I am responsible for driving an innovative and strategic research agenda that introduces differentiating novel and innovating technologies in IBM software offering in healthcare and life sciences.
I apply my experience to a wide set of problems ranging from disease progression modeling to novel approaches for chronic diseases. In the disease progression modeling space, I investigate the application of state of the art machine learning techniques such as temporal sequence mining techniques like newly emerging multitask learning techniques, in novel ways to help the customers and IBM Watson Health better understand how complex chronic disease progress in an objective, data driven way. I am developing such progressions to bring unprecedented new possibilities for the understanding of complex chronic disease that are impacting heavily the overall healthcare development of drugs that may reduce or even halt the progression of these disease. I am also involved in the development of new machine learning schemes that learn not just from data but also in the presence of external knowledge.
On a daily basis in this position, I work in the data curation and statistical data modeling: develop machine learning predictive models; develop new data driven methods able to learn from both data and in the presence of medical knowledge (e.g., medical guidelines); develop generic machine learning techniques for disease progression modeling using novel approaches (e.g., multi-task learning); involve in literature review; organize workshop and conferences; attend technical conferences and write patents and disclosures.