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Hamburg COVID-19 Serie

MITTWOCH, 24.3.2021 - 16 Uhr

Dr. Ayan Paul (DESY) spricht über ihre SARS-CoV-2 Forschung.

Viele Wissenschaftler in der Metropolregion Hamburg sind an der Forschung im Zusammenhang mit SARS-CoV-2 und der COVID-19-Pandemie beteiligt. In Zusammenarbeit mit der Helmholtz-Graduiertenschule für Data Science in Hamburg (DASHH) will der Leibniz ScienceCampus InterACt die Sichtbarkeit dieser Forschung erhöhen und neue Kontakte und mögliche Kooperationen fördern. Deshalb startete am 12. August die Hamburger Online-Vorlesungsreihe COVID-19. Die Reihe stellt eine einzigartige Plattform für einen lebendigen Austausch dar und findet alle zwei Wochen mit einem 30 minütigen Vortag statt mit Raum für weitere Diskussionen im Anschluss.

Am Mittwoch, den 24. März, um 16 Uhr wird Dr. Ayan Paul (Theoretical and Computational High Energy Physicist, Artificial Intelligence Researcher, Open Source Software Developer, co-founder of CoVis) wird Highlights aus seiner Forschung zu SARS-CoV-2 präsentieren. Wir freuen uns auf den Vortrag dieses interdisziplinären Forschers, der Einblicke geben wird, wie Big Data bei der Vorhersage von Immunität im Kontext von Contact-Tracing-Apps helfen könnte. Der Vortrag trägt den Titel "On Transmission Dynamics of COVID-19: A Physicist's Perspective". 

ABSTRACT (in Englisch)
The COVID-19 pandemic has now claimed a year of our lives. I will tell a story in four parts of how this year changed our perspective of how science is practised and its impact on humankind.
I will begin with the story of the success that never came: Automated Contact Tracing. I will elaborate on why it was destined to be so and how the reasons were overlooked. However, the efforts, by no means, are wasted. I will give some insights into possible future applications in vaccination distribution and immunization and possibly building exit strategies.
The second story will be about disparities and how it affected the spread of COVID-19 in the USA. While it is a land far away, it teaches us how the most vulnerable, in terms of health and their ability to react to a crisis, should be protected if the community as a whole needs to not see the worst kind of disease spread. I will also introduce the use of interpretable machine learning in the study of transmission dynamics showcasing how there is much to learn about causation from cooperative game theory.
The third story will be on the emergence of universality in the transmission dynamics of COVID-19. Data scaling principles are resurrected from half a century back to show that there is some method in the madness and that predictability can be achieved by the application of the same physics that goes into understanding phase transitions in fluids, magnets, granular media and several other physical systems.
In the final piece, I will relay an exciting journey made to deliver the fruits of scientific research and knowledge to your phones as a direct technology transfer from COVID-19 research at DESY. The project attracted the DESY Strategy Fund and the application, called CoVis, is going live in March and will be operated by a DESY spin-off company.


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