Kiumars Askari

Aerospace Freelancer at ENVISA
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Contact Information
us****@****om
(386) 825-5501
Location
Milan, Lombardy, Italy, IT

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Credentials

  • C for Everyone: Structured Programming (with Honors)
    Coursera
    Jan, 2022
    - Sep, 2024
  • C for Everyone: Programming Fundamentals
    Coursera
    Dec, 2021
    - Sep, 2024
  • Deep Learning Specialization
    DeepLearning.AI
    Oct, 2021
    - Sep, 2024
  • Introduction to Programming with MATLAB
    Coursera
    Oct, 2021
    - Sep, 2024
  • Python 3 Programming Specialization
    University of Michigan
    Oct, 2021
    - Sep, 2024

Experience

  • ENVISA
    • France
    • Environmental Services
    • 1 - 100 Employee
    • Aerospace Freelancer
      • Apr 2023 - Present

      Python DevelopmentFlight SimulationDeep Learning

    • Project Intern
      • Mar 2022 - Mar 2023

      Flight Simulator TestingPython ProgrammingDeep Learning

  • Self-employed
    • Real Estate
    • 1 - 100 Employee
    • Object Detection for Autonomus Driving Application
      • Oct 2021 - Oct 2021

      Using YOLO algorithm in python, the trained network recognizes cars in the picture.

    • Art Generation with Neural Style Transfer
      • Sep 2021 - Sep 2021

      Given a desired style picture and a base picture, the convolutional neural network changes the style of the base picture to further match the desired style.

    • Sudoku Solver Software Development with Python
      • Aug 2021 - Sep 2021

      You can download the software here for free:https://lnkd.in/e5Fxvpd9

  • Politecnico di Milano
    • Italy
    • Research Services
    • 700 & Above Employee
    • LEO Satellite Attitude Control in Simulink
      • Jun 2021 - Jul 2021

      Using sun sensor, Horizon sensor and magnetic sensor simulations, reaction wheels and magnetometers. Gyro and sensor noise were modeled and Earth pointing with 1 degree accuracy was achieved. Using sun sensor, Horizon sensor and magnetic sensor simulations, reaction wheels and magnetometers. Gyro and sensor noise were modeled and Earth pointing with 1 degree accuracy was achieved.

    • Lunar-Lander Agent Training in Python
      • Jan 2021 - Feb 2021

      Using Deep Q Learning, an agent was trained in python to solve the lunar lander problem in the gym environment, Using Deep Q Learning, an agent was trained in python to solve the lunar lander problem in the gym environment,

    • Interplanetary Trajectory Design
      • Oct 2020 - Dec 2020

      Matlab was used to find the best trajectory for a transfer between Venus and Jupiter with a powered gravity assist from Mars. Genetics algorithm was used in MATLAB. Matlab was used to find the best trajectory for a transfer between Venus and Jupiter with a powered gravity assist from Mars. Genetics algorithm was used in MATLAB.

Education

  • Amirkabir University of Technology - Tehran Polytechnic
    Bachelor's degree, Aerospace Engineering
    2011 - 2015
  • Politecnico di Milano
    Master's degree, Space Engineering
    2020 - 2022

Community

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