Prof. Way is a Full Professor in the School of Computing in DCU. He is Deputy Director and Co-Applicant of ADAPT, the €100 million SFI-funded Centre for Digital Content Technology, where he also leads the Machine Translation group. He was the recipient of the 2015 DCU President’s Research Award for Science and Engineering, and in 2019, received the extremely prestigious Award of Honour from the International Association for Machine Translation for his services to the community. Prof. Way has secured grants totalling over €100 million, with over €12 million directly for his own research. Prof. Way served as President of the European Association for Machine Translation from 2009-2015, and was President of the International Association for Machine Translation from 2011–13. He has been Editor of the Machine Translation journal since 2007. He is currently editing a series of six books for Springer in the area of Machine Translation. Prof. Way has published over 400 peer-reviewed papers, and currently has a Google Scholar h-index of 44, and over 7,000 citations for his research. He has successfully graduated 28 PhD students, five of whom have won Best Thesis Awards, and 11 M.Sc. students. He currently supervises 5 PhD students, and 15 postdoctoral researchers.

Joni Dambre has a background in electronics science engineering (MSc) and computer science engineering (PhD), with experience in digital hardware design, physical reservoir computing, machine learning and (deep) artificial neural networks. She is a tenured professor at Ghent University and one of the three professors leading the AIRO research team of IDLab (Ghent University and imec). Together, the AIRO members explore new horizons in AI and robotics. We take inspiration from biology by firmly connecting robotic learning to compliant physical embodiment, we co-optimise brains and bodies, and exploit multi-modality and interaction with the environment. We develop robots that learn from human examples, mimic or support human learning processes and pose socially acceptable behaviour when interacting with people. We also aim to develop more data-efficient and resource-efficient AI-realisations by more directly exploiting the natural dynamics of computational media and investigate which learning mechanisms from biological neural systems are useful and computationally efficient in artificial (digital or analog) computing substrates. In the early days of the “Deep learning revolution", we started addressing the specific problem of developing agents that can understand sign language from video. Today, we are at the point where we hope to connect our work to powerful NLP models to achieve actual, real-time translation. The SignON project offers the opportunity and the network to achieve this and its community-driven co-development approach will ensure that our developments are maximally useful for all parties involved.

Myriam Vermeerbergen is Associate Professor at KU Leuven, where she teaches general linguistics, general sign language linguistics and several courses on (socio)linguistic aspects of Flemish Sign Language (VGT). In the early 1990s, Myriam pioneered research on VGT and the Flemish Deaf community. As an PhD Fellow of the Research Foundation-Flanders (FWO-Vlaanderen) she worked on the very first large-scale analysis of the grammar of Flemish Sign Language. As of 1997, as a postdoctoral researcher, she further explored the grammar of VGT and participated in international cross-linguistic research and sign language typology projects. In 2008, Myriam joined KU Leuven. As chair of the new Flemish Sign Language Language Group, she and her deaf colleagues worked on the integration of Flemish Sign Language in the Bachelor of Applied Language Studies and the Master in Interpreting. They also founded the Postgraduate Programme in Flemish Sign Language Interpreting. KU Leuven is the first and only institution to offer this academic training programme for VGT interpreters. As one of the few linguists interested in Flemish Sign Language, Myriam also participated in sociolinguistic studies, projects related to the Flemish (and South African) Deaf community, and lexicographical work. She was one of the supervisors of the first lexicographical research which formed the basis for the first digital translation dictionary for Flemish Sign Language, (https://woordenboek.vlaamsegebarentaal.be), and co-supervisor of the Hercules project “Corpus Vlaamse Gebarentaal” (https://www.corpusvgt.be). Myriam is co-founder and former chair of the Flemish Sign Language Centre, recognised by the Flemish Government as a “knowledge and coordination centre for Flemish Sign Language” (www.vgtc.be). She is the current vice-chair of the Advisory Committee on Flemish Sign Language. On an international level, she is a founding member and former board member of the Sign Language Linguistics Society (https://slls.eu) and served several terms as an expert for the World Federation of the Deaf (https://wfdeaf.org).

Professor Lorraine Leeson (female) holds a Dip. Deaf Studies (interpreting), M.Phil Linguistics, PhD. Linguistics. Cert. Gender Studies. She is Professor in Deaf Studies at the Centre for Deaf Studies, School of Linguistics, Speech and Communication Sciences and Associate Dean of Research (Research Integrity) for Trinity College Dublin (2018-present). Prof Leeson has worked with Deaf communities in a range of capacities since 1990. She served as inaugural Director of the Centre for Deaf Studies at Trinity College Dublin from 2001-17. Her research work is multidisciplinary in nature. Her doctoral work was the first to examine aspects of the morphosyntax of Irish Sign Language, and subsequent to this, she has published widely on aspects of the grammar of Irish Sign Language, as well as on applied linguistics topics, including a significant body of work on sign language interpreting (16 books, 58 papers, 13 edited volumes (journals/monographs) and 100+ peer-reviewed conference papers). She was named a European Commission European Language Ambassador for her work on sign languages in 2008. Lorraine was a member of the first cohort of professionally trained Irish Sign Language/English interpreters in Ireland, and she continues to interpret. She has engaged in pan-European research work with academic institutions, Deaf communities and interpreting organisations since 1990, serving as Chair of the European Forum of Sign Language Interpreters Committee of Experts (2013-2019). She is a member of the Royal Irish Academy’s Committee on Languages, Literatures and Cultures (LLC) (2018-present).

Dr. Dimitar Shterionov is an assistant professor in the Department of Cognitive Science and Artificial Intelligence, School of Humanities and Digital Sciences. He is an experienced researcher in MT and NLP, an expert in a plethora of subtopics of MT such as low-resource MT, quality estimation, automatic post-editing, evaluation of MT quality and usability, speech-to-text and text-to-speech translation, etc. He has also experience with user-centred development of software solutions, as well as cloud-based solutions to MT, e.g., KantanMT. Dimitar has obtained a PhD in computer science engineering from KU Leuven in 2015 on the topic of Probabilistic Logic and Learning. After that he moved to industry and joined the team of KantanMT to work on their cloud-based customizable statistical machine translation system. In 2016, he was appointed head of research at KantanMT. His team developed the first cloud-based, customizable and publically available neural machine translation solution, released in early 2017. In November 2017, Dimitar joined the ADAPT team of Prof Andy Way as a post-doctoral researcher to work on industry-oriented MT and NLP projects. In January 2020 Dimitar assumed a position as an assistant professor in the School of Computing at DCU and soon after, in August 2020, moved to take a new role as an assistant professor at the School of Cognitive Science and Artificial Intelligence at TiU. In his academic career Dimitar has published over 30 papers in national and international conference proceedings and journals; he has completed 4 large-scale and 5 small-scale projects. In the last 2 years, Dimitar’s research has focused on Automatic Post-editing, Quality Estimation, MT for low-resource languages, Lexical richness of MT and Cross-lingual Information Retrieval. He also actively participates in cross-field collaborations (e.g. in the medical, arts and legal domains). at KantanMT. His team developed the first cloud-based, customizable and publically available neural machine translation solution, released in early 2017. In November 2017, Dimitar joined the ADAPT team of Prof Andy Way as a post-doctoral researcher to work on industry-oriented MT and NLP projects. In January 2020 Dimitar assumed a position as an assistant professor in the School of Computing at DCU and soon after, in August 2020, moved to take a new role as an assistant professor at the School of Cognitive Science and Artificial Intelligence at TiU. In his academic career Dimitar has published over 30 papers in national and international conference proceedings and journals; he has completed 4 large-scale and 5 small-scale projects. In the last 2 years, Dimitar’s research has focused on Automatic Post-editing, Quality Estimation, MT for low-resource languages, Lexical richness of MT and Cross-lingual Information Retrieval. He also actively participates in cross-field collaborations (e.g. in the medical, arts and legal domains).

I am a postdoctoral researcher at the Cognitive Science and Artificial Intelligence department, at Tilburg University. My research, within the SignOn Project, focuses on Machine Translation between verbal and sign languages. Before, I was postdoctoral researcher in the digital humanities project POSTDATA at UNED (National University of Distance Education) of Madrid. I completed my PhD at Meertens Institute and Radboud University Nijmegen. In my dissertation, I combined a theoretical phonological-metrical approach with computational methods for investigating the interface between phonological and metrical structure. For part of my project, I used a machine learning model for automated annotation of lexical stress in Dutch Renaissance poetry. During my PhD, I spent three months at the University of Oxford, where I designed and ran a behavioural experiment on the English phonological foot. I hold a Research Master’s degree in Linguistics by Leiden University and a Bachelor’s degree in Modern Languages and Literatures, with a major in English and Spanish literature, by the University of Naples Federico II. Before starting my PhD, I briefly worked in the industry where I contributed to an automated speech recognition project. My fields of interest are linguistics, phonology, poetic metrics and the application of natural language processing and computational techniques to their investigation.

Irene Murtagh is an academic and a researcher at the Department of Informatics, TU Dublin and an Adjunct Assistant Professor at the Centre for Deaf Studies, Trinity College Dublin. After completing her BSc. (Hons) in Computing at the Institute of Technology Blanchardstown, Irene carried on her studies to Level 9 by completing an MPhil. in Speech and Language Processing at the Centre for Language and Communication Studies in Trinity College Dublin. Her MPhil. Thesis, “Analysing Voice Source Correlates of Affect in a Corpus of Japanese Expressive Speech”, was supervised by Dr Christer Gobl. Irene went on from here to complete a PhD in Linguistics (by research) at the Centre for Language and Communication Studies in Trinity College Dublin. Her PhD thesis is titled: Developing a Linguistically Motivated Computational Framework for Irish Sign Language, and was supervised by Professor John Saeed and Dr Brian Nolan. Her research interests include: Research in computational linguistics/linguistics using applications of the functional linguistic model of Role and Reference Grammar, sign language linguistics, linguistically motivated embodied conversational agents and avatar technology, speech acoustic processing, natural language processing and computational linguistic applications within the domain of artificial intelligence and cognitive technology.

Zaid Mohammed is a PhD student at the Informatics Department, Technological University Dublin, Ireland. His main research focuses on linguistic analysis of the sign languages as part of the SignON project. He holds a BSc (Hons) in Computer and Software Engineering (University of Technology, Iraq) and a MSc in Software Design with Artificial Intelligence (The Technological University of the Shannon: Midlands Midwest, Ireland).