Tue, 07/07/2020 - 14:44
In this webinar, experts from QCRI-QCAI will discuss the outcomes of COVID-19: the ‘real’ and physical reality on the ground, and the overload of new information.
The physical outcomes are the numbers of people getting infected, rates of recoveries and deaths, managing hospitals, ICUs and equipment. In turn, the information outcomes are about ‘R0’, flattening the curve, testing strategy, drug repositioning, and dissemination of information on social media.
This webinar will also shed light on the role of AI and Data Science in creating an accurate filter on the information outcome, to “make sense” of and help design better policies to overcome the physical outcome
is a principal scientist and the acting managing director of the Arabic Language Technologies at QCRI with an interest in natural language processing (NLP), social computing, and information retrieval. He is currently developing a state-of-the-art Arabic NLP toolkit, which includes POS tagging, named entity recognition, parsing, etc. Darwish is also working on the automated detection of propaganda accounts on social media and stance detection in social computing.
is a principal scientist at QCRI. His research interests include computational linguistics and NLP, disinformation, propaganda, fake news and bias detection, fact-checking, machine translation, question answering, sentiment analysis, lexical semantics, web as a corpus, and biomedical text processing. He is the Principal Investigator (PI) of the QCRI mega-project, Tanbih. He is also the lead-PI of a QCRI-MIT collaboration project on Arabic Speech and Language Processing for Cross-Language Information Search and Fact Verification.
Is the Research Director of the Data Analytics Group and the Qatar Center for Artificial Intelligence (QCAI), QCRI. His research interests are data mining, machine learning and spatial data management.
Has been a principal scientist at QCRI since 2011. Ouzzani's research interests lie in the fields of data management and analytics with a focus on data integration, data cleaning, and collaborative data science. He is the project lead of Rayyan, the leading systematic reviews web and mobile app, that now serves more than 55k users worldwide.
PhD is a principal scientist and leads the Digital Health group within QCRI. His areas of interest are in machine learning, specifically applications for healthcare analytics including clinical informatics, health economics outcomes research, signal detection, disease progression modeling, predictive modeling and risk stratification.
Is the Senior Research Director at QCRI. His research focuses on databases and distributed systems. Aboulnaga has received a Google Research Award, the Ontario Early Researcher Award, and Best Paper Awards at the VLDB 2011 and SoCC 2015 conferences. He is an IEEE Senior Member and an ACM Distinguished Scientist.