Kai Goebel

63 papers Misc 1Journal 47Unranked 13
YearRankTypeTitle / Venue / Authors
2025 J jnl
Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study.
CoRR
Kai Goebel, Patrik Zips
2024 J jnl
A metric for assessing and optimizing data-driven prognostic algorithms for predictive maintenance.
Reliab. Eng. Syst. Saf.
Antonios Kamariotis, Konstantinos Tatsis, Eleni N. Chatzi, Kai Goebel, Daniel Straub
2024 J jnl
AI in Industrial IoT Cybersecurity [Industrial and Governmental Activities].
IEEE Comput. Intell. Mag.
Kai Goebel, Shantanu Rane
2024 J jnl
Health Index Estimation Through Integration of General Knowledge with Unsupervised Learning.
CoRR
Kristupas Bajarunas, Marcia Lourenco Baptista, Kai Goebel, Manuel Arias Chao
2024 J jnl
Health index estimation through integration of general knowledge with unsupervised learning.
Reliab. Eng. Syst. Saf.
Kristupas Bajarunas, Marcia Lourenco Baptista, Kai Goebel, Manuel Arias Chao
2024 J jnl
Monitoring-Supported Value Generation for Managing Structures and Infrastructure Systems.
CoRR
Antonios Kamariotis, Eleni N. Chatzi, Daniel Straub, Nikolaos Dervilis, Kai Goebel, Aidan J. Hughes, Geert Lombaert, Costas Papadimitriou, Konstantinos G. Papakonstantinou, Matteo Pozzi, Michael Todd, Keith Worden
2022 J jnl
Fusing physics-based and deep learning models for prognostics.
Reliab. Eng. Syst. Saf.
Manuel Arias Chao, Chetan S. Kulkarni, Kai Goebel, Olga Fink
2022 J jnl
Relation between prognostics predictor evaluation metrics and local interpretability SHAP values.
Artif. Intell.
Marcia Lourenco Baptista, Kai Goebel, Elsa M. P. Henriques
2021 J jnl
A self-organizing map and a normalizing multi-layer perceptron approach to baselining in prognostics under dynamic regimes.
Neurocomputing
Marcia Lourenco Baptista, Elsa M. P. Henriques, Kai Goebel
2021 J jnl
Aircraft Engine Run-to-Failure Dataset under Real Flight Conditions for Prognostics and Diagnostics.
Data
Manuel Arias Chao, Chetan S. Kulkarni, Kai Goebel, Olga Fink
2021 J jnl
Bearing Life Prediction With Informed Hyperprior Distribution: A Bayesian Hierarchical and Machine Learning Approach.
IEEE Access
Madhav Mishra, Jesper Martinsson, Kai Goebel, Matti Rantatalo
2021 J jnl
Exploring Architectures for Integrated Resilience Optimization.
J. Aerosp. Inf. Syst.
Daniel E. Hulse, Arpan Biswas, Christopher Hoyle, Irem Y. Tumer, Chetan S. Kulkarni, Kai Goebel
2021 J jnl
Improving tail accuracy of the predicted cumulative distribution function of time of failure.
Reliab. Eng. Syst. Saf.
Gina Sierra, Elinirina Iréna Robinson, Kai Goebel
2021 J jnl
Remaining Useful Life Prediction of Bearings Using Ensemble Learning: The Impact of Diversity in Base Learners and Features.
J. Comput. Inf. Sci. Eng.
Junchuan Shi, Tianyu Yu, Kai Goebel, Dazhong Wu
2020 J jnl
Fusing Physics-based and Deep Learning Models for Prognostics.
CoRR
Manuel Arias Chao, Chetan S. Kulkarni, Kai Goebel, Olga Fink
2020 J jnl
Probabilistic Risk-Based Operational Safety Bound for Rotary-Wing Unmanned Aircraft Systems Traffic Management.
J. Aerosp. Inf. Syst.
Jueming Hu, Heinz Erzberger, Kai Goebel, Yongming Liu
2020 J jnl
Real-Time Model Calibration with Deep Reinforcement Learning.
CoRR
Yuan Tian, Manuel Arias Chao, Chetan S. Kulkarni, Kai Goebel, Olga Fink
2019 J jnl
Battery health management for small-size rotary-wing electric unmanned aerial vehicles: An efficient approach for constrained computing platforms.
Reliab. Eng. Syst. Saf.
Gina Sierra, Marcos E. Orchard, Kai Goebel, Chetan S. Kulkarni
2019 J jnl
Hybrid deep fault detection and isolation: Combining deep neural networks and system performance models.
CoRR
Manuel Arias Chao, Chetan S. Kulkarni, Kai Goebel, Olga Fink
2018 J jnl
Bayesian hierarchical model-based prognostics for lithium-ion batteries.
Reliab. Eng. Syst. Saf.
Madhav Mishra, Jesper Martinsson, Matti Rantatalo, Kai Goebel
2018 J jnl
Ensemble of optimized echo state networks for remaining useful life prediction.
Neurocomputing
Marco Rigamonti, Piero Baraldi, Enrico Zio, Indranil Roychoudhury, Kai Goebel, Scott Poll
2018 J jnl
Resilience-based network design under uncertainty.
Reliab. Eng. Syst. Saf.
Xiaoge Zhang, Sankaran Mahadevan, Shankar Sankararaman, Kai Goebel
2017 J jnl
A new algorithm for prognostics using Subset Simulation.
Reliab. Eng. Syst. Saf.
Manuel Chiachío, Juan Chiachío, Shankar Sankararaman, Kai Goebel, John D. Andrews
2015 J jnl
A Recursive Receding Horizon Planning for Unmanned Vehicles.
IEEE Trans. Ind. Electron.
Bin Zhang, Liang Tang, Jonathan A. DeCastro, Michael J. Roemer, Kai Goebel
2015 J jnl
A testbed for implementing prognostic methodologies on cryogenic propellant loading systems.
IEEE Instrum. Meas. Mag.
Chetan S. Kulkarni, George Gorospe, Matthew J. Daigle, Kai Goebel
2015 J jnl
Condition-based prediction of time-dependent reliability in composites.
Reliab. Eng. Syst. Saf.
Juan Chiachío, Manuel Chiachío, Shankar Sankararaman, Abhinav Saxena, Kai Goebel
2015 J jnl
Prognostic Health-Management System Development for Electromechanical Actuators.
J. Aerosp. Inf. Syst.
Edward Balaban, Abhinav Saxena, Sriram Narasimhan, Indranil Roychoudhury, Michael Koopmans, Carl Ott, Kai Goebel
2014 J jnl
Uncertainty Quantification in Remaining Useful Life Prediction Using First-Order Reliability Methods.
IEEE Trans. Reliab.
Shankar Sankararaman, Matthew J. Daigle, Kai Goebel
2013 J jnl
Model-Based Prognostics With Concurrent Damage Progression Processes.
IEEE Trans. Syst. Man Cybern. Syst.
Matthew J. Daigle, Kai Goebel
2012 — conf
A Briefing on Metrics and Risks for Autonomous Decision-making in Aerospace Applications.
Infotech@Aerospace
Susan A. Frost, Kai Goebel, Jose Celaya
2012 — conf
A Discussion on Uncertainty Representation and Interpretation in Model-based Prognostics Algorithms based on Kalman Filter Estimation Applied to Prognostics of Electronics Components.
Infotech@Aerospace
Jose Celaya, Abhinav Saxena, Kai Goebel
2012 — conf
A Model-based Avionic Prognostic Reasoner (MAPR).
Infotech@Aerospace
Sonia Vohnout, Byoung Kim, Neil Kunst, Bill Gleeson, Robert Wagoner, Edward Balaban, Kai Goebel
2012 J jnl
A knowledge-based system approach for sensor fault modeling, detection and mitigation.
Expert Syst. Appl.
Jonny Carlos da Silva, Abhinav Saxena, Edward Balaban, Kai Goebel
2012 J jnl
Decorrelated Feature Space and Neural Nets Based Framework for Failure Modes Clustering in Electronics Subjected to Mechanical Shock.
IEEE Trans. Reliab.
Pradeep Lall, Prashant Gupta, Kai Goebel
2012 J jnl
Extended Kalman Filter Models and Resistance Spectroscopy for Prognostication and Health Monitoring of Leadfree Electronics Under Vibration.
IEEE Trans. Reliab.
Pradeep Lall, Ryan Lowe, Kai Goebel
2012 — conf
Prognostics Health Management and Physics Based Failure Models for Electrolytic Capacitors.
Infotech@Aerospace
Chetan S. Kulkarni, Jose Celaya, Gautam Biswas, Kai Goebel
2012 J jnl
Prognostics Health Management of Electronic Systems Under Mechanical Shock and Vibration Using Kalman Filter Models and Metrics.
IEEE Trans. Ind. Electron.
Pradeep Lall, Ryan Lowe, Kai Goebel
2012 — conf
Requirements Flowdown for Prognostics and Health Management.
Infotech@Aerospace
Abhinav Saxena, Indranil Roychoudhury, Jose Celaya, Bhaskar Saha, Sankalita Saha, Kai Goebel
2012 — conf
Using Markov Models of Fault Growth Physics and Environmental Stresses to Optimize Control Actions.
Infotech@Aerospace
Brian Bole, Kai Goebel, George J. Vachtsevanos
2011 J jnl
Prognostication of Residual Life and Latent Damage Assessment in Lead-Free Electronics Under Thermomechanical Loads.
IEEE Trans. Ind. Electron.
Pradeep Lall, Chandan Bhat, Madhura Hande, Vikrant More, Rahul Vaidya, Kai Goebel
2009 J jnl
Precursor Parameter Identification for Insulated Gate Bipolar Transistor (IGBT) Prognostics.
IEEE Trans. Reliab.
Nishad Patil, Jose Celaya, Diganta Das, Kai Goebel, Michael G. Pecht
2009 J jnl
Prognostics Methods for Battery Health Monitoring Using a Bayesian Framework.
IEEE Trans. Instrum. Meas.
Bhaskar Saha, Kai Goebel, Scott Poll, Jon Christophersen
2008 J jnl
AAAI Fall Symposium Reports.
AI Mag.
Jerry T. Ball, Chris Arney, Samuel G. Collins, Mitchell Marcus, Sergei Nirenburg, Antonio Chella, Kai Goebel, Jason H. Li, Margaret Lyell, Brian Magerko, Riccardo Manzotti, Clayton T. Morrison, Tim Oates, Mark O. Riedl, Goran Trajkovski, Walt Truszkowski, N. Serdar Uckun
2008 J jnl
Correcting Sensor Drift and Intermittency Faults With Data Fusion and Automated Learning.
IEEE Syst. J.
Kai Goebel, Weizhong Yan
2007 — conf
A Bayesian Framework for Remaining Useful Life Estimation.
AAAI Fall Symposium: Artificial Intelligence for Prognostics
Bhaskar Saha, Kai Goebel, Scott Poll, Jon Christophersen
2007 — conf
A Survey of Artificial Intelligence for Prognostics.
AAAI Fall Symposium: Artificial Intelligence for Prognostics
Mark Schwabacher, Kai Goebel
2007 J jnl
Appliance Call Center: A Successful Mixed-Initiative Case Study.
AI Mag.
William Cheetham, Kai Goebel
2007 — ed.
Artificial Intelligence for Prognostics, Papers from the 2007 AAAI Fall Symposium, Arlington, Virginia, USA, November 9-11, 2007.
AAAI Fall Symposium: Artificial Intelligence for Prognostics
George J. Vachtsevanos, N. Serdar Uckun, Kai Goebel
2007 — conf
Health-Management Driven Control Reconfiguration Approach for Flight Vehicles.
AAAI Fall Symposium: Artificial Intelligence for Prognostics
Asif Khalak, Kai Goebel
2007 — conf
Improving Classifier Fusion Using Particle Swarm Optimization.
MCDM
Kalyan Veeramachaneni, Weizhong Yan, Kai Goebel, Lisa Ann Osadciw
2007 — conf
Prognostics in the Control Loop.
AAAI Fall Symposium: Artificial Intelligence for Prognostics
Liang Tang, Gregory J. Kacprzynski, Kai Goebel, Johan Reimann, Marcos E. Orchard, Abhinav Saxena, Bhaskar Saha
2005 J jnl
Evolutionary design and optimization of aircraft engine controllers.
IEEE Trans. Syst. Man Cybern. Part C
Raj Subbu, Kai Goebel, Dean K. Frederick
2005 J jnl
The Workshop Program at the Nineteenth National Conference on Artificial Intelligence.
AI Mag.
Ion Muslea, Virginia Dignum, Daniel D. Corkill, Catholijn M. Jonker, Frank Dignum, Silvia Coradeschi, Alessandro Saffiotti, Dan Fu, Jeff Orkin, William Cheetham, Kai Goebel, Piero P. Bonissone, Leen-Kiat Soh, Randolph M. Jones, Robert E. Wray III, Matthias Scheutz, Daniela Pucci de Farias, Shie Mannor, Georgios Theocharous, Doina Precup, Bamshad Mobasher, Sarabjot S. Anand, Bettina Berendt, Andreas Hotho, Hans W. Guesgen, Michael T. Rosenstein, Mohammad Ghavamzadeh
2005 — conf
Using an Ensemble of Classifiers to Audit a Production Classifier.
Multiple Classifier Systems
Piero P. Bonissone, Neil H. W. Eklund, Kai Goebel
2004 — conf
Classifier Fusion Using Triangular Norms.
Multiple Classifier Systems
Piero P. Bonissone, Kai Goebel, Weizhong Yan
2002 J jnl
The 2002 AAAI Spring Symposium Series.
AI Mag.
Jussi Karlgren, Pentti Kanerva, Björn Gambäck, Kenneth D. Forbus, Kagan Tumer, Peter Stone, Kai Goebel, Gaurav S. Sukhatme, Tucker R. Balch, Bernd Fischer, Doug Smith, Sanda M. Harabagiu, Vinay K. Chaudri, Mike Barley, Hans W. Guesgen, Thomas F. Stahovich, Randall Davis, James A. Landay
2001 — ch.
Applications of Soft CBR at General Electric.
Soft Computing in Case Based Reasoning
Bill Cheetham, Paul Cuddihy, Kai Goebel
2001 J jnl
Architecture and design of a diagnostic information fusion system.
Artif. Intell. Eng. Des. Anal. Manuf.
Kai Goebel
2001 Misc conf
Case-Based Reasoning at General Electric.
FLAIRS
William Cheetham, Anil Varma, Kai Goebel
2001 J jnl
Soft Computing for diagnostics in equipment service.
Artif. Intell. Eng. Des. Anal. Manuf.
Piero P. Bonissone, Kai Goebel
2001 J jnl
Special Issue: AI in equipment service.
Artif. Intell. Eng. Des. Anal. Manuf.
Alice M. Agogino, Piero P. Bonissone, Kai Goebel, George J. Vachtsevanos
2000 J jnl
Reports on the AAAI Spring Symposia (March 1999).
AI Mag.
David J. Musliner, Barney Pell, Wolff Dobson, Kai Goebel, Gautam Biswas, Sheila A. McIlraith, Giuseppina C. Gini, Sven Koenig, Shlomo Zilberstein, Weixiong Zhang
1999 J jnl
Hybrid soft computing systems: industrial and commercial applications.
Proc. IEEE
Piero P. Bonissone, Yu-To Chen, Kai Goebel, Pratap S. Khedkar