DC 3 – Integrating data-driven (AI) and physics-based modelling approaches for improved understanding of functional brain age
Can you share a bit about your academic and professional journey?
I started my academic journey with a B.Sc. and M.Sc. in Electrical and Computer Engineering at Democritus University of Thrace in Greece. During my studies, I became interested in using computational methods in healthcare due to the field’s unique challenges and potential to improve people’s lives. For my diploma thesis, I developed deep learning architectures to explore the possibility of diagnosing COVID-19 from cough sound samples.
Motivated by the prospects of AI in healthcare, I continued my studies with an Advanced M.Sc. in Artificial Intelligence at KU Leuven. There, I collaborated with the UZ Leuven Hospital to integrate machine learning into their urinalysis workflow. I proposed and developed a deep learning model to classify microscope images, investigating the robustness and interpretability of the model and adapting the solution to meet the practical needs of lab technicians in the form of a software tool. Currently, I am excited to have joined the InSilicoHealth network as a Doctoral Candidate (DC-3).
What motivated you to pursue a Doctoral candidacy within the Doctoral Network?
Early in my academic journey, I realised I wanted to become a researcher in the field of biomedical engineering and digital health. This field combines my passion for science and engineering with my belief that those disciplines can greatly help human lives. Not only by providing a systematic framework to understand human functions and diseases, but also by aiding in the enhancement of patient care, the improvement of medical treatments, and the democratisation of healthcare.
Now, to be more specific regarding my position, I am fascinated by the human brain and its complexities, and I was very excited to apply for a position that is focused on brain health in human ageing, both in the context of understanding the functional changes that occur in the brain, but also in trying to uncover personalised biomarkers for early detection of diseases.
Moreover, as I strongly believe in the collaborative and interdisciplinary nature of research, I found the structure of this position and of the network, which is designed to foster collaboration among experts from different fields, to be an excellent fit for my aspirations.
What aspects of this training and research program are you most excited about?
As I previously mentioned, I really believe in research’s collaborative and interdisciplinary nature. With that in mind, I am really excited about meeting and exchanging ideas and perspectives with the rest of the doctoral candidates. In the same light, I look forward to training events and collaboration with industry partners and healthcare professionals.
