I am primarily interested in the field of 'Science of Science', in particular, topics like team assembly mechanisms, biases in academia and effect of university prestige on scientific mobility. The most ambitious goal would be to discover – in a data-driven fashion – ways of accelerating the collective knowledge discovery through suppression of bias, appropriately weighting prestige in career decisions and assembling teams which are more likely to be successful.
I also actively look around for topics and fields where network science has undiscovered applications. At the moment, areas of ‘Mental Health’ and ‘Climate Change’ seem most promising. I am looking to collaborate with experts from these areas who are interested in applying network science tools to produce data-driven insights. If you are a potential collaborator, please get in touch!
Alongside this, most branches of network science fascinate me, for every now and then, I enjoy some game theory, social contagion, and theoretical network models.
On a long day, I go for a long run (I’d rather play basketball/ football but that has been off-menu these days).