- AI-based circuit modeling
- Artificial Neural Networks
- Deep learning
- Computer-Aided Design (CAD)
- Z Naghibi, J Payandehpeyman, K Moradi, "Parametric Investigation of Carbon Nanotube-Based Nanomechanical Mass Sensors Using Structural Mechanics and an Artificial Neural Network Approach", Journal of Stress Analysis, June 2023.
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Z. Naghibi, "Calculating the characteristics of an all-adder digital circuit using a method based on circuit layout design and comparing it with methods based on the IBIS model and methods based on the SPICE model." 6th National Conference on Electrical Engineering and Intelligent Systems, May 2022.
- Z. Naghibi,"Examining the characteristics of the digital block in different processing corners at the transistor level." 6th National Conference on Electrical Engineering and Intelligent Systems, May 2022.
- Z. Naghibi, "Positioning and routing in the MIPS processor chip and calculating time, power consumption and its area using the SoC Encounter tool." International conference on the application of engineering, 2022.
- Z. Naghibi, et al. ,"Predicting the behavior of graphene biosensors using artificial neural networks." 6th National Conference on Electrical Engineering and Intelligent Systems, May 2022.
- Z.Naghibi, S. A. Sadrossadat, S. Safari, “Time-domain modeling of nonlinear circuits using Adjoint Recurrent Neural Network” , International Journal of Circuit Theory and Applications, Nov. 2021.
- A. Kokabi, Z. Nasiri Mahd, Z. Naghibi, “Linear and nonlinear machine learning correlation of transition metal cluster characteristics." Journal of Nanoparticle Research, Aug. 2021.
- S. A. Sadrossadat, Z.Naghibi, "Integrating Parallel Computation Technique to State-Space Dynamic Neural Network Modeling of Optical Fiber", International Microsystems, Packaging, Assembly and Circuits Technology Conference, Dec. 2021.
- S. A. Sadrossadat, Z.Naghibi, “Parallelizing Time-Delay Recurrent Neural Network Modeling Technique on a Multi-Core Architecture", International Microsystems, Packaging, Assembly and Circuits Technology Conference, Dec. 2021.
- Z. Naghibi, et al., "Prediction of low frequency vibration mode and energy dependence of mediating elements with deep neural networks." 14th International Conference of the Iranian Association for Operations Research, Oct. 2021.
- Z. Naghibi, et al., , "Investigating the correlation of properties of transition metal clusters with machine learning methods." 14th international conference of the Iranian Association for Operations Research, Oct. 2021.
- Z.Naghibi, S. A. Sadrossadat, S. Safari, “Dynamic behavioural modeling of nonlinear circuits using a novel recurrent neural network technique”. International Journal of Circuit Theory and Applications, Feb. 2019.
- Z.Naghibi, S. A. Sadrossadat, S. Safari, “Time-domain modeling of nonlinear circuits using deep recurrent neural network technique.” International Journal of Electronics and Communications, Dec. 2019.
- Deep Learning (for M.Sc students)
- Artificial Neural Network (for M.Sc students)
- Advanced Computer Architecture (for M.Sc students)
- Microprocessor and Assembly Language
- Signals and Systems
- Digital System Design
- Operating System
- CAD Tool Laboratory
- Computer Architecture Laboratory
- Digital System Design Laboratory
- Head of Computer Engineering Department, 2022 September -present
- Member of the Support and Supervision Committee for Scientific Societies, 2023 July-present
- Advisor of the Computer Engineering Scientific Society, 2023 May-present
- Head of Logic Circuit and Computer Architecture Laboratory, 2022 April-present
- Ranked 10th in national university entrance exam for Ph.D. degree in computer engineering
- Ranked 1st within top 1% in the national entrance exam for M.Sc. degree
Address: Shahid Fahmideh.St,Hamedan,IRAN
Telephone:+98(81)38411000
Email: info@hut.ac.ir
