Assistant Professor
Computational Mathematics, Science and Engineering (CMSE), College of Engineering
Engineering Bldg, 428 S Shaw Ln Room 2503
Dr. Khasawneh’s research program focuses on complex dynamical systems with applications in science and engineering. The systems he’s interested in are both numerical and experimental, and they often include nonlinearities, delays, and stochastic effects. Examples of his current research activities include leveraging Topological Data Analysis (TDA) and machine learning for signal processing and advanced
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manufacturing including chatter diagnosis from machining vibration signals, and quantifying surface texture in fabricated parts. His work also includes studying the stability of delay differential equations both deterministic and stochastic.
Research Areas -
Dynamical Systems
Time Series Analysis
Advanced Manufacturing
Ph.D., Mechanical Engineering and Materials Science, Duke University, 2010
M.S., Mechanical and Aerospace Engineering, University of Missouri-Columbia, 2006
B.S., Mechanical Engineering, Jordan University of Science and Technology 2004
Max Chumley, Melih Yesilli, Jisheng Chen, Firas Khasawneh, Yang Guo, “Pattern characterization using topological data analysis: Application to piezo vibration striking treatment,” Precision Engineering, (83), pp. 42-57, (May 2023). [Editor’s Choice]. DOI: 10.1016/j.precisioneng.2023.05.005
Audun Myers, David Munoz, Firas A. Khasawneh, Elizabeth Munch; Temporal network analysis using zigzag persistence, EPJ Data Science, 12 (6), pp. 132446, (March 2023). DOI: 10.1140/epjds/s13688-023-00379-5
Audun Myers, and Firas A. Khasawneh; On the automatic parameter selection for permutation entropy. Chaos; 30 (3): 033130. (March 2020). [Editor’s Choice]. DOI: 10.1063/1.5111719
Melih Can Yesilli, Firas Khasawneh, Andreas Otto, “On transfer learning for chatter detection in turning using wavelet packet transform and ensemble empirical mode decomposition," CIRP Journal of Manufacturing Science and Technology, (28), pp. 118-135, (January 2020). DOI: 10.1016/j.cirpj.2019.11.003
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