding across multiple languages, with special attention to Polish language processing.
Cristobal Pagan Canovas is a Permanent Professor (tenure-track) at the Department of English Philology, University of Murcia, where he co-directs the Daedalus Lab and the Murcia Center for Cognition, Communication, and Creativity. He is also a member of the international consortium Red Hen Lab, focusing on multimodal communication research. Education includes: PhD in Ancient and Modern Greek Literature from University of Murcia BA+MA in Classics and BA+MA in English from University of Murcia MA in Classics from University College London His research explores human cognition and communication through interdisciplinary approaches combining humanities and sciences. Primary interests include: Conceptual integration networks in emotional expression Multimodal communication patterns across language, gesture, and prosody Temporal representation in creative artifacts Cognitive foundations of poetic metaphor and verbal art Cultural evolution of integrative patterns in social interactions Recent publications demonstrate consistent focus on temporal cognition, multimodal communication, and creativity across domains including poetry, music, and gesture. Research employs corpus analysis, big data approaches, and cognitive modeling to examine how humans integrate perceptions into meaningful wholes. Scientific awards and fellowships: Ramón y Cajal Grant (elite national scheme) Alexander von Humboldt Fellowship in Quantitative Linguistics EURIAS Fellowship at Netherlands Institute for Advanced Studies FBBVA Leonardo Fellowship Marie Curie Fellowship ENSAYA'10 Award for scientific essay He leads multiple research grants including ERASMUS PLUS KA220-HED (MULTIDATA) and national grants MULTIFLOW and CREATIME. Supervised trainees include postdoctoral researchers (Marie Curie, Juan de la Cierva), MA students, undergraduates, and data scientists. The Daedalus Lab develops interdisciplinary methods to study cognition and communication, while Red Hen Lab enables large-scale multimodal dataset analysis through international collaboration.
Guillem Perarnau is an Associate Professor in the Department of Applied Mathematics at Universitat Politècnica de Catalunya (UPC), affiliated with CRM, IMTech, and BGSMath. He holds a PhD from UPC (advised by Oriol Serra) and was a CARP Postdoc Fellow at McGill University (2013–2015). From 2016 to 2019, he was a Lecturer at the University of Birmingham. His research focuses on Probabilistic and Extremal Combinatorics, Random Combinatorial Structures, and Discrete Stochastic Processes. Education: Bachelor, Master, and PhD in Mathematics at UPC. His academic journey includes postdoctoral research at McGill University and a Lecturer role at the University of Birmingham. Research interests include Percolation Theory, Random Graphs, Stochastic Processes, and Algorithmic Combinatorics. His recent work explores topics like percolation on dense graphs, random walk mixing times, and synchronization in automata. He is co-PI of the COCOA grant and coordinates the Spanish Discrete and Algorithmic Mathematics Network. He participates in the RandNET MSCA Exchange Programme. Key contributions include studies on giant components in directed graphs, phase transitions in Glauber dynamics, and extremal problems in graph colorings. His publications span top journals like Annals of Applied Probability , SIAM Journal on Discrete Mathematics , and Random Structures & Algorithms .
Ramon Ferrer Cancho is an Associate Professor at the Polytechnic University of Catalonia's Department of Computer Science, affiliated with the Barcelona School of Informatics and the LQMC research group (Quantitative, Mathematical, and Computational Linguistics). His work focuses on quantitative linguistics, information theory, and network theory, with applications in language structure, evolution, and animal communication. Education: Doctor in Computer Science, Advanced Studies Diploma in Applied Physics and Simulation. Research Interests: Dependency syntax, linguistic laws (Zipf's law, Menzerath-Altmann law), computational models of language, and cross-disciplinary studies in biology and cognitive science. He leads projects on language optimization, complexity, and data analysis. Recent work includes studies on syntactic dependency distances, ape gesture patterns, and bottlenose dolphin communication parallels. His research bridges computer science, linguistics, and biology, emphasizing universal principles in communication systems. Notable contributions include theoretical frameworks for dependency distance minimization, optimization models of language structure, and empirical analyses of primate vocal sequences.
Ahmed AbuRa'ed is a Researcher at the Department of Information and Communication Technologies (DTIC) at Universitat Pompeu Fabra (UPF), Barcelona. He is affiliated with the TALN research group and the Large-Scale Text Understanding Systems Lab. His work focuses on advancing knowledge in scientific text summarization, information extraction, and machine learning. Education: PhD in Computer Science (2020), UPF, Barcelona, Spain M.Sc. in Computer Science (2015), University of Trento, Italy B.Sc. in Computer Information Systems (2007), An-Najah University, Nablus, Palestine Research Interests: Natural Language Processing (NLP), Machine Learning/Deep Learning, Semantic Web, Information Extraction, Data Mining, and Scientific Document Summarization. His projects include developing systems for automatic generation of state-of-the-art reports, scientific text summarization, and cross-document relation discovery. Publications Focus: His 15 most recent articles (2016–2021) emphasize advancements in scientific literature analysis, including citation detection, text simplification, and cross-document summarization. Notable works involve systems like LaSTUS/TALN for scientific text processing and OlloBot for Arabic health dialogue agents. Labs & Teams: Active member of the TALN research group and the Large-Scale Text Understanding Systems Lab at UPF's DTIC department. Open to collaborations in NLP, Machine Learning, and related fields via email or Skype.
Antonio Ladrón de Guevara is an Associate Professor at Universitat Pompeu Fabra. His research focuses on consumer behavior, diffusion models, and network effects in marketing and economics. He holds a PhD from Universidad Carlos III de Madrid and has published extensively in journals like International Journal of Research in Marketing and Review of Economic Studies. His work combines theoretical models with empirical applications, addressing topics such as hybrid consumption patterns, technology interactions, and price competition dynamics. Key areas of exploration include the impact of network effects on market diffusion and strategic rivalry analysis in multi-market environments. Ladrón de Guevara’s methodologies frequently integrate multivariate analysis techniques and optimization algorithms to solve complex market problems. His academic contributions span over two decades, with notable papers analyzing the Spanish loans market, telecom industry evolution, and consumer decision-making processes. While no specific awards are listed, his prolific publication record reflects sustained scholarly impact. His research often bridges economic theory and applied marketing strategies, offering insights into both theoretical frameworks and practical market phenomena. Though no formal grants or labs are mentioned, his work indicates involvement in collaborative research teams focused on quantitative modeling and interdisciplinary market studies. His advising activities and educational roles remain unspecified in the provided texts.
Lucrecia Rallo Fabra is an Interim Full Professor in the Department of Spanish, Modern and Classical Philology at the University of the Balearic Islands. She holds a degree in English Philology (University of Barcelona, 1993), a Master's in Rehabilitation of Language and Speech Disorders (Polytechnic University of Catalonia, 2002), and a PhD in Linguistics (University of Barcelona, 2005). She has taught at multiple universities including the University of Barcelona and Autonomous University of Barcelona. Her research specializes in speech perception and production in second languages , with particular focus on: Phonetic acquisition challenges for Spanish-Catalan learners of English Cross-linguistic perception models Articulatory training methodologies Classroom-based L2 pronunciation Bilingual speech processing She leads the experimental laboratory group REGAL (Applied Linguistics) and co-directs the BASLA research group (Bilingualism and Spanish Acquisition). Her publication trends show consistent focus on L2 phonetics (2011-2024), with recent work examining Mandarin tone acquisition by Spanish speakers (2021), perceptual assimilation of Tashlhiyt consonants (2022), and articulatory training techniques for English vowels (2024). Research methodologies frequently involve acoustic analysis, perceptual experiments, and classroom interventions. She has conducted research stays at internationally recognized institutions including the University of California Berkeley, University of Oregon, and Macquarie University, and has delivered invited lectures at these centers.
Eneko Agirre is a Full Professor at the Faculty of Computer Science of the University of the Basque Country UPV/EHU, where he serves as the director of the HiTZ Centre on Language Technology. He is an active member of the Ixa Research Group and has established himself as a leading figure in Natural Language Processing, particularly in multilingual and low-resource language settings. His work bridges theoretical advances with practical applications for language technology. Agirre received his PhD from the University of the Basque Country in 1999 with a thesis on conceptual relationships and ontologies, supervised by Dr. Kepa Sarasola Gabiola and Dr. Arantza Díaz de Ilarraza Sánchez. His academic journey has been marked by significant contributions to computational linguistics and language technology. His research primarily focuses on Natural Language Processing challenges, with special emphasis on Word Sense Disambiguation, cross-lingual transfer learning, dialogue systems, and Large Language Models for low-resource languages. He has pioneered work on Basque language technology and has consistently addressed the challenges of multilingual AI systems, particularly examining how language models perform across different linguistic contexts and cultural settings. Analysis of his recent publications reveals a strong trajectory toward advancing Large Language Models for low-resource languages, with particular attention to Basque. His work spans vision-language models, information extraction techniques, and rigorous evaluation methodologies for NLP systems. A recurring theme is the exploration of how language models handle low-resource languages compared to high-resource ones, with groundbreaking findings about cultural knowledge transfer between languages. Fellow of the ACL (2021), one of only 74 research leaders worldwide National Research Prize on Informatics (2021) Best resource paper award at ACL 2024 Honourable mention paper award (top 1%) at EMNLP (2020) Outstanding Paper award (top 2%) at COLING (2020) Recipient of three Google Faculty Research Awards (2017, 2018, 2019) Agirre has supervised over 25 PhD students, many of whom have received prestigious awards including the EurAI Artificial Intelligence PhD Dissertation Award. His research has been supported by numerous European projects including LIHLITH (2018-2020) on lifelong learning for dialogue systems, and he has served as principal investigator for multiple CHIST-ERA and FP7 projects. His work with Google includes collaborative projects on entity dictionaries and conversational question answering systems. As director of the HiTZ Centre on Language Technology and member of the Ixa Research Group, Agirre leads a vibrant team focused on advancing language technology for Basque and other under-resourced languages. The center has developed significant resources including Latxa, an open language model for Basque, and has established itself as a hub for multilingual NLP research. His group actively collaborates with international institutions including Stanford, NYU, and various European universities, fostering a global network for language technology research.
Ana Marcet Herranz is a Professor at the Universitat de València, affiliated with the Faculty of Teacher Training and the Department of Language and Literature. Her academic focus lies in the Didactics of Language and Literature, with a strong emphasis on cognitive and neurological aspects of reading. Her research interests bridge education and cognitive science, particularly in understanding how individuals access abstract linguistic representations during visual word recognition. This work is central to improving literacy instruction and understanding reading disorders. She is an active member of the READit research group, which investigates cognitive neuroscience and reading, and was previously associated with the GIEL Research Group in the Teaching of Languages. Her doctoral training was completed at the Universitat de València in 2018, under the supervision of Dr. Manuel Perea Lara. While no scientific awards or publications are listed in the current data, her profile indicates engagement in interdisciplinary research connecting pedagogy, language acquisition, and brain processes involved in reading.
Maria Ines Caño Melero is a Lecturer (Professora Lectora) at the University of Girona’s Faculty of Education and Psychology, Department of Psychology, and an Associate Professor at the Universitat Autònoma de Barcelona. She is a member of the consolidated research group "Language and Cognition" (GRHCS095 & 2017 SGR 1111) funded by the Catalan government. Education & Accreditations: AQU-Catalunya positive assessment for Lecturer position (2012) Accredited Expert in Clinical Neuropsychology by COPC (2018) Accredited General Health Psychologist by Catalan Ministry of Health (2014) Research Interests: Her work focuses on neuropsychology , psycholinguistics , and bilingual language processing . She investigates lexical access in bilingual speakers, semantic and grammatical deficits in aphasia, numerical cognition, and social-cognitive functions in schizophrenia and Down syndrome. These themes are explored through behavioural, neuropsychological and clinical methodologies. Grants & Projects: PI: Elisabet Serrat – "Grup de Recerca Consolidat Llenguatge i Cognició" (2017 SGR 1111, AGAUR) Co-investigator – UdG Accions Singulars projects on socio-cognitive skills and emotional understanding in deaf and language-impaired children Early-career NIH-funded collaboration with Alfonso Caramazza on lexical access disorders Scientific Awards & Recognitions: Positive accreditation for university teaching and research (AQU, 2012) Certified Clinical Neuropsychology Expert (COPC, 2018) General Health Psychologist certification (Catalan Dept. of Health, 2014) Laboratory & Team Membership: She is an active researcher in the Language and Cognition Research Group at the University of Girona, studying language development, socio-cognitive processes, and basic psychological mechanisms related to psychopathology.
Maria Salamo Llorente is an Associate Professor and researcher in the Department of Mathematics and Computer Science at the University of Barcelona (UB) . She leads the Teaching Innovation Group 'Innovació Docent en Matemàtiques i Informàtica' and is a core member of the Language and Computation Center (CLiC-UB) . Her career spans from postdoctoral work at University College Dublin to extensive contributions in artificial intelligence.
Dr. Borja Sanz Urquijo serves as a Senior Lecturer at the Faculty of Engineering, University of Deusto, and has been a core researcher at DeustoTech-Computing since 2008, including a tenure as Head Researcher (2015-2018). He holds a cum laude PhD in Information Systems (2012) from the University of Deusto, specializing in Android malware detection. Education PhD in Information Systems, University of Deusto (2012, cum laude) His research spans machine learning, big data, and knowledge discovery, with critical expansion into AI ethics, fairness, accountability, and societal impact. He investigates AI applications in domestic violence intervention, health rights, law enforcement transparency, and Edge Computing optimization, consistently bridging technical innovation with social responsibility. His work demonstrates rigorous methodology in small-dataset machine learning and genomic sequence analysis. Dr. Sanz Urquijo's publication trajectory reveals evolving expertise from foundational cybersecurity (Android malware analysis, spam filtering) to contemporary societal challenges (feminist AI frameworks, quantum software security). Recent articles emphasize interdisciplinary collaboration, particularly in feminist technology studies and ethical AI governance, while maintaining technical depth in Edge Computing and genomic analytics. Advising and Projects He has supervised multiple theses including doctoral work on Edge Computing for digital twins and cybersecurity competency frameworks. As lead researcher in over 50 projects (H2020, national, private), he currently directs BEACON (industrial AI systems) and contributes to EU initiatives like IMPROVE (domestic violence response) and ELKARTEK (Industry 5.0 ethics). His collaborations span social organizations, enterprises, and research centers globally. Research Environment As a pillar of DeustoTech-Computing, he operates within a multidisciplinary unit advancing AI, cybersecurity, and Edge Computing applications. His leadership in projects like AI-Driven Cognitive Robotic Platforms and REal tiME control systems demonstrates integration of theoretical research with industrial implementation in smart manufacturing contexts.
María Belén Derqui Zaragoza is a Full Professor at the Department of Business Management, IQS School of Management, Ramon Llull University, where she conducts research and teaches in the field of consumer behavior. Her work integrates neuromarketing, sustainability, digital transformation, and crisis response, contributing to both academic and business communities. University: Ramon Llull University School: IQS School of Management Department: Department of Business Management Academic Rank: Professor Email: belen.derqui@iqs.url.edu Her research interests center on understanding consumer decision-making through interdisciplinary lenses. She applies neuromarketing tools such as EEG and eye-tracking to study emotional and cognitive responses to branding, advertising, and sustainable products. She also investigates the impact of digitalization, the gig economy, and global crises like the pandemic on consumer behavior. The trends in her recent publications reflect a consistent focus on sustainability, digital innovation, and behavioral insights. Her work spans neuromarketing applications, green consumerism, ethical branding, and technology adoption, often using neurophysiological methods to uncover subconscious drivers of choice. She is actively involved in several research projects funded by AGAUR and internal university grants, including: Conhative: Consumer Behavior Perspectives (2022–2025) EcoHarmony (2024–2027) NEUROSOLV: Neuromarketing Solutions (2024) MAGIC3RF: CO2 Capture Materials (2024–2025) The Impact of the Covid-19 Crisis on Local Products (2020) GIG Economy Study (2019) While no specific awards are listed, her sustained research productivity and leadership in multi-year, funded projects indicate recognition within her academic community. She collaborates with researchers across disciplines, suggesting an advisory or mentoring role, though specific student names are not provided. Her ORCID is 0000-0003-4882-129X . She is a key member of research groups such as CONHATIVE and contributes to interdisciplinary teams in projects like MAGIC3RF and EcoHarmony, which involve collaboration between business, engineering, and environmental sciences. Her work bridges academic research and practical applications in the Catalan and broader European business ecosystem.
