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Teaching Staff

Biography

Américo Rio is an Invited Assistant Professor at NOVA Information Management School (NOVA IMS), Universidade NOVA de Lisboa. His teaching and research focus on artificial intelligence, information systems, software engineering, big data, and data- and AI-intensive applications. At NOVA IMS, he teaches across undergraduate, master's, and postgraduate programmes in areas including Agentic AI, Artificial Intelligence and Machine Learning in Healthcare, AI Tools for Business Professionals, Big Data Analytics, Generative AI, Web Technologies, and Mobile Application Development. His research builds on a background in software engineering and information systems, particularly software quality and evolution, and currently extends to intelligent information systems, generative and agentic AI, data-intensive systems, and the application of AI in organizational and societal contexts. His work has been published in journals including Empirical Software Engineering and the Journal of Systems and Software. He has more than 20 years of experience in software development and technology project management and was co-founder of Itcode. He previously taught at ISCTE-IUL and Universidade Europeia. He holds a PhD in Information Science and Technology from ISCTE-IUL, a Master's degree in Computer Engineering from NOVA FCT, and a five-year pre-Bologna degree in Physics Engineering from NOVA FCT. He also holds a postgraduate qualification in Entrepreneurship and Business Creation from ISCTE-IUL.

Scientific Publications

Rio, A., Abreu, F. B. E., & Mendes, D. (2024)

Causal inference of server- and client-side code smells in web apps evolution. Empirical Software Engineering, 29(5), 1-46. Article 133. https://doi.org/10.1007/s10664-024-10478-0

Rio, A., & Abreu, F. B. E. (2023)

PHP code smells in web apps: Evolution, survival and anomalies. Journal of Systems and Software, 200, 1-23. [111644]. https://doi.org/10.1016/j.jss.2023.111644

Rio, A., & Abreu, F. B. E. (2021)

Detecting Sudden Variations in Web Apps Code Smells’ Density: A Longitudinal Study. In A. C. R. Paiva, A. R. Cavalli, P. Ventura Martins, & R. Pérez-Castillo (Eds.), Quality of Information and Communications Technology - 14th  International Conference, QUATIC 2021, Proceedings (pp. 82-96). (Communications in Computer and Information Science; Vol. 1439 CCIS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-85347-1_7

Rio, A., & Abreu, F. B. E. (2019)

Code Smells Survival Analysis in Web Apps. In M. Piattini, P. R. D. Cunha, I. García Rodríguez de Guzmán, & R. Pérez-Castillo (Eds.), Quality of Information and Communications Technology : 12th  International Conference, QUATIC 2019, Ciudad Real, Spain, September 11–13, 2019, Proceedings (pp. 263-271). (Communications in Computer and Information Science; Vol. 1010). Springer. https://doi.org/10.1007/978-3-030-29238-6_19