David Fenstermacher, PhD

David Fenstermacher, PhD

My experience throughout my career has been dedicated to biological research both from wet and dry labs, with over 14 years of experience as a molecular biologist/geneticist and over 22 years of experience in bioinformatics, in academia and industry.  Having been involved in several personalized/precision medicine initiatives in academia and data harmonization projects at a major pharmaceutical company, I am keenly aware of the importance of how data needs to be transformed to information and knowledge within a framework that promotes FAIR data principles.  This is paramount to being able to take advantage of novel AI and machine learning tools that are able to find patterns not accessible by other methods of analysis.  But the ability to find patterns requires data that is characterized by standardized metadata supported by ontologies and structured vocabularies.  In my current role we are exploring how machine learning and graph databases could also be part of the process for harmonizing data in a semantically aware environment such that downstream applications, such as ML or Bayes, can be used to generate more meaningful results while reducing the noise in ever growing datasets.  I received my degrees from the Bloomsburg University of Pennsylvania (BS) and the University of North Carolina – Chapel Hill (PhD).