Atif Khan, PhD

I am a computational scientist possessing a combination of analytical,  machine learning, and  data mining  skills. My research spans the opportunities at the intersection of health data science, computation, and biology. In particular, I am interested doing research in data-intensive biology, where I can build tools and approaches that can directly address a variety of biological problems. I have a broad range of computational modeling experience in diverse domains ranging from engineering, automation, medical diagnostics, agriculture, immunology, bioinformatics, and regulatory genomics. Over the period of the last ten years, the primary focus of my research has been computational biology and health informatics.

My primary interest lies in understanding the rich contextual information associated with most data sets in a variety of real-world domains and using it to infer complex patterns. To this end, I have worked on designing efficient inference and learning pipelines for the models capable of handling uncertainties and interdependencies, a characteristic that is predominantly associated with large-scale data sets. I have computational modeling experience in diverse domains ranging from real-world engineering problems to medical diagnostics, immunology, epidemiology, bioinformatics, and regulatory genomics.