2018 Research Slam

CSCDS Spring Research SLAM and Networking Lunch

This event brought together researchers from the social, cultural, and computational sciences for a half-day, multi-disciplinary collaborative event, with the goal of informing, inspiring, and connecting. Participants are eligible to apply to CSCDS for seed funds for new interdisciplinary research projects.

Photo Gallery

2018 Presentations

Slam Research Presenters & Topics

Presenter Topic

Michelle Dimitris

How Global is Global Health Research? A Work in Progress

Ben Geboe

100% Carbon Neutrality

Yaolong JU

Progress Report for “Automatic Harmonic Analysis for Symbolic Music Using Deep Learning”

Mi LIN

Don't forget the groundwater! Bayesian Network Analysis on Groundwater Management

Daniela Oliveira

Knowledge Classifications and Natural Language Processing

Joseph Rafla

Identifying Narrative Event in Screenplays: A Fabricator’s Computational Approach

Brian Rubineau

Text analysis of sender traits and relationship valence in email meta-data

Local Centres & Resources

Presenter

Local Resource, Centre, or Organization

Thomas Soehl

Centre on Population Dynamics (CPD)

Jean-Philippe Reid Montreal Institute for Learning Algorithms (MILA)
Nikolas Provatas McGill Centre for High Performance Computing (HPC)
Anita Parmar & Jacob Errington Building 21
John Galbraith Center for Interuniversity Research and Analysis of Organizations (CIRANO)
Audray Fontaine

Centre for Interdisciplinary Research on Montreal (CIRM/CRIEM)

PDF icon CIRM/CRIEM Presentation

Tim Elrick

Geographic Information Centre (GIC)

PDF icon GIC Information Package

Pablo Castro Google Brain MTL

Geneviève Brunet-Gauthier

Quebec Inter-University Centre for Social Statistics (QICSS/CIQSS)

PDF icon QICSS Information Package

Jeffry Archer

McGill Library

Database A-Z

Numerical Data Resources

Text Data Mining Resources

Research Commons (Visualization Studio, 2x4 panel wall)

Data Lab (GIS, statistical software, and text analysis software like NVivo)

Research Data services (information on Research Data Management Plans and sharing your data)

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