Agenda

Hosted by
Mork Family Department of Chemical Engineering and Materials Science
University of Southern California
Los Angeles, CA 90089

February 26 - 27, 2018

Monday, February 26, 2018
Ronald Tutor Hall (RTH), Room 526
3710 McClintock Ave, Los Angeles, CA 90089

1:00	Introduction/Agenda Overview	J. Qin (USC)
1:10	PI Overviews	J. Qin (USC) J. Rawlings (UW) M. Baldea (UT) TWCCC Stats
2:10	Break
2:30	Open Automation Architecture	Don Bartusiak (ExxonMobil)
3:10	K-Nearest Neighbor and Kalman Filtering for Car Auction Pricing	Dr. Tao Yuan USC/Opera Solutions
3:40	A Comparison of Three Different ALS Problems for Kalman Filter Tuning and Controller Performance Monitoring	Travis Arnold (UW)
4:10	Poster Session
6:00	Adjourn
6:30	Dinner – University Club, Carnegie Room -705 W 34th St, Los Angeles, CA; Phone: (213) 740-2030

 

Poster Session

Student	Poster Title
Y. Dong, USC	Dynamic Latent Variable Analytics for Process Diagnosis
Y. Jin, USC	Machine Learning Approach to Batch Operation Diagnosis
H. Liu, USC	Modeling of Subway Indoor Air Quality Using Gaussian Process Regression
S. Liu, USC	DiCCA of DFT Data for Power System Events Detection and Localization
W. Ling, USC	Multivariate Causality Analysis on off-line Measurements of Batch Processes
A. Patel, USC	Big Data Challenge via The Tennessee Eastman Process
B. Yang, USC	Fault Dictionary Learning of Wind Turbine Bearings via Sparse Representation and Shift-Invariant K-SVD
J. Costandy, UT	A Scheduling Perspective on Quantifying the Value of (Advanced)Process Control
T. Arnold, UW	A Comparison of Three Different ALS Problems for Kalman Filter Tuning and Controller Performance Monitoring

 

Tuesday, February 27, 2018
Ronald Tutor Hall (RTH), Room 526
3710 McClintock Ave, Los Angeles, CA 90089

8:00 a.m.	Meeting with PI’s and Sponsors – Continental Breakfast
9:00	Tutorial Overview on Machine Learning and Data Analytics Techniques	Joe Qin, USC
9:40	A Scheduling Perspective on Quantifying the Value of (Advanced) Process Control	Joseph Costandy, UT
10:10	Break
10:30	Dynamic Latent Variable Analytics for Process Diagnosis	Dr. Yining Dong, USC/Stanford
11:00	Machine Learning Approach to Batch Operation Diagnosis	Yuan Jin, USC
11:20	Application of Dynamic Latent Modeling for Power Grid Stability and Event Detection	Sam Liu, USC
11:45	Adjourn