Dr. Siavash Fakhimi Derakhshan, Ph.D.

Research associate

Siavash Fakhimi Derakhshan
Research interests: Optimization, Machine learning, Lazy Learning, Fully probabilistic decision making, Fuzzy systems and control, multiple model control, nonlinear predictive control, and robust control

Biography

Publication list

Education

  • Ph.D. in Electrical Engineering – Control, Department of Electrical Engineering, K.N. Toosi University of Technology, Tehran, Iran

    • Thesis: “Reduce the conservatism in stability analysis for Takagi-Sugeno fuzzy systems”, July 2012

    • Supervisor: Dr. A. Fatehi

  • M.Sc. in Electrical Engineering – Control, Department of Electrical Engineering, K.N. Toosi University of Technology, Tehran, Iran

    • Thesis: “Identification and Robust Controller Design for the Servo-Hydraulic Robot Shoulder”, July 2005

    • Supervisor: Dr. H. Taghirad

  • B.Sc. in Electrical Engineering – Control, Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran

    • Thesis: “Controller Design for Airplane with Inertial Cross Coupling in Frequency Domain”, September 2003

    • Supervisor: Dr. M. Mobed

  • High School: Shahid Madani (under the supervision of NODET – National Organization for Developing Exceptional Talents), Tabriz, Iran

Professional Experience

  • Research Assistant, February 2017 – Present
    Institute of Information Theory and Automation of the Czech Academy of Sciences, Department of Adaptive Systems, Prague, Czech Republic

    • Research in topics related to optimization, lazy learning, and fully probabilistic decision making

  • Researcher and Programmer, May 2006 – December 2016
    K.N. Toosi University of Technology, Advanced Process Automation & Control Research Group, Tehran, Iran

    • Worked on universal controller systems, advanced control methods in oil refineries, and stability analysis and stabilization of Takagi-Sugeno fuzzy systems

  • Lecturer

    • Shahid Rajaee Teacher Training University, Tehran, Iran (October 2012 – July 2014)

      Courses taught: Industrial Control, System Identification, Modern Control Theory

    • University of Applied Science and Technology, Tehran, Iran (October 2009 – July 2015)

      Courses taught: Linear Control Systems, Digital Control Systems, Modern Control Theory, Robotics, Industrial Control, Intelligent Systems

Fields of Interest

  • Lazy learning

  • Fully probabilistic decision making

  • Robust control

  • Fuzzy sets and systems

  • Optimization

Journal articles

  1. Fakhimi Derakhshan Siavash, Shamsabad Farahani S. S.: Nonmonotonic‑Based Congestion Control Schemes for a Delayed Nonlinear Network, Circuits Systems and Signal Processing 39 1 (2020), p. 154-174 Download Download DOI: 10.1007/s00034-019-01187-x [2020]
  2. Fakhimi Derakhshan Siavash, Shamsabad Farahani S. S.: LMI-based Congestion Control Algorithms for a Delayed Network, International Journal of Industrial Electronics, Control and Optimization (IECO) 2 2 (2019), p. 91-98 Download Download DOI: 10.22111/ieco.2018.24948.1038 [2019]
  3. Behzadimanesh S., Fatehi A., Fakhimi Derakhshan Siavash: Optimal fuzzy controller based on non-monotonic Lyapunov function with a case study on laboratory helicopter, International Journal of Systems Science 50 3 (2019), p. 652-667 Download Download DOI: 10.1080/00207721.2019.1567864 [2019]
  4. Shamsabad Farahani S. S., Fakhimi Derakhshan Siavash: Comments on ‘‘Stability, l2-Gain, and Robust H∞ Control for Switched Systems via N-Step-Ahead Lyapunov Function Approach’’, IEEE Access 7 1 (2019), p. 2396-2400 Download Download DOI: 10.1109/ACCESS.2018.2886231 [2019]

Other publications

  1. Fakhimi Derakhshan Siavash, Guy Tatiana Valentine: Policy Learning via Fully Probabilistic Design, DYNALIFE WG1-WG2 Interaction Meeting Data driven evidence: theoretical models and complex biological data, p. 52-52 Download [2024]
  2. Guy Tatiana Valentine, Fakhimi Derakhshan Siavash, Štěch Jakub: Lazy Fully Probabilistic Design: Application Potential, Multi-Agent Systems and Agreement Technologies, p. 281-291 Download DOI: 10.1007/978-3-030-01713-2_20 [2018]