Frank den Hollander
Frank den Hollander received his PhD at the University of Leiden in 1985. From 1985 to 2005 he worked at the universities of Delft, Utrecht, Nijmegen and Eindhoven. He is currently professor of probability theory at the University of Leiden. His research covers probability theory, statistical physics, ergodic theory, population genetics and complex networks. His main focus has been on interacting particle systems, phase transitions and disordered media. He was visiting professor in Bonn, Erlangen, Gottingen, Heidelberg, Toronto and Vancouver. Frank was elected to the Royal Netherlands Academy of Sciences in 2005. In 2016 he became Knight in the Order of the Dutch Lion. In 2018 he received a Humboldt Research Award. He has served on national and international advisory boards, and has co-organised 55 national and international workshops. He is the author of 170 research papers and 3 monographs. He has supervised 27 PhD students and 34 postdocs. Frank has received multiple grants from the Netherlands Organisation for Scientific Research, as well as an Advanced Grant from the European Research Council. He is also one of the Principle Investigators of the Dutch Gravitation program NETWORKS.
My name is Ines Lindner. My background is Mathematical Economics. The reason why I started to work on the topic networks is that it enriches existing classical social and economic theories. In fact, I have often experienced that it answers long tackled open questions.
Michel Mandjes is a professor of applied probability at the University of Amsterdam, with a broad interest in probabilistic modelling and its applications in various domains. A special interest area concerns networks and their random dynamics. Recently, with my PhD student Danny Chan (Transtrend and the University of Amsterdam) we have been starting a research line on opinion formation.
Valentin is a MPhil student at the Tinbergen Institute and is writing his thesis with Ines Lindner and Bernd Heidergott on the topic of using complex networks to shed light on the frailty index and human mortality. More broadly, he is interested in using network theory in tackling disinformation, modeling polarization in media, and the effects these two forces have on the ability of society to make decisions. Whether they are diseases, opinions, or damage, modeling these processes on complex networks is key to tackling the challenges of our time.