Dr. Siavash Fakhimi Derakhshan, Ph.D.

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