| Optimization for industrial problems P Bangert Springer Science & Business Media, 2012 | 70 | 2012 |
| In search of minimal random braid configurations PD Bangert, MA Berger, R Prandi Journal of Physics A: Mathematical and General 35 (1), 43, 2001 | 30 | 2001 |
| Machine learning and data science in the oil and gas industry: Best practices, tools, and case studies P Bangert Gulf Professional Publishing, 2021 | 28 | 2021 |
| Machine Learning and Data Science in the Power Generation Industry: Best Practices, Tools, and Case Studies P Bangert Elsevier, 2021 | 20 | 2021 |
| Enhancement of superthermal ultracold neutron production by trapping cold neutrons PD Bangert, MD Cooper, SK Lamoreaux Nuclear Instruments and Methods in Physics Research Section A: Accelerators …, 1998 | 16 | 1998 |
| Optimization: simulated annealing P Bangert, P Bangert Optimization for Industrial Problems, 165-200, 2012 | 15 | 2012 |
| Highly efficient representation and active learning framework for imbalanced data and its application to covid-19 x-ray classification H Hao, S Didari, JO Woo, H Moon, P Bangert | 13 | 2021 |
| Active learning performance in labeling radiology images is 90% effective P Bangert, H Moon, JO Woo, S Didari, H Hao Frontiers in radiology 1, 748968, 2021 | 11 | 2021 |
| Predicting and detecting equipment malfunctions using machine learning P Bangert SPE Middle East Oil and Gas Show and Conference, D043S090R003, 2019 | 11 | 2019 |
| Diagnosing and predicting problems with rod pumps using machine learning P Bangert SPE Middle East Oil and Gas Show and Conference, D032S106R001, 2019 | 11 | 2019 |
| Beam pump dynamometer card classification using machine learning SA Sharaf, P Bangert, M Fardan, K Alqassab, M Abubakr, M Ahmed SPE Middle East Oil and Gas Show and Conference, D032S066R003, 2019 | 10 | 2019 |
| Smart condition monitoring using machine learning P Bangert SPE Middle East Intelligent Oil and Gas Symposium, SPE-187936-MS, 2017 | 10 | 2017 |
| Predictive maintenance for rod pumps P Bangert, S Sharaf SPE Western Regional Meeting, D031S009R003, 2019 | 9 | 2019 |
| Mathematical model using machine learning boosts output offshore China: Advances in production C TAN, JIE ZHANG, P BANGERT, B Liu World oil 231 (11), 2010 | 9 | 2010 |
| Introduction to machine learning in the oil and Gas Industry P Bangert Machine Learning and Data Science in the Oil and Gas Industry, 69-81, 2021 | 8 | 2021 |
| The Digitalization Journey of the Brage Digital Twin P Kronberger, P Dabrowski, J Chacon, P Bangert SPE Norway Subsurface Conference?, D021S006R001, 2020 | 6 | 2020 |
| Raid braid: Fast conjugacy disassembly in braid and other groups PD Bangert Proceedings of Applications of Computer Algebra, 2004 | 6 | 2004 |
| Real-Time Quality Control of Injection Molding P Bangert, P Cajaraville, B Dormann, M Kohler, P Imgrund, J Haack, ... Proceedings of the XIX Conference on Machine Tools and Manufacturing …, 2012 | 5 | 2012 |
| Braids and knots MA Berger, LH Kauffman, B Khesin, HK Moffatt, RL Ricca, DW Sumners, ... Lectures on topological fluid mechanics, 1-73, 2009 | 5 | 2009 |
| Algorithmic problems in the braid groups PD Bangert PQDT-Global, 2002 | 5 | 2002 |
