Dr Chaimaa Tarzi is a Lecturer in Computing & Games at Teesside University, within the Department of Computing & Games. She holds a PhD in Computer Science from Teesside University (2025) and an MSc in Software Engineering (2019) from ENSIAS Rabat, Morocco. Her early academic background is rooted in Mathematics and Physics, having completed the Classe Préparatoire Scientifique aux Grandes Écoles in Nîmes, France (2014).

Chaimaa’s research lies at the intersection between community metabolic modelling, computational biology, and machine learning, with a strong focus on understanding the metabolic behaviour of microbial communities in health and disease. In collaboration with Complement Genomics Ltd, her work investigates biofilm dynamics in mixed microbial populations, aiming to reconstruct pairwise genome-scale metabolic (GEM) models from metagenome-assembled genomes (MAGs).

Her current research explores community-level modelling frameworks to refine metabolic networks and elucidate pairwise interactions in disease contexts. By integrating machine learning and explainable AI approaches, she develops predictive models to enhance GEM reconstruction, interpret metabolic fluxes, and improve the coverage and robustness of biological datasets.

Beyond metabolic modelling, Chaimaa’s work extends to protein modelling and structural bioinformatics, where she applies molecular docking and 3D structure reconstruction techniques to investigate the pathophysiological roles of proteins in cancer and infectious diseases. Her interdisciplinary expertise bridges software engineering, AI, and mathematical modelling, contributing to the development of innovative computational tools for biological and biomedical research.

Her work is being extended to broader disease and cancer research contexts, demonstrating the translational impact of computational modelling in healthcare.

External Roles and Professional Activities

• Co-Lead of WP2 – Extremophilic hosts and enabling technologies for efficient biodiscovery of novel genes and enzymes. "Integrative omics for ecology and adaptations within the Horizon Europe Project XTREAM.
• Member of "Clinical AI Interest Group", The Alan Turing Institute
• Collaborator with Complement Genomics Ltd, integrating AI and bioinformatics for applied healthcare research.
• Member of EDI and Women in AI initiatives within Teesside University, promoting inclusive participation in STEM research and education. She co-organises the Hello World event, an annual outreach initiative aimed at inspiring young girls from local schools to pursue careers in Computer Science, and contributes to community engagement and widening participation activities. She also co-organises "GirlsWhoML: Building Inclusive AI in the Biosciences Community", an event supported by the AIBIO-UK FlexiFund to promote diversity and inclusion in AI and biosciences research.
• Working with the AIBIO-UK (BBSRC) Network as part of  AIBIO-UK’s Interdisciplinary Sandpit Event
• Invited keynote Speaker, MoroccoAI Webinar Series, presenting on AI-driven metabolic modelling for microbiome research.
• Contributed to the preparation and delivery of funded CPD activities in Machine Learning, GenAI and Big Data and Business Intelligence.
• Active mentor and supervisor of undergraduate and postgraduate projects in AI, machine learning, and computational biology.