Alessio Ferrari is a Lecturer at University College Dublin (UCD), Ireland, and a Senior Research Scientist at Consiglio Nazionale delle Ricerche Istituto di Scienza e Tecnologie dell’Informazione “A. Faedo” (CNR-ISTI), Italy. He received a Ph.D. in computer engineering from the University of Florence in 2011. He has about 17 years of research experience, and 3 years of industrial experience at General Electric Transportation Systems, a world-leading railway signalling company.

His main research interests are software engineering and requirements engineering. In particular, his research focuses on: (a) application of natural language processing technologies and large language models to requirements engineering, with a focus on detection of ambiguity and communication defects in requirements documents; (b) requirements elicitation by means of interviews, workshops, focus groups, and model-based prototyping; and (c) software process improvement for safety-critical systems, with a focus on formal/semi-formal model-based development and code generation in the railway domain.

He is a co-author of more than 100 publications in international conferences and journals. In 2015 and 2018, he received the Best Paper Award at the IEEE RE conference. He co-organised the NLP4RE workshop and AIRE workshop in multiple editions, regularly serves on the program committee of international conferences such as ICSE, RE, and REFSQ, and he is part of the Steering Committee of IEEE RE and REFSQ. He is part of the Editorial Boards of ACM Transactions of Software Engineering and Methodology (TOSEM), Springer Requirements Engineering Journal, and Springer Software Quality Journal. He has been the organiser of REFSQ 2020, PC co-chair of REFSQ 2023, and PC co-chair of RE 2025. He participated in several FP7, H2020, and Horizon Europe EU projects, such as LearnPAd, ASTRail, 4SecuRail, DESIRA, and CODECS. He has been also actively involved in technology transfer studies with railway companies, such as Alstom, GE Transportation, SIRTI, Trenord, and Caterpillar.