The Qatar Centre for Artificial Intelligence (QCAI), part of Qatar Computing Research Institute (QCRI) under Hamad Bin Khalifa University, has launched a series of artificial intelligence (AI) lectures related to the novel coronavirus (Covid-19).
The lectures - six of them in total - by QCAI start tomorrow. They will explore the need to understand a pandemic like Covid-19 and how to contain it.
“Covid-19 is the first pandemic of the Information Age. There are two parallel pandemics. The first is the physical pandemic of infections, recoveries, deaths, hospitals, ventilators. The second is the information tsunami: flattening the curve, predictions, R0 (indicates how contagious an infectious disease is), drug repurposing and social distancing,” Dr Sanjay Chawla, research director at QCAI, told Gulf Times.
“The role of AI and data science is to create an accurate information filter to ‘make sense of’ and design better policies for managing the physical pandemic. There will be six lectures which elaborate on how AI and data science is being used,” he said.
The first lecture to be held tomorrow will be on ‘Data Visualisation and Exploration of Covid-19 Data’. QCRI experts will study several aspects of Covid-19 by reviewing the different types of visualisation techniques and challenges associated with them.
QCRI scientists Dr Nan Tang and Dr Mohamed Amin Sadeghi will discuss various aspects of the topic. 
“We need to analyse relevant data and develop an authentic and informative mental model. This can be carried out through ‘visualisation’ and ‘exploration’. There are many ways in which visualisations could lead to misleading conclusions; therefore, good visualisation is challenging,” Dr Chawla noted. 
The second half of the lecture will cover exploratory data analysis where experts will interpret visualisations, develop hypotheses, analyse them and compare the advantages and disadvantages of different visualisations. The lecture aims to review best practices in analysing the statistics of Covid-19.
Dr Tang is a senior scientist at QCRI and was formerly a research fellow at the Laboratory for Foundations of Computer Science at the University of Edinburgh.
His research interests focus on data preparation, data visualisation and collaborative data science.
Dr Sadeghi studies machine learning applications at QCRI. Earlier, he was an assistant professor at the University of Tehran. He graduated from the University of Illinois Urbana-Champaign. He has previously worked at Google, Amazon and Adobe. His research interests include machine learning, computer vision and their applications.

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