Stanford Data Science Initiative Fall 2018 Retreat
Event Details:
Location
Paul Brest Hall
555 Salvatierra Walk
Stanford, 94305
United States
Emerging Topics in Data Science for Business and Society
The Stanford Data Science Initiative (SDSI) 2018 Fall Retreat explores emerging topics in data science for business and Society. As the state of the art and practice of data science continues to advance at a rapid pace, today’s agenda presents a wide array of innovative technologies such as advanced analytics, security, understanding and preventing bias, and their application to fields ranging from healthcare to how people communicate. Stanford’s talented researchers work at the forefront of data intensive methodologies with a strong interdisciplinary nature. Stanford’s strong presence in many domains encourages the development of new approaches in a number of fields that benefit both academia and industry.
Agenda
| 8:00 am | Breakfast and Registration |
| 9:00 am | Welcome and Introductions |
| 9:05 am | Vision for Data ScienceAssociate Professor of Computer ScienceSDSI Affiliates Program Co-Director |
| 9:15 am | Consumer Choice in Longitudinal Data: New Methods and ApplicationsThe Economics of Technology Professor, Stanford Graduate School of Business |
| 9:45 am | Uncovering Security Weaknesses through Internet-Wide ScanningAssistant Professor of Computer Science |
| 10:15 am | Understanding Deep LearningAssistant Professor of Computer Science |
| 10:45 am | Break |
| 11:15 am | Finding and Reducing Human Biases in AIAssistant Professor of Biomedical Data Science |
| 11:45 am | Using Past Technologies to Predict Future CommunicationRoberta Bowman Denning Professor of Humanities |
| 12:15 pm | Lunch |
| 1:15 pm | Welcome back |
| 1:20 pm | Data Science for Humans and PopulationsProfessor of Medicine |
| 1:30 pm | Hardware Architectures for Software 2.0Cadence Design Systems Professor Electrical Engineering and Computer Science |
| 2:00 pm | The Artful Design of TechnologyAssociate Professor of Music |
| 2:45 pm | Break |
| 3:00 pm | Almond: An Open User-Programmable Virtual AssistantProfessor of Computer Science |
| 3:30 pm | Mostly Exploration-Free Algorithms in Personalized Decision-MakingAssociate Professor of Operations, Information and Technology |
| 4:00 pm | The Good, the Bad, and the Challenging of Machine Learning for Networked SystemsAssistant Professor of Computer Science |
| 4:30 pm | Poster Preview Presentations |
| 4:50 pm | Closing Comments |
| 4:55 pm | Poster Viewing and reception |
| 6:30 pm | Adjourn |