Research

Research internship project where I conducted literature-review and compare state-of-the-art analysis used in EEG signal processing. Implemented DL pipeline to decode grasping action from EEG

Automatic derived parameter for valve motion assessment and interactive visualization dashboard for cluster analysis and anomaly detec.

M.Sc. Thesis carried out in collaboration with Siemens Healthineers. Research state-of-the-art literature on cardiac MRI slice tracking and medical landmark detection. Develop a robust novel valve tracking 3D-CNN algorithm based on heatmap regression

The project aims to combine multi-sequence CMR data to classify the myocardial pathology. It willl be segmented into into normal, infarcted and edema regions, which is essential in the diagnosis and treatment management for patients suffering from myocardial infarction (MI)

New adaptive sampling strategy based on a motion context measure for ego +centric video was developed. The new method enables to save energy keeping a promising performance rate.

B.Sc. Thesis where I implemented a GUI to help ECG annotations and developed a machine learning algorithm to retrospectively classify arrhythmia based on 5 more discriminative ECG features