Christian Jauvin
Independent software developer/data analyst/researcher specializing in
scientific computing (M.Sc. CS + Machine Learning, 2003, UdeM).
Ongoing Contracts
My current business model is to partner up with lab researchers in
various fields to help them solve problems with computing techniques
(machine learning algorithms, among others), open source software and
tools, and sometimes even come up with original research ideas and
directions. Currently I’m working with:
Open Source Code
- PyLIDAR, a Python/VTK-based graphical tool
to reconstruct botanical trees from point cloud data (soon to be
open-sourced)
- Dracones, a web mapping
framework based on MapServer
- Various smaller projects and experiments (@GitHub)
Publications
- PyLIDAR article, soon to come
- An infrastructure for real-time population health assessment and monitoring,
Buckeridge D, Izadi M, Shaban-Nejad A, Mondor L, Jauvin C, Dube L, Jang Y, Tamblyn R,
IBM Journal of Research and Development, 2012.
- Simulation Analysis Platform (SnAP): a Tool for Evaluation of
Public Health Surveillance and Disease Control Strategies,
Buckeridge DL, Jauvin C, Okhmatovskaia A, Verma AD, AMIA Annual
Symposium, 2011.
- Residential address errors in public health surveillance data: A
description and analysis of the impact on geocoding,
Zinszer K, Jauvin C, Verma A, Bedard L, Allard R, Schwartzman K, de
Montigny L, Charland K, Buckeridge DL, Spatial and Spatio-temporal
Epidemiology. 1(2-3): 163-168, 2010.
- Quantifying the Potential Benefit of Early Detection for Preventing
Morbidity and Mortality: A Simulation Study of Cryptosporidium
Outbreak.
Okhmatovskaia A, Verma AD, Jauvin C, Barbeau B, Allard R, Buckeridge
DL, presented at the ISDS Conference, 2010.
- A Neural Probabilistic Language Model,
Yoshua Bengio, Réjean Ducharme, Pascal Vincent and Christian Jauvin,
Journal of Machine Learning Research, 3:1137-1155, 2003.