Lavinia Mendes Araujo

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Lavinia Mendes Araujo

Visiting Graduate Researcher
Federal University of Pernambuco

Lavinia Mendes Araujo is a Ph.D. Candidate in Industrial Engineering at the Universidade Federal de Pernambuco (UFPE), Brazil, where she also completed her M.Sc. She holds a Bachelor's degree in Industrial Engineering from the Universidade Federal da Paraíba, with a year in France at the École de Génie Industriel – Grenoble INP as part of an exchange program. She is a member of the Center for Risk Analysis, Reliability Engineering, and Environmental Modeling (CEERMA/UFPE) and is part of the human resources program of Brazil's National Agency for Petroleum, Natural Gas, and Biofuels. Currently, she is involved in a research project in collaboration with the R&D center of a company in the Brazilian oil and gas sector. Her Ph.D. research focuses on modeling and solving reliability engineering problems in the energy industry through quantum methods, emphasizing combinatorial optimization and machine learning. During the six months as a visiting graduate researcher at UCLA, she will work under the supervision of Professor Droguett, concentrating on quantum computing methods.

Djayr Alves Bispo Junior

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Djayr Alves Bispo Junior

Visiting Graduate Researcher
Federal University of Pernambuco

Djayr Alves Bispo Junior is a Ph.D. Candidate in Mechanical Engineering at the Federal University of Pernambuco (UFPE), Brazil. He holds a bachelor's degree in Mechanical Engineering from the Federal University of Campina Grande (UFCG) and a master's degree from the Federal University of Paraíba (UFPB). He is also specialized in Occupational Safety Engineering. Currently, he is a Visiting Graduate Researcher at the University of California, Los Angeles (UCLA), in the Civil and Environmental Engineering Department. During his master's degree, Djayr Bispo focused on research related to the energy utilization of biogas from landfills. His Ph.D. research focuses on deep learning models to predict wind power generation and wind speed, with the aim of maximizing the productive efficiency of wind farms. He is also involved in a research project funded by a Brazilian energy company, in partnership with UFPE, focused on developing a computational tool for Energy Performance Assessment to optimize Predictive Maintenance strategies.