Research

Current Research

Inline with my previous research topics in the feild of machine learning, I am focusing on the security aspects of machine/deep learning networks. In addition, I am utilizing advanced machine/deep learning algorithms in the domain of computer, network, and software security.

Past Research

My past research was mostly involved with applications of machine learning, pattern recognition, and nonlinear system identification methods for solving industry related problems. I have publications in this field which can be found in Google Scholar as well as the publication section.

Publications

  • Anwar, A., Khormali, A., Nyang, D., Mohaisen, A., 2018. Understanding the Hidden Cost of Software Vulnerabilities: Measurements and Predictions. In Proceedings of the 14th EAI International Conference on Security and Privacy in Communication Networks, SecureComm 2018.

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  • Anwar, A., Khormali, A., Mohaisen, A., 2018. POSTER: Understanding the Hidden Cost of Software Vulnerabilities: Measurements and Predictions. In Proceedings of the 13th ACM ASIA Conference on Information, Computer and Communications Security, ACM ASIACCS 2018.

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  • Addeh, A., Khormali, A., Golilarz, N. A., 2018. Control chart pattern recognition using RBF neural network with new training algorithm and practical features. ISA Transactions, In Press.

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  • Khormali, A. and Addeh, J., 2016. A novel approach for recognition of control chart patterns: Type-2 fuzzy clustering optimized support vector machine. ISA transactions, 63, pp.256-264.

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  • Shabanian, A., Tousiwas, A.A.P., Pourmandi, M., Khormali, A. and Ataei, A., 2015. Optimization of brushless direct current motor design using an intelligent technique. ISA transactions, 57, pp.311-321.

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  • Valadkhani, A.H., Khormali, A., Shoorehdeli, M.A., Khaloozadeh, H. and Fatehi, A., 2016. On-line Full Probability Distribution Identification of ARX Model Parameters Based on Bayesian Approach. IFAC-PapersOnLine, 49(7), pp.508-513.

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  • Khormali, A., Yousefi, I., Yahyaei, H. and Aliyari, S.M., 2015. Identification of an industrial gas turbine based on Rowen's model and using Multi-Objective Optimization method. In 3rd RSI International Conference on Robotics and Mechatronics (ICROM 2015), IEEE, pp. 482-487.

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  • Khormali, A.O. and Sh, M.A., 2014. Gas turbine fault detection and identification by using fuzzy clustering methods. In Second RSI/ISM International Conference on Robotics and Mechatronics(ICRoM 2014), IEEE, pp. 070-075.

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Contact

  • Research 1, University of Central Florida, Central Florida Blvd., Orlando, Florida 32816