Welcome to CADS-LAB

Dear Visitor:

Welcome to Computer Architecture and Dependable Systems (CADS) laboratory website. Our researches focus on embedded machine learning, brain-inspired computing, reliability, and the internet of things (IoT). All related things to CADS-Lab, including news, publications, open-source tools, etc. are updated on this website, regularly.

CADS-Lab is located in the Department of Electrical and Computer Engineering, Tarbiat Modares University.

We are looking forward to hearing from you!

Notice (10/2023): Feel free to contact me for more info (o.akbari@modares.ac.ir).

  1. 2023/09: Congratulations to Mr. Morteza Yousefloo for successfully defending his M.Sc. thesis.
  2. 2023/09: Congratulations to Mr. Morteza Yousefloo for receiving the acceptance of funding support for his MSc thesis from the Iran Telecommunication Research Center (ITRC).
  3. 2023/09: Congratulations to Ms. Fariba Jorghanian for receiving the acceptance of funding support for her MSc thesis from the Iran Telecommunication Research Center (ITRC).
  4. 2022/10: Congratulations to Alireza Senobari for successfully defending his M.Sc. thesis.
  5. 2022/09: Congratulations to Fatemeh Hossein Khani for successfully defending her M.Sc. thesis.

  1. B. Vakili, O. Akbari, B. Ebrahimi, “Efficient Approximate Multipliers Utilizing Compact and Low-power Compressors for Error-Resilient Applications,” accepted in AEUE – International Journal of Electronics and Communications , Nov. 2023.
  2. A. A. Bahoo, O. Akbari, M. Shafique, “An Energy-Efficient Generic Accuracy Configurable Multiplier Based on Block-Level Voltage Overscaling,” accepted in IEEE Transactions on Emerging Topics in Computing (Q1, IF=6.595) , May. 2023.
  3. J. Vafaei, O. Akbari, M. Shafique, Ch. Hochberger, “X-Rel: Energy-Efficient and Low-Overhead Approximate Reliability Framework for Error-Tolerant Applications Deployed in Critical Systems,” in IEEE Transactions on Very Large Scale Integration Systems , vol. 31, no. 7, pp. 1051-1064, July 2023.
  4. M. Ghanatabadi, B. Ebrahimi and O. Akbari, “Accurate and Compact Approximate 4:2 Compressors with GDI Structure,” in Circuits, Systems, and Signal Processing (CSSP) , vol. 42, pp. 4148–4169, 2023.
  5. A. Khaksari, O. Akbari and B. Ebrahimi, “BEAD: Bounded Error Approximate Adder with Carry and Sum Speculations,” in Integration, the VLSI journal , vol. 88, pp. 353-361, 2023.
  6. F. Ebrahimi-Azandaryani, O. Akbari, M. Kamal, A. Afzali-Kusha and M. Pedram, “Accuracy Configurable Adders with Negligible Delay Overhead in Exact Operating Mode,” in ACM Transactions on Design Automation of Electronic Systems (TODAES) , july. 2022. https://doi.org/10.1145/3549936

  • Embedded machine learning
  • Internet of things
  • Hardware Security
  • Brain-inspired computing
  • Machine learning for reliability and safety-critical systems
  • Energy and security in smart buildings
  • Robust and energy-efficient system design
  • Hardware implementation of advanced neural networks on FPGA

  1. Professor Massoud Pedram, University of Southern California
  2. Professor Ali Afzali-Kusha, University of Tehran
  3. Professor Christian Hochberger, Technische Universität Darmstadt
  4. Professor Muhammad Shafique, New York University (NYU) Abu Dhabi
  5. Dr. Mehdi Kamal, University of Tehran
  6. Dr. Behzad Ebrahimi, Islamic Azad University Science and Research Branch