January 12 – 23, 2015 Opening Conference and Boot Camp
Organizing Committee	Location
Nancy Reid (Toronto), Sallie Keller (Virginia Tech), Lisa Lix (Manitoba), Bin Yu ( UC, Berkeley)	Room 230, Fields Institute

On-site registration for Opening Conference and Boot Camp, waiting list only		Application for Participant support deadline to apply March 1, 2015	Reimbursement information for funded participants
Back to main index	List of Participants (Opening Conference and Boot Camp)	Accommodation in Toronto	Information for speakers

Program

The goals are to to prepare students, postdoctoral fellows, visitors and interested researchers to benefit from the activities to follow, and to build momentum and generate widespread interest in the thematic program. We are very pleased that Robert Bell, ATT Bell Labs, will open the Conference and that Emmanuel Candes will open Day 2 with a Public Lecture. After two overview days, each day is devoted to one of the themes addressed in more depth during the thematic semester.

WEEK ONE: JANUARY 12 - 16

Monday January 12: Introductory Lectures and Overview
8:00	Coffee and Registration
8:45	Welcome
9:00-9:30	Nancy Reid, University of Toronto
9:30-10:30	Keynote Lecture: Bob Bell, AT&T Labs - Research Big Data: It's Not the Data
10:30-11:00	Coffee
11:00-12:00	Adam Kalai, Microsoft Machine learning and crowdsourcing
12:00-2:00	Lunch
2:00-3:00	Hugh Chipman, Acadia University An overview of Statistical Learning
3:00-3:30	Tea
3:30-4:30	Yulia Gel, University of Waterloo The Role of Modern Social Media Data in Surveillance and Prediction of Infectious Diseases: from Time Series to Networks
4:30	Cash Bar Reception
Tuesday January 13: Introductory Lectures and Overview
9:30-10:30	Keynote Lecture: Emmanuel Candes, Stanford University Big Data and the Reproducibility of Scientific Research: What Can Statistics Offer (video)
10:30-11:00	Coffee break
11:00-12:00	Steve Scott, Google Inc Bayes and Big Data: The Consensus Monte Carlo Algorithm
12:00-1:30	Lunch break
1:30-2:30	Naomi Altman, The Pennsylvania State University Generalizing Principal Components Analysis
2:30-3:00	Tea break
3:00-4:00	Emmanuel Candes, Stanford University Randomized Matrix Computations in the Big Data World
Wednesday January 14: Inference
9:30-10:30	Mark Girolami, University of Warwick Differential Geometric Simulation Methods for Uncertainty Quantification in Large Scale PDE Systems
10:30-11:00	Coffee break
11:00-12:00	Han Liu, Princeton University (presented by Ethan X. Fang, Princeton University) Testing and Confidence Intervals for High Dimensional Proportional Hazards Model
12:00-2:00	Lunch break
2:00-3:00	Ejaz Ahmed, Brock University Big Data Analysis: The Universe is not Sparse
3:00-3:30	Tea break
3:30-4:30	Richard Lockhart, Simon Fraser University Inference after LASSO -- limits and limitations
Thursday January 15: Environmental Science
9:30-10:30	Charmaine Dean, Western University Wildfire and Forest Disease Prediction to Inform Forest Management: Statistical Science Challenges
10:30-11:00	Coffee break
11:00-12:00	Doug Woolford, Wilfrid Laurier University Exploratory data analysis, visualization and modelling methods for large data in forest fire science
12:00-2:00	Lunch
2:00-3:00	Bo Li, University of Illinois Reconstructing Past Temperatures using Short- and Long-memory Models
3:00-3:30	Tea break
3:30-4:30	Alex Schmidt, Universidade Federal do Rio de Janeiro An overview of covariance structures for spatial and spatio-temporal processes
Friday January 16: Optimization
9:30-10:30	Martin Wainwright, University of California, Berkeley Statistics meets optimization: Rigorous guarantees for solving nonconvex programs
10:30-11:00	Coffee break
11:00-12:00	Anima Anundkumar, University of California, Irvine Guaranteed Non-Convex Optimization for Big Data
12:00-2:00	Lunch
2:00-3:00	Stephen Vavasis, University of Waterloo Clique and Biclique: An example of using convex optimization for data mining
3:00-3:30	Tea break

WEEK TWO: JANUARY 19 - 23

Monday January 19: Visualization
9:30-10:30	Sheelagh Carpendale, University of Calgary Information Visualization: Making Data Accessible
10:30-11:00	Coffee
11:00-12:00	Dianne Cook, Iowa State University Data Visualization and Statistical Graphics in Big Data Analysis
12:00-2:00	Lunch
Tuesday January 20: Social Policy
9:00	James Stafford, University of Toronto Patrick Brown, Cancer Care Ontario
10:30-11:00	Coffee break
11:00-12:00	Chad Gaffield, University of Ottawa Big Data vs. Human Complexity: An early status report on the central question of the 21st century
12:00-2:00	Lunch break
2:00-3:00	Sallie Keller, Virginia Tech Building Resilient Cities: Harnessing the Power of Urban Analytics
3:00-3:30	Tea break
3:30-4:30	Shane Reese, Brigham Young University From Basis Expansions to Insurgency Prediction: Applications of Bayesian Compressive Sensing
Wednesday January 21: Health Policy
9:30-10:30	David Buckeridge, McGill University Using (Big) Data to Address Challenges in Public Health
10:30-11:00	Coffee break
11:00-12:00	David Henry, Health Systems Data IHPME and Dalla Lana School of Public Health, University of Toronto
12:00-2:00	Lunch break
2:00-3:00	Lisa Lix, University of Manitoba Chronic Disease Research and Surveillance: The Power of Big Databases, the Challenges of Data Quality
3:00-3:30	Tea break
3:30-4:30	Thérèse Stukel, Institute for Clinical Evaluative Sciences Innovative uses of big data for health policy research
Thursday January 22: Deep Learning
10:30-11:00	Coffee break
11:00-12:00	Dale Schuurmans, University of Alberta Convex Methods for Latent Representation Learning
12:00-2:00	Lunch
2:00-3:00	Russ Salakhutdinov, University of Toronto Learning Structured, Robust, and Multimodal Models
3:00-3:30	Tea break
3:30-4:30	Sham Kakade, Microsoft Research Non-convex approaches to learning representations
Friday January 23: Networks and Machine Learning
9:30-10:30	Sofia Olhede, University College London Understanding Large Networks
10:30-11:00	Coffee break
11:00-12:00	Patrick Wolfe, University College London Estimating Latent Variable Densities for Exchangeable Network Models
12:00-2:00	Lunch
2:00-3:00	Eric Kolaczyk, Boston University A Whirlwind Tour of Statistical Analysis of Network Data
3:00-3:30	Tea break

Back to top