1.     Deypir, M., & Zoughi, T. (2024). Risk Score Computation for Android Mobile Applications Using the Twin k-NN Approach. Journal of Web Engineering, 23(4), 535-559.

1.     Zoughi, T., & Deypir, M. (2024). Mathematical analysis of AMRes: unlocking enhanced recognition across audio-visual domains. International Journal of Information Technology, 1-20.

1.     Deypir, M., Zoughi, T. Novel Security Metrics for Identifying Risky Unified Resource Locators (URLs). Iran J Sci Technol Trans Electr Eng 48, 1209–1227 (2024). https://doi.org/10.1007/s40998-023-00690-x

1.     Zoughi, T., & Deypir, M. (2024). Formal Verification of an Enhanced Deep Learning Model: Unveiling Computational Effectiveness in Speech Recognition. Scientia Iranica, (), -. doi: 10.24200/sci.2024.63333.8341

1.     دی پیر, محمود, معارفی, آرمین, ذوقی, & تکتم. (2024). ارائه یک روش مسیریابی ترکیبی چند متغیره برای بهبود کارایی شبکه های خودرویی. فصلنامه علمی کارافن.‎

1.     Afsharpour, P., Zoughi, T., Deypir, M., & Zoqi, M. J. (2024). Robust deep learning method for fruit decay detection and plant identification: enhancing food security and quality control. Frontiers in Plant Science, 15, 1366395.

1.     T. Zoughi, M. M. Homayounpour, “pre-training deep neural network based on deep Boltzmann machine for phone recognition,” in Computer Society of Iran Computer Conference (CSICC), 2015, pp. 625-630.

1.     T. Zoughi, M. M. Homayounpour, “Gender aware deep Boltzmann machines for phone recognition,” in International Joint Conference on Neural Networks (IJCNN), 2015, pp. 1-5. doi: 10.1109/IJCNN.2015.7280605

1.     T. Zoughi, R. Boostani, “Analyzing autocorrelation fluctuation of EEG signal for estimating depth of anesthesia”, in Electrical Engineering (ICEE), 2010 18th Iranian Conference, 2010, pp. 24-29.

1.     T. Zoughi, R. Boostani, P. Gifani, “New Method for Improving Smoothed Pseudo Wigner-Ville Algorithm for Estimating Depth of Anesthesia”, in International CSI computer conference, Iran, Tehran, 2009.