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Title: Data Visualization for The Understanding of COVID-19
 
Speaker: Joao Comba (UFRGS)
 
Abstract: In this talk, I will describe several data visualization
projects related to COVID-19 data analysis. The first work describes
an analysis tool for comparing the evolution of COVID-19
data in different regions worldwide. The main component of our tool is
a similarity engine that searches for similar patterns of COVID-19 time
series and a storytelling dashboard that identifies the waves of COVID-
19. We also introduce a new type of difference plot that allows a more
straightforward comparison of time series evolution. The second work
leverages the big-data infrastructure we developed for real-time
analysis to study two years of clinical admissions in the public health
system of Brazil, composed of more than 100 million records. The third
work is related to the diagnosis of COVID-19 from computed tomography
and clinical data. We will describe COVID-VR, a novel approach for
classifying pulmonary diseases based on volume rendering images of the
lungs taken from different angles, thus providing a global view of the
entire lung in each image. I will conclude the talk with a summary of
my current research projects.
 
Short-bio: João L. D. Comba is a Full Professor at the Instituto de
Informática at UFRGS, where he conducts research activities,
undergraduate and graduate education, and supervises doctoral,
master, and scientific initiation students. He holds a Ph.D. in
Computer Science from Stanford University, United States. 2000. His
research areas include data visualization and analysis, data science,
geometric algorithms, and spatial data structures. He is currently co-
chair of the Visualization Corner of the Journal Computing in Science &
Engineering and associate editor of the Computer & Graphics Journal.