28/03/2024

Lucas Resende defends doctoral thesis on Monday (1st)

Next Monday (1st), Lucas Resende will defend his doctoral thesis “Robustness via trimmed sample means ” , at 4 pm, in room 232 of IMPA. The defense can also be followed on YouTube, at this link .

Originally from São João Del Rei (MG), the 26-year-old graduated in computational mathematics from UFMG (Federal University of Minas Gerais), an institution where he also completed his master's degree.

His love for mathematics has always been with him. In the 7th grade of elementary school, he won a silver medal at the OBMEP (Brazilian Mathematics Olympiad for Public Schools). This achievement increased his love for the subject, especially because upon entering university, the young man also began to participate in the Scientific Initiation and Master's Program , PICME.

After completing his master's degree, he chose IMPA for his doctorate because of the institution's renown and relevance. During his time at the institute, the young man also collaborated on two projects at the PI Center (IMPA's Center for Projects and Innovation), which develops technological solutions for companies and the public sector.

About to earn his doctorate, Lucas explained that his thesis, supervised by IMPA researcher Roberto Imbuzeiro, investigates the applications and properties of trimmed averages in the context of robust estimation using data from heavy-tailed or even contaminated distributions.

“It can happen that in an analysis, we have contaminated data, and with that we want to recover information that is closer to reality. My thesis outlines ways to do this, leaving the analysis clean and closer to the original data. We do this using the same strategy used to evaluate samba schools in the Rio Carnival: we discard the highest and lowest values and take the average of the rest. What we show in this work is that, in many aspects, this strategy is the best possible.”

In the second semester, Lucas will go to France to do a post-doctoral fellowship in an artificial intelligence project in healthcare.