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Conference Presentations in Fairfax, Virginia, on October 7, 2015


Using Machine Learning to Determine effects of Sleep Duration and Physical Activity on Stroke Risk: Analysis of the National Health Interview Survey

Azizi Seixas
NYU Medical School


Learning Dynamic Bayesian Networks from fMRI Time Series under Conditions of Chronic Pain and Opioid Addiction

Larry Price
Texas State University


A Case Study Guide to Avoid Bayesian Network Modeling Pitfalls

Swapnil Rajiwade and Michael Abramovich
Booz Allen Hamilton


Big data, small data: Bayesian networks in environmental policy analysis in Canada’s energy sector

Steven Wilson
Standpoint Decision Support 


Marketing Mix Optimization – Using Bayesian Network Modeling

Neeraj Kulkarni
Cooler Heads Intelligence


Sky Mining - Photomorphic Redshift Estimation using Bayesian Networks

Pragyansmita Nayak
CGI Federal


Optimizing Specific Fuel Consumption in Army Command Post Electrical Power Grids

David Aebischer
U.S. Army


Innovations in Managing the Training Process in Elite Sports; Using Predictive Analytics to Build Optimal Roadmaps for Lasting Success

Roman Fomin

BayesiaLab Courses

May 21–23, 2019 Paris, France Advanced Course (3 Days, in French) 
June 5, 2019 Washington, D.C. BayesiaLab 101 Short Course (1 Day)
June 12–14, 2019 Seattle, WA Introductory Course (3 Days)
June 17–19, 2019 Seattle, WA Advanced Course (3 Days)
October 7–9, 2019 Durham, NC Introductory Course (3 Days)
October 14–16, 2019 Durham, NC Advanced Course (3 Days)

7th Annual BayesiaLab Conference

October 7–9, 2019 Durham, NC 3-Day Introductory Course
October 10–11, 2019 Durham, NC 7th Annual BayesiaLab Conference
October 14–16, 2019 Durham, NC 3-Day Advanced Course