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, Tehran, Iran.

We are looking forward to hearing from you!

Notice (05/2024): At CADS-Lab, there is a Ph.D position for applicants who participated in the Sanjesh Ph.D entrance exam (1403/2024), in the computer engineering field. Contact me for more information (o.akbari@modares.ac.ir).

Recent News:

  1. 2024/10: Congratulations to Ms. Fariba Joorghanian for successfully defending her M.Sc. thesis.
  2. 2024/05: Congratulations to Mr. Reza Ghorbansiahi for receiving the acceptance of funding support for his MSc thesis from the Iran Telecommunication Research Center (ITRC).
  3. 2024/05: Congratulations to Mr. Alireza Fouladloo for receiving the acceptance of funding support for his MSc thesis from the Iran Telecommunication Research Center (ITRC).
  4. 2024/05: Congratulations to Ms. Farzaneh Abouali for receiving the acceptance of funding support for her MSc thesis from the Iran Telecommunication Research Center (ITRC).
  5. 2024/01: Congratulations to Mr. Amirhossein Azimi for successfully defending his M.Sc. thesis.

Recent Publications:

  1. J. Vafaei and O. Akbari “HPR-Mul: An Area and Energy-Efficient High-Precision Redundancy Multiplier by Approximate Computing,” accepted in IEEE Transactions on Very Large Scale Integration Systems , Aug. 2024.
  2. F. Hosseinkhani, O. Akbari, and M. Shafique “A Two-Level Thermal Cycling-aware Task Mapping Technique for Reliability Management in Manycore Systems,” accepted in IEEE Access , Aug. 2024.
  3. A. Azimi and O. Akbari, “A Deep Reinforcement Learning-Based Method for Dynamic Quality of Service aware Energy and Occupant Comfort Management in Intelligent Buildings,” accepted in e-Prime – Advances in Electrical Engineering, Electronics and Energy , July 2024.
  4. A. Senobari, J. Vafaee, O. Akbari, Ch. Hochberger, M. Shafique, “A Quality-Aware Voltage Overscaling Framework to Improve the Energy Efficiency and Lifetime of TPUs based on Statistical Error Modeling,” in IEEE Access , vol. 12, pp. 92181-92197, 2024.
  5. F. Joorghanian and O. Akbari, “Energy Management of Smart Buildings Using Graph Neural Network,” accepted in Tabriz Journal of Electrical Engineering (TJEE) , May. 2024.
  6. M. Yousefloo and O. Akbari, “Design Exploration of Fault-Tolerant Deep Neural Networks using Posit Number Representation System,” in IEEE Transactions on Very Large Scale Integration Systems , vol. 32, no. 7, pp. 1350-1363, July 2024.
  7. B. Vakili, O. Akbari, B. Ebrahimi, “Efficient Approximate Multipliers Utilizing Compact and Low-power Compressors for Error-Resilient Applications,” in AEUE – International Journal of Electronics and Communications, vol. 174, no. 155039, Jan. 2024.

Current Research Areas

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

Collaborations with other Universities:

  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