Chrysoula Zerva is a post-doctoral researcher at the DeepSPIN Lab at Instituto Telecomunicacoes (IST). She previously worked as a post-doctoral researcher at the University of Manchester (NaCTeM group) and held the EPSRC doctoral prize fellowship (grant ref: EP/N509565/1), for the project: “Fake Health News: Leveraging scientific literature to validate misleading information”. She obtained her PhD degree in Computer Science from the University of Manchester (PhD thesis: “Automatic Identification of Textual Uncertainty”). She holds a MSc degree in Computer Science from Ecole Polytechnique Federale de Lausanne (EPFL) and a bachelor's degree from National Technical University of Athens (NTUA). Her research interests lie in the quantification of uncertainty with a focus on NLP applications and the evaluation of credibility and trustworthiness of information. She is also interested in model explainability within the context of evidence and explanation generation as well as the disentanglement of textual aspects as latent representations. During her PhD she contributed in various projects, including EMPATHY and Big Mechanism and worked on event extraction and quantification of uncertainty for extracted events. During the EPSRC DP fellowship she worked on the automated identification of cited evidence text spans across documents and won the best system award in the CL-SciSumm 2019 shared task.