HBKU’s QBRI organizes webinar series to discuss COVID-19 related issues
Qatar Biomedical Research Institute (QBRI) at Hamad Bin Khalifa University (HBKU) had organized two webinars to assist policymakers in accurately forecasting and responding to COVID-19 outbreaks, as well as supporting the next generation to pursue a career in biotechnology.
QBRI held a webinar titled Pursuing Careers in the Biotech Industry, on November 18. During the webinar, Dr. Lawrence Stanton, Director of the Neurological Disorders Research Center at QBRI, shared his perspective on careers in the biotechnology industry, particularly the transition from academia to industry and the key differences between these two research environments.
The required skill set for pursuing a career in the biotech industry, which has been playing a major role globally in developing diagnostics, therapies, and vaccines to fight the coronavirus was also explored.
QBRI’s webinar series featured inspiring talks from pioneers who discuss their personal journey in a scientific career, with the aim of sparking conversation among young minds to actively pursue personal and professional development.
QBRI is also hosting another webinar series, in relation to the career development series, dedicated to highlighting various topics of current global significance. On November 9, COVID-19 Outbreak Prediction and Assessment of Prevention Policies: A Data Science Approach presented to the audience, two COVID-19 prediction models.
Based on information from countries with similar demographic, socioeconomic, and health sector indicators, the first module used a deep learning approach to forecast the cumulative number of cases. The model also took lockdown measures into perspective.
The second method used a deep learning model for evaluating and predicting the impact of various lockdown policies on daily COVID-19 cases. This was possible by group countries with similar lockdown policies, then training a prediction model based on the daily cases in each cluster along with the data describing their lockdown policies. Once the model is trained, it is used to evaluate scenarios associated with lockdown policies and investigate their impact on predicted COVID-19 cases.
Dr. Abdelkarim Erradi, Associate Professor in the Computer Science and Engineering Department at Qatar University, whose research activities and interests focus on service-oriented computing, cloud services composition, and mobile crowdsensing presented these models.
Qatar was the focus of the compelling case study during the webinar and highlighted the potential consequences of lifting restrictions without fully taking into account what the data reveals about the current status of COVID-19.
Dr. Erradi explained that data science and recent advances in machine learning can be used to gain a better understanding of the COVID-19 outbreak. The trained prediction model allows for the evaluation of various what-if scenarios related to lockdown policies, such as easing travel restrictions and quantifying their impact on predicted COVID-19 cases.
Dr. Julie Decock, QBRI scientist and moderator of the webinar said, “While policymaking responses to COVID-19 vary from one country to another, all are united by the need for accurate forecasting of the coronavirus’ propagation. This webinar demonstrated that data science approaches have an important role to play in predicting and tracking the spread of COVID-19. As always, we enjoyed hosting our colleagues from Qatar University.”
For more information on QBRI’s initiatives and research, please visit qbri.hbku.edu.qa
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