[ABE-L] Ciclo de Palestras PPG Estatística UFRJ (Dário Oliveira FGV/EMAp - 12/04 às 15:30h)

[Viviana Lobo]

Prezados,
dando continuidade ao Ciclo de Palestras do Programa de Pós-Graduação
em Estatística do IM-UFRJ,  *na próxima 4a feira, 12/04/2023, às 15:30h*,
teremos a palestra do professor e pesquisador:

*Palestrante: *Dário Oliveira (FGV/EMAp)


*Title*: Machine Learning to approach sustainability using scarcely labeled
to unlabeled earth observation data



*Abstract*: In the last decades, a debate on a responsible, sustainable
human presence on Earth emerged strongly. With climate change and the
overwhelming economic pressure on Nature, empowering procedures for
efficient resource use with the recent advances in artificial intelligence
is vital to create adequate policies and trigger warning alerts
accordingly. Remotely sensing natural dynamic phenomena, like phenological
crop cycles or deforestation processes, is challenging. Continuous and
smooth physical processes usually rule such phenomena, but remote sensing
involves different sensors with very different essence, scale, and visit
rates, corrupted by stochastic events, resulting in highly complex
multimodal multitemporal and multi-scale datasets. Moreover, data labeling
in Earth Observation (EO) applications is usually scarce or unavailable due
to the massive amount of data continuously acquired or notorious fieldwork
limitations. This presentation discusses machine learning approaches for
earth observation data with scarce labeling, aiming to develop
environmental protection solutions, promote efficient tools to adapt to
EO's global warming effects, and support efficient agricultural practices
with a lower data annotation burden.


*Bio*: Dario Oliveira received his M Sc. (2009) and Ph.D. (2013) degrees in
Electrical Engineering from the Pontifical Catholic University of Rio de
Janeiro, Brazil. He was a visiting scholar at the Instituto Superior
Técnico in Lisbon, Portugal (2008-2009) and the Leibniz University of
Hannover in Germany (2011-2012). As a postdoctoral fellow, he studied
machine learning applied to neuroscience at the University of Sao Paulo,
Brazil (2014-2015) and applied to dairy science at the University of
Wisconsin, USA (2020-2021). From 2015 to 2021, he worked in the industry at
the General Electric Global Research Center in Rio de Janeiro and later at
the IBM Research lab in São Paulo, Brazil. From 2021 to 2022 he worked as a
Guest Professor at the AI4EO lab at the Technical University of Munich,
Germany. He currently works at the School of Applied Mathematics, Getulio
Vargas Foundation, Rio de Janeiro, Brazil.


As palestras ocorrem *de forma presencial *às quartas-feiras às 15:30h
no *Laboratório
de Sistemas Estocásticos no Bloco I sala 044-b (subsolo)*, do Centro de
Tecnologia, Ilha do Fundão da Universidade Federal do Rio de Janeiro.

abs
viviana

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