Research Roundup: Science & Technology Versus the 2019 Novel Coronavirus

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The world has quickly come to know and fear the word “coronavirus” — which comes from the Latin corona, referring to the viral particles’ halo-like appearance when viewed under a microscope. Coronaviruses cause respiratory tract illnesses and can infect both animals and people. The 2019 Novel Coronavirus has affected tens of thousands of people and killed over 700. The outbreak has also spread misinformation. In a bid to advance understanding of the coronavirus, Synced has assembled a selection of research papers and other resources that may be of interest to our readers.

Coronavirus Research at a Glance

Research Papers | Coronavirus Outbreak
– A Pneumonia Outbreak Associated With a New Coronavirus of Probable Bat Origin (Nature)
– A New Coronavirus Associated With Human Respiratory Disease in China (Nature)

Research Papers | Coronavirus Transmission
– Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia (New England Journal of Medicine)
– Study Claiming New Coronavirus Can Be Transmitted by People Without Symptoms Was Flawed (Science Mag)
– Transmission Dynamics of 2019 Novel Coronavirus (2019-nCoV) (bioRxiv)

Research Papers | Potential Treatments
– Baricitinib as Potential Treatment for 2019-nCoV Acute Respiratory Disease (The Lancet)

Research Papers | Coronavirus Prediction
– Novel Coronavirus 2019-nCoV: Early Estimation of Epidemiological Parameters and Epidemic Predictions (Medrxiv)
– Host and Infectivity Prediction of Wuhan 2019 Novel Coronavirus Using Deep Learning Algorithm (bioRxiv)
– Linearfold: Linear-Time Approximate Rna Folding by 5′-To-3′ Dynamic Programming and Beam Search (Bioinformatics)

Research | Coronavirus Maps
Coronavirus 2019-nCoV Global Cases by Johns Hopkins CSSE & Modeling the Spread of 2019-nCoV (John Hopkins)

Research | Information Collection Platforms on GitHub
WUHAN 2020 (GitHub)

New York Times Live Updates
Latest news and updates on Wuhan coronavirus and its spread in China and around the world, as well as medical and scientific information about surgical masks, treatments, vaccines, quarantines and more of what you need to know.
(New York Times)

Battling the Coronavirus: Alibaba and Baidu AI Accelerate Vaccine and Drug R&D
China’s big tech companies provide advanced AI algorithms to help global research institutes identify, predict and fight the 2019-nCoV.


ML-fairness-gym: A Tool for Exploring Long-Term Impacts of Machine Learning Systems
Google AI researchers demonstrate how the ML-fairness-gym can be used to research the long-term effects of automated decision systems on a number of established problems from current machine learning fairness literature.
(Google AI Blog) / (Paper)

An Opinionated Guide to ML Research
In this essay, John Schulman, a research scientist and founding member of OpenAI, provides some advice to up-and-coming researchers in machine learning (ML), based on his experience doing research and advising others. The advice covers how to choose problems and organize your time.
(John Schulman’s Blog)

Analysis of Gender Inequality in Face Recognition Accuracy
Researchers present a comprehensive analysis of how and why face recognition accuracy differs between men and women. They show that accuracy is lower for women due to the combination of (1) the impostor distribution for women having a skew toward higher similarity scores, and (2) the genuine distribution for women having a skew toward lower similarity scores.
(University of Notre Dame & Florida Institute of Technology)

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Machine Unlearning: Fighting for the Right to Be Forgotten
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IBM and China’s Digital Bank WeBank Jointly Held Workshop on Federated Learning
IBM and China’s leading digital bank WeBank jointly organized “Workshop on Federated Learning and Analytics (FL-IBM’20)” at IBM T.J. Watson Research Center. New methods of federated learning were shared by 9 invited speakers, and ideas were exchanged at the panel discussion on“Data Privacy and Regulatory Issues in AI: Enterprise and Customer Perspectives”.

Share My Research
Share My Research is a new Synced column that welcomes scholars to share their own research breakthroughs with global AI enthusiasts. Beyond technological advances, Share My Research also calls for interesting stories behind the research and exciting research ideas. Share your research with us by clicking here.

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Sr. SDET M Mehedi Zaman

Currently working as Sr. SDET at Robi Axiata Limited, a subsidiary of Axiata Group. As a Senior SDET: - Played a key role in introducing Agile Scrum methodology and implementing CI/CD pipeline to ensure quality & timely delivery. - Trained colleagues on emerging technologies, e.g. Apache Spark, Big Data, Hadoop, Internet of Things, Cloud Computing, AR, Video Streaming Services Technology, Blockchain, Data Science- Developed a test automation framework for Android and iOS apps - Developed an e2e web automation framework with Pytest - Performed penetration testing of enterprise solutions to ensure security and high availability using Kali, Burp Suite etc. - Learned Gauntlet security testing automation framework and shared the lesson learned in a knowledge sharing session

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