Joao Comba

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.