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November 16th 2018

Eui-Hong (Sam) Han

Eui-Hong (Sam) Han is Senior Director - Advanced Data Science at Marriott. He is an experienced practitioner of AI, machine learning and data science. He has in-depth understanding of data science technologies and has experience of successfully applying these technologies to solve real business problems. His team at Marriott is responsible for building machine learning models for customer life cycle management, credit card marketing and loyalty program. Prior to joining Marriott, he led a data science team at The Washington Post that provided AI and machine learning tools and services to readers, newsroom and advertisement team. His other experiences include Big Data and data mining consulting work at Persistent Systems and machine learning work at Sears Holdings Online Business Unit. He holds PhD in Computer Science from the University of Minnesota - Twin Cities.

Ann Hermundstund

Ann received her bachelor's degree in Engineering Physics from the Colorado School of Mines, where she worked with Lincoln Carr on problems related to the quantum behavior of ultracold atoms. After a brief hiatus volunteering overseas, she moved to the University of California, Santa Barbara, to pursue her doctorate in physics. She joined the Complex Systems Group, headed by Jean Carlson, where she worked on a variety of topics in statistical physics related to granular materials, biophysics, and neuroscience. After her PhD, she moved to the University of Pennsylvania to work with Vijay Balasubramanian. During her postdoc, she split my time between Philadelphia and France, working between the Physics of Living Matter Group at UPenn and the Laboratoire de Physique Theorique at Ecole Normale Superieure. She is now a Group Leader at Janelia Research Campus, where she works in close collaboration with experimental groups to develop theoretical and computational approaches for studying information processing in the brain.

Cara Crawford

Cara Crawford is data scientist with nearly a decade of experience using statistics to improve decision-making. Drawing on her background in experimental psychology, statistics and economics, Ms. Crawford brings a creative approach to her work with attention to the human aspects of data-driven solutions. Recent projects include developing models of customer churn to drive sales resource allocation, using text analytics to improve product positioning, and developing protocols to test the acceptability of explainable machine learning techniques. Past quantitative research analyzed the impact of using of high-stakes educational testing to assess school quality. Experimental work evaluated how people use reinforcement learning to adapt to context changes, and measured the extent to which doctors make treatment decisions on the basis of electronic order system defaults. Ms. Crawford has a bachelor’s degree in economics from Duke University, and a master’s degree in research methods in psychology from the University of Bristol.

Christian L. Müller

Christian L. Müller is a Project Leader in Computational Statistics at the Center for Computational Mathematics, Flatiron Institute, a division of the Simons Foundation. He joined the Simons Foundation in 2014 as a research scientist at Simons Center for Data Analysis to develop high-dimensional statistics methods and algorithms for microbiome data. Before joining the Simons Foundation, he held postdoctoral positions at ETH Zürich and New York University. Müller holds an M.S. in computer science from Uppsala University, Sweden, an M.S. in bioinformatics and computer science and a university certificate in literature and poetry from the University of Tübingen, Germany, and a Ph.D. in computer science from ETH Zürich, Switzerland.

Stefan Natu

Dr. Stefan Natu obtained his PhD in theoretical physics at Cornell University. He continued in academia with a postdoctoral position at the Kavli Institute and the University of Maryland, College Park. He then entered industry as a senior researcher for Exxon Mobile where he leveraged machine learning to to predict oil/gas phase fractions from sensor data. Following this work, he earned a prestigious data science fellowship at Insight Data Science. He is now a data scientist at Publics.Sapient.

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