My research is centered around the application of deep learning and advanced signal-processing techniques to the field of biomedicine. Specifically, I focus on using these technologies to accomplish tasks such as the classification, segmentation, and denoising of essential medical data. This work includes the analysis of heart sounds, lung sounds, and EEG signals. By leveraging the power of artificial intelligence, my aim is to automate and improve the interpretation of these crucial medical datasets, leading to more accurate diagnoses and enhanced patient care.

Another significant area of my research involves computational protein research. This field involves utilizing computer simulations and modeling to gain a deeper understanding of the structures, functions, and interactions of proteins. The outcomes of this research have far-reaching applications, from aiding in the discovery of new pharmaceuticals to unraveling the mechanisms of various diseases and the development of innovative therapeutic solutions 

In collaboration with experts in the field of radiology, my research extends to the development of advanced algorithms for the analysis of CT scans, particularly in the context of lung cancer detection and nodule classification. These algorithms are designed to automatically classify and segment lung nodules, assisting medical professionals in the early detection and precise diagnosis of lung cancer.