Dave Campbell
Professor, School Of Mathematics And Statistics And School Of Computer Science
Ottawa, Ontario, Canada
Summary
👤
Senior🎓
Top SchoolDave Campbell is a professor and computational statistics researcher with 11+ years of experience building interdisciplinary data science programs and leading applied research at the nexus of statistics, computer science, numerical analysis and optimization. He runs a research lab at Carleton University, teaches a wide spectrum of courses from data acquisition and SQL to Bayesian computation and stochastic processes, and has directed undergraduate data science programs and applied teams in academia and government. His methodological work focuses on statistical modeling and algorithms for differential equation systems, probabilistic numerics, image and text modeling, systems biology, causal inference and anomaly detection—often turning “black box” models into interpretable, evidence-based solutions mindful of data quality and business constraints. He has served as Associate Editor for SIAM Journal of Uncertainty Quantification and held leadership roles in the Statistical Society of Canada, blending scholarly rigor with community building. Colleagues value his ability to bridge theory and practice, supervising projects that deploy TensorFlow CNNs, text security models, and wearable-tech anomaly detection in real-world settings.
11 years of coding experience
15 years of employment as a software developer
BSc, Environmetrics, BSc, Environmetrics at Simon Fraser UniversityMSc, Statistics, MSc, Statistics at Dalhousie UniversityExchange, Marine Science, Exchange, Marine Science at University of the South PacificPhD, Statistics, PhD, Statistics at McGill University
Github Skills (13)
science6
python5
machine-learning5
open-data4
data-science4
sentiment3
datasets3
data-validation2
nlp2
sentiment-analysis2
open-source1
deep-learning1
natural-language-processing1
Programming languages (5)
Github contributions (5)
iamdavecampbell/hBayesDM
Apr 2017 - Jun 2021
An R package for hierarchical Bayesian modeling of RLDM tasks.
Contributions:7 PRs, 20 pushes, 4 branches in 4 years 2 months
r-packagemodelingbayesianhierarchical
iamdavecampbell/DHSI2019
Jun 2019 - Mar 2021
Contributions:11 commits, 10 pushes, 1 branch in 1 year 9 months
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