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Jayanta Mandi
Jayanta Mandi is a doctoral candidate in the Faculty of Economic, Social and Political Sciences at Vrije Universiteit Brussel. He is also a research associate in the MOBI research group at Vrije Universiteit Brussel. After acquiring his master's degree in data science and analytics from Indian Statistical Institute (ISI), Kolkata in 2015, he gained industry experience in data science for one year. His current research, under the supervision of Prof. Dr. Tias Guns, started in December 2018 and lies at the confluence of machine learning, data mining and optimisation, with a special focus on developing innovative methodologies for data-driven optimisation in logistics.
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How to ease Covid-19 lockdown? Forward guidance using a multi-dimensional vulnerability index
While extending the nationwide Covid-19 lockdown for two more weeks starting 17 May 2020, the government has given major relaxations for public movement and economic activity in non-containment zones in India. Essentially the current method for classifying all the districts into zones is unidimensional in nature, relying primarily on the existing penetration of the infection as a predictor of future spread. Chakrabarty, Mandi, and Mukherjee construct a multi-dimensional Vulnerability Index for Indian districts that can provide guidance for lifting the lockdown sequentially.
