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About Peter Gedeck
Dr. Peter Gedeck holds a Ph.D. in chemistry. He worked for twenty years as a computational chemist in drug discovery at Novartis in the United Kingdom, Switzerland, and Singapore. His research interests include the application of statistical and machine learning methods to problems in drug discovery. He is a scientist in the research informatics team at Collaborative Drug Discovery, which offers the pharmaceutical industry cloud-based software to manage the huge amount of data involved in the drug discovery process.
Peter’s specialty is the development of machine learning algorithms to predict biological and physicochemical properties of drug candidates. His scientific work is published in more than 50 peer reviewed articles.
Peter also teaches at University of Virginia's School of Data Science and gives a series of courses on Predictive Analytics at Statistics.com.