University of Waterloo

An emerging challenge for inference and prediction of large-scale complex systems is to efficiently analyze and assimilate the ever-increasing high dimensional data produced by the vast number of engineered and natural systems.
The goals of our laboratory are to develop novel mathematical and statistical methods for
1. discovering fundamental structures and extracting useful information contained in high dimensional data; and
2. assimilating this information into the dynamical models in order to understand (and control) large-scale data-centric problems.
These new model-based and data-driven tools have a specific application to detect, control and mitigate dynamic instabilities in modern jet engines.
Lab Team
Sue Ann Campbell
University of Waterloo
Leo Dostal
Technische Universität Hamburg, Germany
Peter Imkeller
Humboldt University at Berlin
Jun Liu
University of Waterloo
Sagar Naik
University of Waterloo
Nicolas Perkowski
Humboldt University at Berlin
Sander Rhebergen
University of Waterloo
Henry J. van Roessel
University of Alberta
Alexander Schied
University of Waterloo
Siv Sivaloganathan
University of Waterloo
Giang Tran
University of Waterloo
Postdocs and Graduate Trainees
Ryne Beeson
PhD Candidate, University of Illinois
Kyle Ray Cochran
Master’s Candidate, University of Illinois
Gwenael Gatto
PhD Candidate, University of Waterloo
Michael Jagan
Master’s Candidate, University of Waterloo
Fei (Justina) Liu
Master’s Candidate, University of Waterloo
Ricardo Manzono
Master’s Candidate, University of Waterloo
Yiming Meng
PhD Candidate, University of Waterloo
Jonathan Murley
PhD Candidate, University of Waterloo
Dr. Alyssa Novelia
Postdoctoral Fellow, University of Waterloo
Momoiyioluwa Oluyemi
Master’s Candidate, University of Waterloo