Andreia Sofia Teixeira


I am an Assistant Professor in the Department of Informatics at the Faculty of Sciences, University of Lisbon and a Researcher at LASIGE, being the Co-Coordinator of the PhD Program in Complexity Sciences. I am also a member of the Executive Committee of the Network Science Society, a member of the council of the Complex Systems Society, the General Secretary of the Women in Network Science Society and the former Chair of the advisory board of yrCSS.

Additionally, I am the Program Chair of Complenet 2023 (Aveiro, Portugal), Organization Chair of Complexity 72h (Palma de Mallorca, Spain), one of the organizers of the AMETHYST: gAME THeorY in complex SysTems.

Previously I was a Research Scientist at Hospital da Luz Learning Health, and a Collaborator at INESC-ID. Between August 2019 and December 2020 I was a Postdoctoral Researcher at Indiana University Bloomington, and a Fellow at IU Network Science Institute (IUNI), Indiana, United States. Between 2013 – 2018 I was a teaching assistant at the Department of Computer Science and Engineering of Instituto Superior Técnico and between September 2018 – August 2019 I was an Invited Assistant Professor at the Department of Informatics of Faculdade de Ciências da Universidade de Lisboa (FCUL). In 2017 (June and July), I was also as an invited junior researcher in Kyushu University, Japan, contributing to the the BIRD’s Research Project in Task 1 – Algorithms for Sequence Analysis – and Task 2 – Compression and Indexing Techniques for Repetitive Data.

I have a PhD (July, 2019) in Information Systems and Computer Engineering from the Department of Computer Science and Engineering of Instituto Superior Técnico (IST), Universidade de Lisboa (Portugal).

My research interests are:

  • Graph Theory / Algorithms on Graphs
  • Network Science / Complex Systems
  • Computational Cognitive / Social Sciences
  • Computational Medicine/ Epidemiology / Biology
  • Network Neuroscience
  • Human Behavior / Evolutionary Game Theory

My research work is focused on the development of measures, computational models and simulation frameworks to understand structure and dynamics of collective behavior in complex systems, using and developing Network Science and Machine Learning techniques.

(photo by Marta Banza)