Apoorva Sikka completed her and degrees in Computer Engineering from RTU Ajmer and MNIT Jaipur (India). She is currently pursuing PhD at Indian Institute of Technology Ropar, India. Her work is based on exploring recent machine learning technologies like deep learning to different medical imaging domains to perform tasks such as classification, delineation, synthesis. In past, she has devised a method using fully connected neural networks to perform brain segmentation of MR scans. She is working as a visiting scholar in canlab where she focuses on analysis of deep learning approaches applied to neuroimaging data(fMRI).
This PhD program is designed to harness traditional medicine knowledge from the practitioners in communities for possible scientific interpretation, documentation, validation, standardization, and development into the curriculum for training in traditional medicine at undergraduate and master level. The research will focus on practitioners’ understanding of health and disease, their diagnosis of disease, treatment, and prevention of disease as well as materials used and their preparation methods and precautions.
Admission Requirements: Applicants must have Master of Science or M. Med (or equivalent) degree in a field related to Medicine, Dentistry, Nursing, Clinical Pharmacy, Public Health, and Epidemiology.