School of Engineering of Warwick, Coventry, CV4 7AL
E: M dot Porumb at warwick dot ac dot uk
-Machine learning for Pattern Recognition and Biomedical signal processing
-Time series analysis
-Deep learning methodologies
Biography and Research Project
I graduated from Technical University of Cluj-Napoca, and received my B.Sc. in Computer Science in 2012. I received my M.Sc. in 2015 from the same department, thesis title ‘Automatic Relation Extraction from Medical Documents’. After graduation, I worked as a software engineer in financial and automotive domains. Currently, I am a PhD research student under the supervision of Dr. Leandro Pecchia. My research interests include the development of Machine Learning techniques for the analysis of biomedical data. In particular, the main objective of my project is to study how non-invasive biomedical signals (obtained through wearable devices), together with behavioral monitoring can be used to predict other metabolic signals like blood glucose levels. The aim is to help diabetic people to handle their disease by using alternative, non-invasive methods.
- Barbantan, I., Barbantan, I., Porumb, M., Porumb, M., Lemnaru, C., Lemnaru, C., & Potolea, R. (2016). Feature Engineered Relation Extraction–Medical Documents Setting. International Journal of Web Information Systems, 12(3), 336-358.
- Porumb, M., Barbantan, I., Lemnaru, C., & Potolea, R. (2015, December). REMed: automatic relation extraction from medical documents. In Proceedings of the 17th International Conference on Information Integration and Web-based Applications & Services (p. 19). ACM.