George M. Bollas

Krishna R. Pattipati

IEEE Trans. Control. Syst. Technol., May, 2026

Hyperdimensional computing for explainable information fusion and multi-task adaptation in advanced manufacturing.

[BibT_eX]

[DOI]

Inf. Fusion, 2026

2025

Tool wear classification in precision machining using distance metrics and unsupervised machine learning.

[BibT_eX]

[DOI]

J. Intell. Manuf., January, 2025

Fault Diagnosis and Prognosis With Inferential Sensors: A Hybrid Approach Integrating Symbolic Regression and Information Theory.

[BibT_eX]

[DOI]

Krishna R. Pattipati

IEEE Access, 2025

GAN-based feature representation and data augmentation for tool wear classification.

[BibT_eX]

[DOI]

Seulki Han

Proceedings of the 11th International Conference on Control, 2025

2024

Fault detection and isolation in uncertain dynamic systems using composite optimization and inferential sensing.

[BibT_eX]

[DOI]

Comput. Chem. Eng., February, 2024

Physics-informed genetic programming for discovery of partial differential equations from scarce and noisy data.

[BibT_eX]

[DOI]

Benjamin Cohen

Burcu Beykal

J. Comput. Phys., 2024

Image-based Cutting Tool Health Diagnosis in Multi-machine Settings.

[BibT_eX]

[DOI]

Debasish Mishra

Krishna R. Pattipati

Proceedings of the 6th International Conference on Industry 4.0 and Smart Manufacturing (ISM 2024), 2024

Symbolic regression-based hybrid models for a manufacturing process.

[BibT_eX]

[DOI]

Proceedings of the 10th International Conference on Control, 2024

Fault Detection in Closed-Loop Systems Based on Inferential Sensors.

[BibT_eX]

[DOI]

Proceedings of the American Control Conference, 2024

2023

Explainable Symbolic Regression Model for Tool Wear Diagnosis.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Control, 2023

Dynamic System Identification from Scarce and Noisy Data Using Symbolic Regression.

[BibT_eX]

[DOI]

Benjamin Cohen

Burcu Beykal

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

Symbolic Regression for Fault Prognosis and Remaining Useful Life Estimation.

[BibT_eX]

[DOI]

Proceedings of the American Control Conference, 2023

2022

Inference of faults through symbolic regression of system data.

[BibT_eX]

[DOI]

Comput. Chem. Eng., 2022

2021

Sensor Selection Embedded in Active Fault Diagnosis Algorithms.

[BibT_eX]

[DOI]

IEEE Trans. Control. Syst. Technol., 2021

Sensor Fusion and Inferential Sensing for Fault Detection and Isolation in Uncertain Systems<sup>*</sup>.

[BibT_eX]

[DOI]

Proceedings of the 5th International Conference on Control and Fault-Tolerant Systems, 2021

2020

Least-Squares- and Information-Theory-Based Inferential Sensor Design for Fault Diagnostics.

[BibT_eX]

[DOI]

Proceedings of the 2020 American Control Conference, 2020

2019

Active Fault Identification by Optimization of Test Designs.

[BibT_eX]

[DOI]

IEEE Trans. Control. Syst. Technol., 2019

Analysis of transient data in test designs for active fault detection and identification.

[BibT_eX]

[DOI]

Comput. Chem. Eng., 2019

Semi-infinite programming for global guarantees of robust fault detection and isolation in safety-critical systems.

[BibT_eX]

[DOI]

Comput. Chem. Eng., 2019

2018

Design of Built-In Tests for Active Fault Detection and Isolation of Discrete Faults.

[BibT_eX]

[DOI]

Harish Chaandar Ravichandar

IEEE Access, 2018

Learning Stable Nonlinear Dynamical Systems with External Inputs using Gaussian Mixture Models.

[BibT_eX]

[DOI]

Proceedings of the 2018 Annual American Control Conference, 2018

Active Fault Diagnosis with Sensor Selection in a Diesel Engine Air Handling System.

[BibT_eX]

[DOI]