Ana Catarina Nunes is an Assistant Professor at ISCTE-IUL. She has a PhD in Mathematics Applied to Economics and Management, a MSc in Operations Research, and graduated in Statistics and Operations Research. She teaches quantitative methods, namely Operations Research and Optimization. She has presented communications in several conferences, and has published in scientific journals such as the European Journal of Operational Research. Her research topics are operations research (combinatorial optimization), mainly on mathematical models and heuristics for the designs of routes and sectors for real applications in delivery and collection systems. In this context, she has been a researcher in projects supported by national funding from FCT (Fundação para a Ciência e a Tecnologia) focused on the efficient resource management in environmental services related to household refuse collection.

Ana Maria de Almeida has a Ph.D. in Applied Mathematics, with a specialization in Computer Science. Her research interests include Algorithmics, Complexity, Machine Learning and Pattern Recognition, Data Science, Evolutionary Computation, and Ethics for AI and Research. She also has a particular interest in the construction of self-adjusting predictive and reactive models for real applications, as well as in the development of evolutionary and hybrid strategies for tackling multicriteria combinatorial problems.  She participates and has participated in fundamental and applied research projects and research & innovation projects between academia and industry, both at national as well as international levels. 

Diana E. Aldea Mendes is an associate professor at Department of Quantitative Methods for Management and Economics, ISCTE-IUL Lisbon, Portugal. She is a mathematician and applied scientist with broad experience in nonlinear dynamics (stochastic and deterministic), time series analysis, data science, ML and deep learning, computational economics and finance, control and synchronization. She is a researcher at BRU-IUL (Business Research Unit - University Institute of Lisbon, Portugal) and has authored or co-authored more than 40 technical papers and reports.

Fernando Batista received his PhD (2011) in Computer Science and Engineering from Instituto Superior Técnico (IST). He is currently Associate Professor at Iscte - University Institute of Lisbon, and integrated researcher at INESC-ID, Lisbon. He is the Executive Coordinator of the Human Language Technologies Scientific Area at INESC-ID (2021-), and member of the Supervisory Board of CVTT - Iscte-Conhecimento e Inovação (since Apr.2021). He was President of the Pedagogical Council of ISCTE-IUL  (2017-2019), member of the Permanent Committee of the Pedagogical Council of ISCTE-IUL (2015-2017), and member of the Pedagogical Committee of the ISTA School (2015-2017). He is the scientific coordinator of the AppRecommender (2019-2021) project, has coordinated the INESC-ID team in the SpeDial project (2014-2015), and participated in several other European and National projects. His current research focuses on spoken and written Natural Language Processing, Machine Learning, and Text Mining for social media. He has been member of the organisation team of the LxMLS - Lisbon Machine Learning Summer School (since 2016), and was also member of the LxMLS technical staff between (2011-2015). He has participated in the organisation of several scientific events: editorial co-chair of PROPOR 2020, editorial chair of EAMT 2020, web chair of the IPMU 2020, co-chair of the Human-Human languages track of SLATE 2019, co-chair of the demos session in PROPOR 2018, publication chair of IberSPEECH 2016, co-chair of the PROPOR 2016 Student Workshop, publication chair of IberSPEECH 2016, co-chair of the PROPOR 2016 Student Workshop, and handbook chair of EMNLP 2015. He is Senior Member of the IEEE (since 2016), and member of the ISCA Speech (since 2008).

Ricardo Ribeiro is an Associate Professor at Iscte - Instituto Universitário de Lisboa and a researcher at INESC-ID Lisboa, where he is part of the Human Language Technologies research area.