About

I am a technologist and software architect working in Microsoft Healthcare on problems in the space of genomics and personalized medicine. I have a broad background in molecular biology, machine learning, databases and AI and have been a part of Microsoft Research for nearly 20 years. Much of my work has focused on developing robust and scalable techniques for data discovery, data integration and data analysis.

We are in the midst of a revolution in biology and medicine. Whole genome sequencing has become affordable, we are rapidly uncovering the molecular mechanisms that drive disease and many breakthrough treatment options are on the horizon. It is no longer hard to imagine a future free from infectious diseases, cancer, diabetes, heart disease, Alzheimer’s and aging. We are so close, yet to get there, tremendous work is needed to understand, manage and operationalize the deluge of data that is being generated. Patient health records will soon encompass multiple terabytes of data per person across genomics, imaging and other health data. Patients want their data to be portable so that they can easily share it with different health providers. At the same time, the true promise of 21st century medicine will only be achieved by pooling and analyzing health data across large populations of patients. All of this requires vast amounts of storage, computation and AI in the cloud along with systems that ensure the highest levels of privacy, security and individual control over health data.

My work presently focuses on developing new techniques that enable large-scale pan-genomic analysis across individuals. I am also working to holistically apply machine learning and data integration techniques to multi-omics data generated from different analytical methods. A longer-term ambition is integration of all of this data into multi-scale models to aid research, diagnosis and treatment planning.

I additionally work on developing new methods in biological engineering and Biological Computation. I have developed techniques for DNA Storage, DNA computation and molecular recording within single cells.

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