2023 Stanford Data Science Conference

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The Distinguished Lecture will be recorded and shared via our YouTube Channel.

Stanford Data Science hosted its second annual conference in 2023! This full-day conference took place on Stanford's campus on May 10th and concluded with our second talk in the SDS Distinguished Lecture series from Prof. Michael Jordan (UC Berkeley).

The day featured work from early career researchers at Stanford, working in various aspects of data science, to increase our sense of community, exchange ideas, and foster interdisciplinary collaboration. SDS aims to bring together faculty, postdocs, students, and staff in this daylong event which is designed to bridge traditional disciplinary silos and connect people who are learning from data.

Agenda:    Unless otherwise noted, all sessions are in Huang 300.
       
Registration     8:30 - 9:00am
Opening: Emmanuel Candès   9:00 - 9:15am
Classical Inference and Causal Analysis Across Fields  Posters with Lightning Talks 9:15 - 10:35am
Machine Learning and Predictive Modeling: A Data Science Deep Dive  Posters with Lightning Talks 10:50 - 12:05pm
Lunch    Huang Amphitheater 12:05 - 1:00pm
Lunch Breakout: Focus Group on Developing a Data Science Community  Room 305 Huang 12:15 - 1:00pm
Panel: The Future of Data Intensive Science: Methods, Applications, and Discovery   1:00 - 2:30pm
  Todd Coleman, Bioengineering    
  Dora Demzky, Education Data Science    
  Gulio De Leo, Oceans & Earth System Science    
  Risa Wechsler, Physics    
  Moderated by Erin Craig and Jonas Metzger, Stanford Data Science Scholars    
Tools and Practices for Data Science Now  Posters with Lightning Talks 2:40 - 4:10pm
Poster Recognitions & Closing   4:10 - 5:00pm
Reception Dinner   Huang Amphitheater 5:00 - 6:00pm
Distinguished Lecture: Michael Jordan (UC Berkeley)   6:00- 7:30pm
An Alternative View on AI: Collaborative Learning, Incentives, and Social Welfare    

Distinguished Lecture: Professor Michael Jordan
Title: An Alternative View on AI: Collaborative Learning, Incentives, and Social Welfare
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Michael I. Jordan is the Pehong Chen Distinguished Professor in the Department of Electrical Engineering and Computer Science and the Department of Statistics at the University of California, Berkeley. He received his Masters in Mathematics from Arizona State University, and earned his PhD in Cognitive Science in 1985 from the University of California, San Diego. He was a professor at MIT from 1988 to 1998. His research interests bridge the computational, statistical, cognitive, biological and social sciences.

Congratulations to these poster presenters recognized for the excellence of their work:

King Center on Global Development Award Alyson Singleton
McCoy Family Center for Ethics in Society Award Melissa Franco
Center for Spatial and Textual Analysis (CESTA) Award Amit Haim
Center for Education Policy Research Award Mike Hardy
Human-Centered Artificial Intelligence (HAI) Award Xiao Ge
Freeman Spogli Institute for International Studies Award Janka Deli
Center for Open and REproducible Science Award Hancheng Cao
Stanford Causal Science Center Award Apoorva Lal
Center for Mind, Brain, Computation, and Technology Award Anna Xu
Women in Data Science (WIDS) Award Marissa Reitsma
Spotlight Award: Creative & Effective Visualization Alyson Singleton
Spotlight Award: Accessible to a General Audience Yuzu Ido
Spotlight Award: Policy-relevant Research Jonas Metzger
Spotlight Award: Original Dataset Rebecca Grekin
Spotlight Award: Simulated Dataset Marissa Reitsma
Spotlight Award: Creative use of Secondary Data Yingjie Li
Spotlight Award: Creative "Data-free” (Theoretical) Project Ambarish Chattopadhyay

Special thanks to our poster recognition sponsors!