Feed conversion targeting in an FCC pilot plant using a non-linear MPC strategy. - George M. Bollas; Ismini Anastasiou; Simira Papadopoulou; Spyros Voutetakis; Panos Seferlis (ACC, 2007)

Supervisory Control for Resilient Chiller Plants Under Condenser Fouling. - Khushboo Mittal; James P. Wilson; Brian P. Baillie; Shalabh Gupta; George M. Bollas; Peter B. Luh (IEEE Access, 2017)

Design of Built-In Tests for Robust Active Fault Detection and Isolation of Discrete Faults in Uncertain Systems. - William T. Hale; Kyle A. Palmer; Matthew D. Stuber; George M. Bollas (ACC, 2018)

Active Fault Diagnosis with Sensor Selection in a Diesel Engine Air Handling System. - Kyle A. Palmer; William T. Hale; George M. Bollas (ACC, 2018)

Learning Stable Nonlinear Dynamical Systems with External Inputs using Gaussian Mixture Models. - Harish Chaandar Ravichandar; Iman Salehi; Brian P. Baillie; George M. Bollas; Ashwin P. Dani (ACC, 2018)

Design of Built-In Tests for Active Fault Detection and Isolation of Discrete Faults. - William T. Hale; George M. Bollas (IEEE Access, 2018)

Semi-infinite programming for global guarantees of robust fault detection and isolation in safety-critical systems. - William T. Hale; Matthew Wilhelm; Kyle A. Palmer; Matthew D. Stuber; George M. Bollas (Comput. Chem. Eng., 2019)

Analysis of transient data in test designs for active fault detection and identification. - Kyle A. Palmer; George M. Bollas (Comput. Chem. Eng., 2019)

Active Fault Identification by Optimization of Test Designs. - Kyle A. Palmer; William T. Hale; George M. Bollas (IEEE Trans. Control. Syst. Technol., 2019)

Least-Squares- and Information-Theory-Based Inferential Sensor Design for Fault Diagnostics. - William T. Hale; George M. Bollas (ACC, 2020)

Sensor Fusion and Inferential Sensing for Fault Detection and Isolation in Uncertain Systems*. - Efi Safikou; George M. Bollas (SysTol, 2021)

Sensor Selection Embedded in Active Fault Diagnosis Algorithms. - Kyle A. Palmer; George M. Bollas (IEEE Trans. Control. Syst. Technol., 2021)

Inference of faults through symbolic regression of system data. - William T. Hale; Efi Safikou; George M. Bollas (Comput. Chem. Eng., 2022)

Symbolic Regression for Fault Prognosis and Remaining Useful Life Estimation. - Efi Safikou; George M. Bollas (ACC, 2023)

Dynamic System Identification from Scarce and Noisy Data Using Symbolic Regression. - Benjamin Cohen; Burcu Beykal; George M. Bollas (CDC, 2023)

Explainable Symbolic Regression Model for Tool Wear Diagnosis. - Debasish Mishra; Seulki Han; Krishna R. Pattipati; George M. Bollas (CoDIT, 2023)

Fault Detection in Closed-Loop Systems Based on Inferential Sensors. - Efi Safikou; George M. Bollas (ACC, 2024)

Symbolic regression-based hybrid models for a manufacturing process. - Seulki Han; Debasish Mishra; Krishna R. Pattipati; George M. Bollas (CoDIT, 2024)

Image-based Cutting Tool Health Diagnosis in Multi-machine Settings. - Debasish Mishra; Krishna R. Pattipati; George M. Bollas (ISM, 2024)

Physics-informed genetic programming for discovery of partial differential equations from scarce and noisy data. - Benjamin Cohen; Burcu Beykal; George M. Bollas (J. Comput. Phys., 2024)

Fault detection and isolation in uncertain dynamic systems using composite optimization and inferential sensing. - Efi Safikou; George M. Bollas (Comput. Chem. Eng., 2024)

Fault Diagnosis and Prognosis With Inferential Sensors: A Hybrid Approach Integrating Symbolic Regression and Information Theory. - Efi Safikou; Krishna R. Pattipati; George M. Bollas (IEEE Access, 2025)

Tool wear classification in precision machining using distance metrics and unsupervised machine learning. - Debasish Mishra; Utsav Awasthi; Krishna R. Pattipati; George M. Bollas (J. Intell. Manuf., 2025)