Skip to main content
Computer, Electrical and Mathematical Sciences and Engineering
CEMSE
Computer, Electrical and Mathematical Sciences and Engineering
Home
Study
Prospective Students
Current Students
Internship Opportunities
Research
Research Overview
Research Areas
Research Groups
Programs
Applied Mathematics and Computational Science
Computer Science
Electrical and Computer Engineering
Statistics
People
All People
Faculty
Affiliate Faculty
Instructional Faculty
Research Scientists
Research Staff
Postdoctoral Fellows
Students
Alumni
Administrative Staff
News
Events
About
Who We Are
Leadership Team
Apply
anomaly detection
Data-driven Anomaly Detection in Industrial Processes
Fouzi Harrou, Senior Research Scientist, Statistics
Feb 12, 12:00
-
13:00
B9 L2 R2325
anomaly detection
multivariate statistics
artificial intelligence
AI
This talk presents a model-based anomaly detection framework, along with data-driven process monitoring approaches based on multivariate statistical methods and artificial intelligence techniques.