
Dr. Firuz Kamalov |
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Highest Degree | PhD University of Nebraska (USA) |
Position | Associate Professor |
Faculty | Faculty of Engineering, Applied Science and Technology |
Telephone/Ext | +971(4)7096175 |
Location | C3-01 |
Position Associate Professor
Email firuz@cud.ac.ae
Telephone/Ext +971(4)7096175
Location C3-01
Highest Degree PhD University of Nebraska (USA)
Faculty Faculty of Engineering, Applied Science and Technology
Biography
Dr Kamalov obtained PhD in Mathematics in 2011 from University of Nebraska-Lincoln. While at UNL he was a recipient of prestigious Othmer Fellowship (2005-2008) given to exceptional incoming scholars. Dr Kamalov obtained BA in Mathematics and Economics from Macalester College where he was a recipient of DeWitt Wallace Distinguished Scholarship (2000-2004). Dr Kamalov joined Canadian University Dubai in 2011 where he has taught a wide range of mathematics courses across curricula. He is a recipient of CUD Academic Research Award (2013) and CUD Teaching Award (2013). Dr Kamalov's research interests include C*-algebras, functional analysis, machine learning, and data mining. He is a managing editor of Gulf Journal of Mathematics.
Google Scholar
Selected publications
- Kamalov, F., Gurrib, I. & Rajab, K. (2021). Financial Forecasting with Machine Learning: Price Vs Return. Journal of Computer Science, 17(3), 251-264.
- Kamalov, F., & Leung, H. H. (2020, November). Deep learning regularization in imbalanced data. In 2020 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI) (pp. 1-5). IEEE.
- Kamalov, F., Moussa, S., Zgheib, R., & Mashaal, O. (2020, December). Feature selection for intrusion detection systems. In 2020 13th International Symposium on Computational Intelligence and Design (ISCID) (pp. 265-269). IEEE.
- Kamalov, F.(2020). Kernel density estimation based sampling for imbalanced class distribution. Information Sciences, 512, 1192-1201.
- Kamalov, F., & Denisov, D. (2020). Gamma distribution-based sampling for imbalanced data. Knowledge-Based Systems, 207, 106368.
- Kamalov, F., Smail, L., & Gurrib, I. (2020, December). Forecasting with Deep Learning: S&P 500 index. In 2020 13th International Symposium on Computational Intelligence and Design (ISCID) (pp. 422-425). IEEE.
- Kamalov, F., Smail, L., & Gurrib, I. (2020, December). Forecasting with Deep Learning: S&P 500 index. In 2020 13th International Symposium on Computational Intelligence and Design (ISCID) (pp. 422-425). IEEE.
- Kamalov, F., Smail, L., & Gurrib, I. (2020, November). Stock price forecast with deep learning. In 2020 International Conference on Decision Aid Sciences and Application (DASA) (pp. 1098-1102). IEEE.
- Thabtah, F., Hammoud, S., Kamalov, F., & Gonsalves, A. (2020). Data imbalance in classification: Experimental evaluation. Information Sciences, 513, 429–441.
- Thabtah, F., Kamalov, F., Hammoud, S., & Shahamiri, S. R. (2020). Least Loss: A simplified filter method for feature selection. Information Sciences, 534, 1-15.
- Thabtah, F., Kamalov, F., & Rajab, K. (2018). A new computational intelligence approach to detect autistic features for autism screening. International Journal of Medical Informatics, 117, 112–124.
- Okash, A., Kamalov, F., Hamidi, S., Roberts, C., & Abdulnasir, S. (2020). Data mining in the time of COVID-19. PalArch’s Journal of Archaeology of Egypt / Egyptology, 17(8), 224-248.
- Kamalov, F. (2020). Forecasting significant stock price changes using neural networks. Neural Computing and Applications, 32, 17655–17667.
- Kamalov, F. (2020). Generalized feature similarity measure. Annals of Mathematics and Artificial Intelligence, 88, 987–1002.
- Kamalov, F., Leung, H.H. & Moussa, S. (2020). Monotonicity of the χ2-statistic and Feature Selection. Annals of Data Science.
- Gurrib, I., Elsharief, E., & Kamalov, F. (2020). The effect of energy cryptos on efficient portfolios of key energy listed companies in the S&P composite 1500 energy index. International Journal of Energy Economics and Policy, 10(2), 179–193.
- Gurrib, I., Kamalov, F. & Elshareif, E. (2021). Can the leading us energy stock prices be predicted using Ichimoku clouds? International Journal of Energy Economics and Policy. 11(1), 41-51.
- Gurrib, I., & Kamalov, F. (2019). The implementation of an adjusted relative strength index model in foreign currency and energy markets of emerging and developed economies. Macroeconomics and Finance in Emerging Market Economies, 12(2), 105–123.
- Kamalov, F. (2019). Sensitivity Analysis for Feature Selection. In Proceedings - 17th IEEE International Conference on Machine Learning and Applications, ICMLA 2018 (pp. 1466–1470).
Dr Kamalov obtained PhD in Mathematics in 2011 from University of Nebraska-Lincoln. While at UNL he was a recipient of prestigious Othmer Fellowship (2005-2008) given to exceptional incoming scholars. Dr Kamalov obtained BA in Mathematics and Economics from Macalester College where he was a recipient of DeWitt Wallace Distinguished Scholarship (2000-2004). Dr Kamalov joined Canadian University Dubai in 2011 where he has taught a wide range of mathematics courses across curricula. He is a recipient of CUD Academic Research Award (2013) and CUD Teaching Award (2013). Dr Kamalov's research interests include C*-algebras, functional analysis, machine learning, and data mining. He is a managing editor of Gulf Journal of Mathematics.
Google Scholar
Selected publications
- Kamalov, F., Gurrib, I. & Rajab, K. (2021). Financial Forecasting with Machine Learning: Price Vs Return. Journal of Computer Science, 17(3), 251-264.
- Kamalov, F., & Leung, H. H. (2020, November). Deep learning regularization in imbalanced data. In 2020 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI) (pp. 1-5). IEEE.
- Kamalov, F., Moussa, S., Zgheib, R., & Mashaal, O. (2020, December). Feature selection for intrusion detection systems. In 2020 13th International Symposium on Computational Intelligence and Design (ISCID) (pp. 265-269). IEEE.
- Kamalov, F.(2020). Kernel density estimation based sampling for imbalanced class distribution. Information Sciences, 512, 1192-1201.
- Kamalov, F., & Denisov, D. (2020). Gamma distribution-based sampling for imbalanced data. Knowledge-Based Systems, 207, 106368.
- Kamalov, F., Smail, L., & Gurrib, I. (2020, December). Forecasting with Deep Learning: S&P 500 index. In 2020 13th International Symposium on Computational Intelligence and Design (ISCID) (pp. 422-425). IEEE.
- Kamalov, F., Smail, L., & Gurrib, I. (2020, December). Forecasting with Deep Learning: S&P 500 index. In 2020 13th International Symposium on Computational Intelligence and Design (ISCID) (pp. 422-425). IEEE.
- Kamalov, F., Smail, L., & Gurrib, I. (2020, November). Stock price forecast with deep learning. In 2020 International Conference on Decision Aid Sciences and Application (DASA) (pp. 1098-1102). IEEE.
- Thabtah, F., Hammoud, S., Kamalov, F., & Gonsalves, A. (2020). Data imbalance in classification: Experimental evaluation. Information Sciences, 513, 429–441.
- Thabtah, F., Kamalov, F., Hammoud, S., & Shahamiri, S. R. (2020). Least Loss: A simplified filter method for feature selection. Information Sciences, 534, 1-15.
- Thabtah, F., Kamalov, F., & Rajab, K. (2018). A new computational intelligence approach to detect autistic features for autism screening. International Journal of Medical Informatics, 117, 112–124.
- Okash, A., Kamalov, F., Hamidi, S., Roberts, C., & Abdulnasir, S. (2020). Data mining in the time of COVID-19. PalArch’s Journal of Archaeology of Egypt / Egyptology, 17(8), 224-248.
- Kamalov, F. (2020). Forecasting significant stock price changes using neural networks. Neural Computing and Applications, 32, 17655–17667.
- Kamalov, F. (2020). Generalized feature similarity measure. Annals of Mathematics and Artificial Intelligence, 88, 987–1002.
- Kamalov, F., Leung, H.H. & Moussa, S. (2020). Monotonicity of the χ2-statistic and Feature Selection. Annals of Data Science.
- Gurrib, I., Elsharief, E., & Kamalov, F. (2020). The effect of energy cryptos on efficient portfolios of key energy listed companies in the S&P composite 1500 energy index. International Journal of Energy Economics and Policy, 10(2), 179–193.
- Gurrib, I., Kamalov, F. & Elshareif, E. (2021). Can the leading us energy stock prices be predicted using Ichimoku clouds? International Journal of Energy Economics and Policy. 11(1), 41-51.
- Gurrib, I., & Kamalov, F. (2019). The implementation of an adjusted relative strength index model in foreign currency and energy markets of emerging and developed economies. Macroeconomics and Finance in Emerging Market Economies, 12(2), 105–123.
- Kamalov, F. (2019). Sensitivity Analysis for Feature Selection. In Proceedings - 17th IEEE International Conference on Machine Learning and Applications, ICMLA 2018 (pp. 1466–1470).