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Universidade Presbiteriana Mackenzie (UPM). Escola de Engenharia (EE) (Institutional affiliation from the last research proposal) Birthplace: Brazil
Renata PELISSARI received the B.S. degree from University of São Paulo (USP), Brazil, in Mathematics in 2006. She holds a MSc degree (2009) in Applied Mathematics specialized in Probability and Stochastic Process, from the same university. In 2019, she concluded her PhD in Industrial Engineering at Methodist University of Piracicaba (UNIMEP), Brazil, having conducted a doctoral internship in the Telfer School of Management at University of Ottawa, Canada. Now, she is a Post-Doctoral fellowship in the School of Applied Sciences at University of Campinas (UNICAMP) in Brazil. Her research interest includes but is not limited to Multi-criteria Decision Making Aid (MCDA) under uncertainty, preference learning, and applied studies in Operations Management and Healthcare Management. She is also interested in software developments for decision-making applications. (Source: Lattes Curriculum)
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Recent studies have shown that algorithmic decision-making can be inherently prone to injustice. In fact, the increasing use of machine learning (ML) algorithms for decision-making in various fields has highlighted the problem of unintentionally replicating historical discrimination embedded in data related to sensitive attributes such as gender, race, skin color, and nationality. Althoug…
Multicriteria decision analysis consists of a set of principles and tools developed to assist in resolution of complex decision problems. One of the main features that distinguishes multicriteria decision methods from other methods in the fields of operational research and statistics is its high degree of incorporation of decision makers' preferences. Usually, preference information shoul…
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