March, 2026
Event Details
From High-Dimensional Data to Biological Insights: Machine Learning Approaches for Infectious Diseases
When: Tuesday, March 3, 2026 | 11:30
Where: DC-710, Aghia Paraskevi Campus
Organized by: Department of Computing and Mathematics, Deree – The American College of Greece
In collaboration with: Department of Natural Sciences, Deree – The American College of Greece
About the lecture
Dr. Leonardos Mageiros, Chair of the Department of Computing and Mathematics at Deree – The American College of Greece, cordially invites you to attend a guest lecture by Dr. Myrsini Kaforou, Associate Professor in Bioinformatics in the Department of Infectious Disease at Imperial College London. The talk will explore the application of machine learning to resolve diagnostic uncertainty in infectious and inflammatory diseases.
Decoding the host immune response in blood to resolve diagnostic uncertainty in infectious and inflammatory diseases, this presentation will outline advanced machine learning frameworks used to identify robust omic-based diagnostic signatures. It will detail computational strategies for integrating heterogeneous, high-dimensional transcriptomic datasets from large international consortia, while addressing key technical and clinical real-world challenges. The talk will also highlight the successful translation of complex genomic insights into rapid, point-of-care clinical tests, bridging bioinformatics innovation with bedside decision-making to help reduce antibiotic misuse.
This lecture will be of particular interest to faculty and students in bioinformatics, biology, biomedical sciences, computer science, and related disciplines.
About the speaker
Dr Myrsini Kaforou
Associate Professor in Bioinformatics in the Department of Infectious Disease at Imperial College London
Dr Kaforou’s research focuses on identifying host biomarkers for infectious diseases by applying machine learning techniques and statistical modelling to genomic, transcriptomic, and proteomic datasets. She is particularly interested in integrating multiple “-omics” datasets to improve diagnosis and to better understand host responses to infection.
She has received a Sir Henry Wellcome Postdoctoral Fellowship, the Emerging Leaders Prize in Antimicrobial Resistance from the Medical Research Foundation, and an Early Career Fellowship through the Wellcome Trust Institute Strategic Support Fund. She currently leads the bioinformatics, data management, and modelling work packages within international research consortia aiming to improve the diagnosis and management of febrile patients through machine learning approaches applied to large-scale patient cohorts.
Dr Kaforou holds a PhD and an MSc in Bioinformatics and Theoretical Systems Biology from Imperial College London, and completed her undergraduate studies at the School of Electrical and Computer Engineering at the National Technical University of Athens (NTUA).