Maya Wardeh

Dr Maya Wardeh is a researcher at the Faculty of Health and Life Sciences at the University of Liverpool, specializing in computational approaches to disease ecology and integrative virology. After obtaining her PhD in Computational Argumentation (University of Liverpool) and MEng in Information Technology (University of Damascus), she transitioned from computer science to epidemiology, focusing on machine learning and big data analysis of host-pathogen networks.

• Education: MEng (Information Technology, University of Damascus), PhD (Computational Argumentation & Data Mining, University of Liverpool)

Her research integrates machine learning, complex network analysis, and big data epidemiology to address critical questions about host-pathogen associations. Key projects include developing the Enhanced Infectious Diseases Database (EID2) and predicting zoonotic reservoirs for betacoronaviruses. She has secured grants from UKRI and BBSRC for her work.

Recent work focuses on multi-perspective prediction of host-pathogen associations, analyzing evolutionary signatures to predict viral transmission routes, and characterizing life-history patterns of mammalian viral carriers. Her methods combine viral traits, mammalian characteristics, and network features to enhance predictive accuracy, identifying over 20,000 previously unknown virus-mammal associations.

Scientific Awards:

• NPIF Fellowship (UKRI)
• BBSRC Grant for Big Data Approaches to Host-Pathogen Mapping
• BBSRC Grant for Predicting Animal Hosts for Coronavirus Recombination

Dr Wardeh contributes to teaching through modules in Database and Information Systems (COMP518) and Emerging Infections and Pandemics (LIFE751/IVES711), emphasizing data-driven approaches to infectious disease understanding.