This track focuses on the impact of data science on human beings and our environment. We look for applied science that will augment our interactions in the world and help us make informed decisions on issues that are relevant or urgent in order to make measurable improvements in our quality of life. The speakers in this track are selected for their abilities to address a relevant unmet need, and to provide an in-depth technical explanation of a novel data-driven solution in the areas of health & wellness, social interactions, learning, and economics.
Paula has a decade’s experience implementing novel technology and analytics to support decision-making in the life science industry. With an entrepreneurial spirit, she has worked in academia, pharma, biotech and health IT startups.
A PhD in Biophysics from Stanford University, her field of expertise has been the integration and mining of heterogeneous information at the intersection of chemistry, biology and medicine. She has developed machine learning models applied to drug discovery. Her latest work in neuroscience combines imaging and machine learning to predict early Alzheimer's disease before the appearance of symptoms. In the latest years, she has been focusing on the analysis of real-world evidence based on patient data to understand disease and make drug development more efficient. She serves as a data science advisor helping startups and pharma companies with their digital strategy and innovation programs.
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