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Bioengineer and Data Scientist with 12 years of research experience in commercial, academic, and clinical settings. Expertise includes microfluidics, machine learning, image processing and statistics utilizing Python. Dedicated to continuous learning and building principled data analytics workflows for reproducible science; a driven, self-motivated engineer who enjoys learning and applying new methods to resolving real problems involving human health. Particular interest in data analytics, biotechnology, and pharmaceuticals. Holds a BS in Bioengineering from Rice University, and a PhD degree in Bioengineering from the University of California, Los Angeles.

• Developed image analysis software to process results from in vitro diagnostic devices.
• Utilized machine learning on high dimensional, heterogeneous bioinformatics data to gain insights and identify populations of interest.