Rachel McCarthy is a PhD researcher at University College Cork, where she previously earned a bachelor’s degree in ‘Digital Humanities and Information Technology’. After completing a master’s degree in ‘Digital Text Analysis’ at the University of Antwerp, she now focuses on computational literary studies. Her research involves using techniques such as stylometry, natural language processing, and language models to investigate authorship attribution and writing styles, and to track semantic changes in texts beyond traditional reading methods. Passionate about advancing text analysis, she aims to uncover new insights into literary and historical texts using digital methodologies.

Rasika Edirisinghe is a Visiting Lecturer at the University of Ruhuna, Sri Lanka and Sri Lanka Telecom Training Centre, specializing in Data Science, fundamentals of AI, and Business Intelligence. With an M.Sc. in Business Analytics from Robert Gordon University and over five years of industry experience across various data science roles, Rasika brings a wealth of practical and theoretical knowledge to academia. His research interests span NLP, Machine Learning, and Deep Learning, with a focus on sentiment reason mining and healthcare analytics. Rasika’s recent work includes developing a Twitter Sentiment Reason Mining Framework for the US healthcare industry. As a Data Analyst at EFL Global.llc, he has implemented data-driven solutions for automating business processes across global operations.

Ke Shu is currently a PhD student in Digital Humanities at Helsinki University, having previously graduated from Uppsala University with a degree in Language Technology. Her research interests lie at the intersection of computational methods and the humanities, with a particular focus on Natural Language Processing (NLP). Ke specialises in computational history, exploring 18th-century English political thought and the history of ideas. Her work aims to apply advanced computational techniques to better understand and analyze historical texts, bridging the gap between technology and humanities research.

Yu Wu is a PhD researcher at the University of Helsinki, focusing on adapting computational methods to address large-scale challenges in historical research. He previously completed a master’s degree in computer science at ShanghaiTech University, where his research primarily centered on vision-language reasoning in AI and multimodal machine learning models. His current work draws from expertise in both natural language processing and computer vision, specifically targeting semantic matching and ensuring robust computational measures that can adapt to diverse types of historical data. Yu is passionate about using computational tools to bridge the gap between humanities and technology, with a long-term goal of contributing new methodologies that can advance historical and literary research.

Bách PHAN-TẤT developed an interest in Linguistics in the third year of his Finance undergrad. He then obtained an MSc in Linguistics from the University of Stirling (Scotland) and is currently expanding his understanding of the fields of Linguistics and Cognition. His linguistic research interests include (Cognitive) Semantics, Language Variation and Change, Construction Grammar, Grammaticalisation. Bách is familiar with Quantitative/Statistical methods, Python Programming, and several Machine/Deep Learning models. He is currently a PhD student @ QLVL Research Group @ KU Leuven, working as part of the MSCA-funded Doctoral Network CASCADE.

Ángela María Gómez Zuluaga is a doctoral scholarship holder within the CASCADE MSCA network and is currently a member of the Quantitative Lexicology and Variational Linguistics (QLVL) research group at KU Leuven (Belgium). She holds a BA in English-Spanish-French Translation from the University of Antioquia (Colombia) and an MA in Theoretical and Applied Linguistics from Pompeu Fabra University (Spain), specializing in computational linguistics. For her MA thesis, she explored different proxies of context confusability and their capacity for predicting colexification in Spanish and English. Her research interests include distributional semantics, cognitive linguistics, language change, and using computational methods for linguistic research.

Formally trained in bioengineering then transitioned into computational linguistics, Sofía Aguilar Valdez is now a PhD researcher at the Universität des Saarlandes aiming to formalize the nuanced interactions that lead to semantic change and linguistic variation. Her approach involves using techniques such as natural language processing, scientometrics, and knowledge graphs to model contexts for diachronic text analysis. Addressing linguistic and paralinguistic features, she seeks to unveil how paradigm shifts occur in scholarly documents.

Anastasiia Vestel completed her MA at an Erasmus Mundus program called “European Master’s in Technology for Translation and Interpreting” (EM TTI), having studied at Ghent University, Belgium, and the University of Málaga, Spain. As an EM TTI student, she had the opportunity to acquire practical skills in the field of computational linguistics and natural language processing, which eventually led her to apply for a PhD at the CASCADE (MSCA) Doctoral Networks. Her research interests include literary machine translation, diachronic semantic change, as well as propaganda and disinformation detection.

Penelope Gia Bao Huu Nguyen is a doctoral researcher at the Digital Humanities Institute, the University of Sheffield. She holds a bachelor’s degree in English Studies from Can Tho University in Vietnam, where she first developed her passion for linguistics, particularly in the field of pragmatics. As a Fulbright scholar, she completed her master’s in Linguistics at Purdue University (USA), focusing on impoliteness and emoji usage on Vietnamese Facebook pages. Her research integrates computational and corpus linguistics to address questions that advance linguistic theory and interdisciplinary fields. Beyond research, Penelope is also an experienced literary translator, ESL teacher, and content creator.

Maria Jimena Flores is a doctoral research fellow and part of the CASCADE Doctoral Network who is currently based at The University of Sheffield. She earned her bachelor’s degree in Languages from Universidad de las Américas Puebla in México and went on to complete a master’s degree in Linguistics and Literary studies at Vrije Universiteit Brussels under the Mastermind Scholarship Scheme. She has a wide variety of research interests including language teaching and language acquisition, Spanish as a Foreign language, corpus linguistics and lexicography. Her current research focuses on the development of new methods for historical thesauri creation by blending aspects of techniques like hierarchical structures, word embedding and linguistic concept modelling.