Algorithmic, Mathematical, and Statistical Foundations of Data Science and Applications
April 12-13, 2019
About
Data Science is a growing field that uses data and computing to improve everyday life. This field poses a unique set of multi-disciplinary challenges spanning:
- Computer science
- Statistics
- Applied mathematics
- Machine learning
and their use in the sciences (such as biology, chemistry, physics, engineering, sociology, economics, medicine, etc.). The data science workshop at Purdue will focus on the theoretical foundations of Data Science while highlighting the helpful feedback cycle between foundational work and applications.
Program
| Time | Event |
|---|---|
| 8:30am - 9:15am | Registration & Coffee |
| 9:15am - 9:30am | Introductory Remarks |
| 9:30am - 10:45am |
Session 1 On the Theory of Gradient-Based Learning: A View from Continuous Time - Abstract Controlling Confounding and Selection Biases in Causal Inference - Abstract Engineering Drug Discovery using Chemical Data Science - Abstract |
| 10:45am - 11:15am | Coffee Break |
| 11:15am - 12:30pm |
Session 2 Stochastic Gradient Descent, in Theory and Practice - Abstract Learning to Grow Economies - Abstract From ADMM to Consensus Equilibrium - Abstract |
| 12:30pm - 2:00pm | Lunch Break |
| 2:00pm - 3:15pm |
Session 3 Graph Mining at Scale: From Theory to Practice and Back - Abstract Statistical methods for prediction and anomaly detection in dynamic networks - Abstract Leveraging Big Data to Understand the Genetics of Health and Disease - Abstract |
| 3:15pm - 3:45pm | Coffee Break |
| 3:45pm - 5:00pm |
Session 4 Computation in the Brain - Abstract Information Content in Dynamic Networks - Abstract Brain Connectomics: From Maximizing Subjects Identifiability to Disentangling Heritable and Environment Traits - Abstract |
| Time | Event |
|---|---|
| 9:00am - 9:30am | Breakfast |
| 9:30am - 10:45am |
Session 5 Stochastic Optimization for Large-Scale Tensor Decomposition - Abstract Stein Goodness-of-fit Tests for Discrete and Point Process Data - Abstract Data Science Case Studies at Purdue and Sparse Bayesian Deep Learning - Abstract |
| 10:45am - 11:15am | Coffee Break |
| 11:15am - 12:15pm |
Session 6 Sparse Matrices in Sparse Analysis - Abstract Goodness of Fit Testing for Dynamic Network Models - Abstract |
| 12:15pm - 12:30pm |
Closing Remarks |
Speakers
Keynote Speakers
On the Theory of Gradient-Based Learning: A View from Continuous Time
University of California Berkeley
Department of Electrical Engineering and Computer Sciences, Department of Statistics
Google Research
Stochastic Gradient Descent, in Theory and Practice
University of Texas at Austin
Department of Mathematics
Purdue Highlight Speakers
Controlling Confounding and Selection Biases in Causal Inference
Department of Computer Science
From ADMM to Consensus Equilibrium
Department of Electrical and Computer Engineering, Statistics
Department of Chemistry
Brain Connectomics: From Maximizing Subjects Identifiability to Disentangling Heritable and Environment Traits
Department of Industrial Engineering
Data Science Case Studies at Purdue and Sparse Bayesian Deep Learning
Department of Mathematics
Department of Computer Science
Leveraging Big Data to Understand the Genetics of Health and Disease
Department of Biological Sciences
Stein Goodness-of-fit Tests for Discrete and Point Process Data
Department of Statistics
Registration
Click here to register. Registration is complimentary for (Purdue or non-Purdue) undergraduates; $10 for Purdue graduate students; $20 for Purdue faculty, Purdue postdocs, and non-Purdue graduate students; $40 for non-Purdue faculty or non-Purdue postdocs; and $60 for non-academic participants.
Logistics
The conference will be held in two different locations on Friday and Saturday.
Friday
We will be in the Shively Club, 3rd floor of Ross-Ade Pavilion at the Purdue Stadium. The address is 850 Steven Beering Dr, West Lafayette, IN 47906. For parking, please feel free to park in the North Stadium Lot, immediately north of the stadium. The signs say parking for ABC permits only, but we have negociated an arrangement for people attending our conference. Please feel free just to park there.
Saturday
We will be in the Lawson Computer Science Building 305 N. University St. West Lafayette, IN 47907, room 1142. Parking is available in the adjacent parking garage (parking garage entrance just south of Third Street on University Street).
Organizers
