Event Details:
Thursday, November 21, 2019 - Friday, November 22, 2019
Stanford Data Science Initiative / AI for Health 2019 Annual Fall Meeting
Advances In Data Sciences and Applications
Paul Brest Hall, Stanford University
November 21-22, 2019
We are entering a new era of innovation in Data Science where actions can be responsibly taken from predictions, training data sets generated and used more efficiently, and complex knowledge graphs mined in real time. These advancements are providing even more value in new applications areas and domains. SDSI and AI for Health are co-hosting their 2019 Annual Fall Meeting exploring new methods in data science and demonstrating these technologies in customer understanding, finance, healthcare and other domains. Stanford’s talented researchers work at the forefront of data intensive methodologies with a strong interdisciplinary nature, encouraging the development of new approaches in fields that benefit both academia and industry.
Agenda
Thursday, November 21
8:00 am | Breakfast and Registration | |
9:00 am | Welcome | |
9:10 am |
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9:30 am |
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Service Quality in the Gig Economy:
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9:50 am |
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Advancements in Graph Neural NetworksJure LeskovecAssociate Professor of Computer Science
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10:10 am |
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Privacy from your Pocket |
10:30 am | Break | |
11:00 am |
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Weak Supervision in Medicine: Optimism and
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11:20 am |
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Deep Reinforcement Learning |
11:40 am |
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Analyzing Video at Scale |
12:00 pm |
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SDSI Collaboration from Corporate and Visiting
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12:20 pm |
Lunch |
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1:40 pm | Industry Panel | |
2:40 pm | Break | |
3:10 pm |
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Evaluating Seeding Strategies in NetworksJohan UganderAssistant Professor, Management Science & Engineering |
3:30 pm |
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Computation and OrganizationMichael BernsteinAssociate Professor of Computer Science |
4:00 pm | Student Poster Lightening Talks | |
5:00 pm | Student Poster Session & Reception |
Friday, November 22
9:00 am | Breakfast and Registration | |
9:50 am | Welcome | |
10:00 am |
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Digital and Data Tools for Precision Health |
10:20 am |
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How to Get the Most out of your Data with Modern MLJames ZouAssistant Professor of Biomedical Data Science and Computer Science (Courtesy) and Electrical Engineering (Courtesy)
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10:40 am |
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Leveraging Real World Data with Federated Learning and Making Clinical Predictions using EMR DataDaniel RubinProfessor of Biomedical Data Science,Radiology, Medicine (BMIR), Computer Science (Courtesy) and Ophthalmology (Courtesy)
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11:00 am | Break | |
11:20 am |
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A Framework for Personalizing and Testing Medical Decisions |
11:40 am |
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Machine Learning for Small Molecule Lead Optimization |
12:00 pm |
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Ambient Intelligence in AI-Assisted HospitalsSerena YeungAssistant Professor of Biomedical Data Science, Computer Science (Courtesy) and of
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12:30 pm |
Lunch Open Mic Talks 1:00-2:00 |
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2:10 pm |
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Real World Data for Clinical Trial Optimization |
2:30 pm |
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Using Data to Educate the Learning Health
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3:00 pm |
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Pharmacovigilance Tools for Leveraging
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3:30 pm | Thank You's! |
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