Emma Prevot
CDT student
Emma moved to London from Italy in 2019 where she completed an undergraduate degree at University College London (UCL) in Physics with Medical Physics
During her time at UCL, Emma developed a strong fascination for the human body as a complex and physical system, especially the enigmatic workings of the brain. She then started getting curious about the potential of AI in unravelling the intricacies of such systems. Driven by a heartfelt interest in Alzheimer's disease, Emma studied the heterogeneity of this disease with unsupervised clustering techniques as part of her final year research project and dissertation with the UCL POND group.
Following her undergraduate journey, she graduated with an MPhil in Machine Learning and Machine Intelligence from the University of Cambridge with the goal of gaining precious knowledge of the state-of-the-art in Machine Learning and enriching my expertise in academic research.
For her master's thesis, Emma focused on AI-enabled precision medicine, specifically exploring disease stratification and biomarker discovery using model-based clustering with variable selection on high-dimensional breast cancer transcriptomic data.
Now, as a Health Data Science CDT student, she is thrilled about the opportunity to contribute to the advancement of healthcare through data-driven research, with an emphasis on ethics and research responsibility. She is particularly interested in disease progression modelling, especially neurodegenerative of infectious diseases.