Fall 2019 SDSI / AI for Health Annual Meeting

Stanford Data Science Initiative / AI for Health 2019 Annual Fall Meeting

Advances In Data Sciences and Applications

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		Robust Reinforcement Learning Emma Brunskill Assistant Professor of Computer Science View Video
9:30 am		Service Quality in the Gig Economy:Empirical Evidence about Driver Behavior at Uber Susan Athey The Economics of Technology Professor, Stanford Graduate School of Business View Video
9:50 am		Advancements in Graph Neural Networks Jure Leskovec Associate Professor of Computer ScienceCo-Director of Stanford Data Science Initiative View Video
10:10 am		Privacy from your Pocket John Duchi Assistant Professor of Statistics and Electrical Engineering View Video
10:30 am		Break
11:00 am		Weak Supervision in Medicine: Optimism anda Pitfall Christopher Re Associate Professor of Computer Science
11:20 am		Deep Reinforcement Learning Tengyu Ma Assistant Professor of Computer Science and Statistics View Video
11:40 am		Analyzing Video at Scale Maneesh Agrawala Forest Baskett Professor of Computer Science View Video
12:00 pm		SDSI Collaboration from Corporate and VisitingScholar Point of View Keita Yokoyama and Yusuke Fukazawa DOCOMO Visiting Scholar & Industry Member View Video
12:20 pm		Lunch
1:40 pm		Industry Panel
2:40 pm		Break
3:10 pm		Evaluating Seeding Strategies in Networks Johan Ugander Assistant Professor, Management Science & Engineering
3:30 pm		Computation and Organization Michael Bernstein Associate 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		Digital and Data Tools for Precision Health Euan Ashley Professor of MedicineCo-Director of Stanford Data Science Initiative View Video
10:20 am		How to Get the Most out of your Data with Modern ML James Zou Assistant Professor of Biomedical Data Science and Computer Science (Courtesy) and Electrical Engineering (Courtesy)Faculty Director of AI for Health Program View Video
10:40 am		Leveraging Real World Data with Federated Learning and Making Clinical Predictions using EMR Data Daniel Rubin Professor of Biomedical Data Science,Radiology, Medicine (BMIR), Computer Science (Courtesy) and Ophthalmology (Courtesy) View Video
11:00 am		Break
11:20 am		A Framework for Personalizing and Testing Medical Decisions Mohsen Bayati Associate Professor of Operations, Information and Technology View Video
11:40 am		Machine Learning for Small Molecule Lead Optimization Bowen Liu PhD Candidate, Chemistry View Video
12:00 pm		Ambient Intelligence in AI-Assisted Hospitals Serena Yeung Assistant Professor of Biomedical Data Science, Computer Science (Courtesy) and ofElectrical Engineering (Courtesy)
12:30 pm		Lunch Open Mic Talks 1:00-2:00
2:10 pm		Real World Data for Clinical Trial Optimization Ruishan Liu PhD Candidate, Electrical Engineering View Video
2:30 pm		Using Data to Educate the Learning HealthSystem Nigam Shah Associate Professor of Medicine (Biomedical Informatics)
3:00 pm		Pharmacovigilance Tools for LeveragingSocial Media Russ Altman Kenneth Fong Professor of Bioengineering, Genetics, Medicine, Biomedical Data Science and Computer Science (courtesy) View Video
3:30 pm		Thank You's!

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Fall 2019 SDSI / AI for Health Annual Meeting

Event Details:

Location

Stanford Data Science Initiative / AI for Health 2019 Annual Fall Meeting

Advances In Data Sciences and Applications

Agenda

Thursday, November 21

Robust Reinforcement Learning

Assistant Professor of Computer Science

Service Quality in the Gig Economy:Empirical Evidence about Driver Behavior at Uber

The Economics of Technology Professor, Stanford Graduate School of Business

Advancements in Graph Neural Networks

Associate Professor of Computer ScienceCo-Director of Stanford Data Science Initiative

Privacy from your Pocket

Assistant Professor of Statistics and Electrical Engineering

Weak Supervision in Medicine: Optimism anda Pitfall

Associate Professor of Computer Science

Deep Reinforcement Learning

Assistant Professor of Computer Science and Statistics

Analyzing Video at Scale

Forest Baskett Professor of Computer Science

SDSI Collaboration from Corporate and VisitingScholar Point of View

DOCOMO Visiting Scholar & Industry Member

Evaluating Seeding Strategies in Networks

Assistant Professor, Management Science & Engineering

Computation and Organization

Associate Professor of Computer Science

Friday, November 22

Digital and Data Tools for Precision Health

How to Get the Most out of your Data with Modern ML

Assistant Professor of Biomedical Data Science and Computer Science (Courtesy) and Electrical Engineering (Courtesy)Faculty Director of AI for Health Program

Leveraging Real World Data with Federated Learning and Making Clinical Predictions using EMR Data

Professor of Biomedical Data Science,Radiology, Medicine (BMIR), Computer Science (Courtesy) and Ophthalmology (Courtesy)

A Framework for Personalizing and Testing Medical Decisions

Associate Professor of Operations, Information and Technology

Machine Learning for Small Molecule Lead Optimization

PhD Candidate, Chemistry

Ambient Intelligence in AI-Assisted Hospitals

Assistant Professor of Biomedical Data Science, Computer Science (Courtesy) and ofElectrical Engineering (Courtesy)

Real World Data for Clinical Trial Optimization

PhD Candidate, Electrical Engineering

Using Data to Educate the Learning HealthSystem

Associate Professor of Medicine (Biomedical Informatics)

Pharmacovigilance Tools for LeveragingSocial Media

Kenneth Fong Professor of Bioengineering, Genetics, Medicine, Biomedical Data Science and Computer Science (courtesy)

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