Samuel Edet is a PhD researcher working with the Analysis for Complex Economic Systems (AXES) group at the IMT School for Advanced Studies Italy and the Management, Strategy and Innovation (MSI) group at the Katholieke Universiteit Leuven, Belgium. The focus of his research is to investigate the innovation dynamics across global and non-global cities, their local and international connectedness, their rate of entry into new technology domains and the role of collaboration and multinational corporations in the innovation performance of cities. His research contributes to the growing discussion of innovations in cities and very insightful for developing strategic policies to increase the innovation performance of cities.

Prior to his doctoral program, he worked on the application of recurrent neural networks in forecasting S&P 500 index, and the application of fundamental group to hanging puzzle.

Samuel Edet was a nominee of the 2017 Thomson Reuters Excellence award for research in data science. He has been a recipient of scholarships and funding e.g. Erasmus mobility consortium, IMT doctoral scholarship, African Institute for Mathematical Sciences, University of Ibadan (UI) scholar, Mandela Rhodes(decline) etc.