September 30, 2023


Thematic Program on Statistical Inference, Learning, and Models for Big Data, January to June, 2015

Friday June 12 & Saturday June 13, 2015
Closing Conference: Statistical and Computational Analytics for Big Data

Held at Dalhousie University

Organizing Committee

Hugh Chipman (Chair) : hugh.chipman (at)
Stan Matwin
Nancy Reid

On-line Registration
Registration fees:$75 (regular rate), $30 (students and PDF)
Online registration open to end of June 4. Onsite registration available during workshop: $100 (regular rate) $50 (students and PDF)

Presented jointly with the Institute for Big Data Analytics (IBDA) at Dalhousie University and sponsored by the Canadian Statistical Sciences Institute and the Atlantic Association for Research in the Mathematical Sciences, this workshop will give an overview of highlights of the thematic program on Statistical Inference, Models and Learning for Big Data, will showcase current IBDA student projects and will present research at IBDA on text mining, high-performance computing, visualization, bioinformatics, and privacy.

Funding support: Students and Postdoctoral Fellows may apply for travel funding. When registering, select "Funding Application Form" and complete that form. Deadline: Extended to May 19


Conference Location:

Computer Science Auditorium
Goldberg Computer Science Building
6050 University Avenue, Dalhousie University


Schedule Overview:

Friday June 12
9:00 - 9:10 Opening Remarks
9:10 - 9:50 Hugh Chipman, Acadia University, Statistical and computational challenges in networks and cybersecurity
9:50 - 10:30 Jean-Francois Plante, HEC Montréal, Challenges, Tools and Examples for Big Data Inference
10:30 - 11:00 Coffee
11:00 - 11:40 Lisa Lix, University of Manitoba, How Big Data and Causal Inference Work Together in Health Policy
11:40 - 12:20 Stephanie Shipp, Virginia Tech, Policy meets Social and Decision Informatics
12:20 - 1:30 Lunch
1:30 - 2:10 Stan Matwin, Dalhousie University, Big Data meets Big Water: Mining Ocean Vessel Trajectory Data

2:10 - 2:50

Evangelos Milios, Dalhousie University, Exploiting Semantic Analysis of Documents for the Domain User
2:50 - 3:30 Andrew Rau-Chaplin, Dalhousie University, Scaling up to Big Data: Algorithmic Engineering + HPC
3:30 - 4:00 Coffee
4:00 - 4:40 Rosane Minghim, Dalhousie University/University of São Paulo, Multidimensional Projections and Tree-based Techniques for Visualization and Mining

4:40 - 5:20

Rob Beiko, Dalhousie University, Microbial genomics for rapid investigation of infectious disease

5:30 - 7:00

Saturday June 13
9:00 - 10:20 Panel discussions on training for data science at the undergraduate and graduate levels.
10:20 - 10:40 Coffee
10:40 - 11:20 Roger Grosse, University of Toronto, Highlights from the deep learning workshop
11:20 - 12:00 Einat Gil, University of Toronto, Learning about Big Data among Secondary School Students in a technology-supported collaborative learning environment



This workshop is immediately before the annual meeting of the Statistical Society of Canada. Consult their accommodations page for links to accommodations in the area.


Confirmed Speakers:

Hugh Chipman, Acadia
Jean-François Plante,HEC
Lisa Lix, U Manitoba
Stephanie Shipp, Virginia Tech
Stan Matwin, IBDA
Evangelos Milios, Dalhousie
Andrew Rau-Chaplin, Dalhousie
Rosane Mingham, Dalhousie University / University of São Paulo
Rob Beiko, Dalhousie
Roger Grosse, U Toronto
Einat Gil, U Toronto



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