The human genome project has brought multidisciplinary scientists to cancer research with their great minds and their methods to discern the complex genomic data. Cancer imaging is one the key element that allows non-invasive monitoring the disease physiology and make assessment on its progression. In our lab we focus on extracting information from imaging and other allied data sets that are routinely collected on the cancer patients that then can be used to derive prognosis for disease condition and provide progression risk. We use advanced machine learning based methods to extract information, integrate multi-model data sets that can help build a decision support systems. Our lab currently focuses on understanding disease condition, improving disease detection and risk assessment in prostate cancer, lung cancer and lymphoma.
We are a team of multidisciplinary researchers with a focus to Oncology, who strives to improve current standard of care-based detection and treatment procedures with the use of engineering methods and models. Our teams have Machine Learning as its broad focus with interest in Medical Imaging related to Radiological and Pathological Sciences. The lab is directed by Yoga Balagurunathan, Ph.D.
We are looking for talented individuals who can make a difference in our lab and support our mission ‘To Contribute to the Prevention and Cure of Cancer’. We are a dynamic research group focused on using the machine learning methods in big data sets like imaging and other omics data. We are in the department of Machine learning with in quantitative sciences division. Please reach out for enquires on open positions with your current CV and brief research statement to the lab director, Dr. Yoga Balagurunathan (email@example.com).
“If we knew what it was we were doing, it would not be called research, would it?” - Albert Einstein