shahin darvishpoor

About

I am a Ph.D student in mechanical engineering at University of British Columbia. I hold a master’s degree in flight dynamics and control. My major field of study is control and dynamic systems. I have been working on applications of artificial intelligence and machine learning in control systems and now I have focused on data-driven approaches. My other interests are machine vision, nature-inspired engineering, bio-inspired algorithms and aerospace systems of course.

 

Work Experiences

  • Present2019

    Head of Department

    Space Systems Design Institute

  • 20192017

    Assistant Researcher

    Space Systems Design Institute

Education & Training

  • Ph.D Present

    PhD in Mechanical Engineering

    University of British Columbia

  • M.S. 2020

    MSc in Aerospace Engineering, Flight Dynamics and Control

    K.N. Toosi University of Technology

  • B.S. 2017

    BS in Aerospace Engineering

    K.N. Toosi University of Technology

  • H.S.D. 2013

    High School Diploma in Mathematics and Physics

    National Organization for Development of Exceptional Talents (Sampad)

News

Best Thesis of The Year Award

I am pleased to announce that my master’s thesis titled “Control Design and Stability Proof of a Moving Mass Controlled

Outstanding Student Award

I am pleased to announce that I have been selected a the Outstanding Master’s student of the K. N. Toosi

Best Researcher Award of KNTU

I am pleased to announce that I have been selected as the Best Researcher of the K. N. Toosi University

Blog

Nature-inspired algorithms and Aerospace

This week my latest paper “Nature-Inspired Algorithms from Oceans to Space: A Comprehensive Review of Heuristic and Meta-Heuristic Optimization Algorithms

A quick start with LaTeX for academic purposes

Painful Word! If you have ever worked on a large publication in Microsoft Word, you may have experienced the pain

NIA, Nature-Inspired Optimization Python Package

Nature-inspired optimization is a very popular subject in engineering, terms heuristic algorithms or metaheuristic algorithms are also common to refer