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Muhammad Rehmoz S.

@DevRehmoz

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Aerospace Engineer | Game Developer | Programming

$35 USD / tunti
・
Maan lippu
Pakistan (10:04 ip.)
・
Liittyi kesäkuuta 2, 2023
$35 USD / tunti
・
I am an aerospace engineer with 5 years of work experience and can help you complete any sort of technical project. I am proficient in several programming languages and can assist you in bringing your ideas to life!
Vahvistukset
Freelancer Python Developers Pakistan
Katso kaikki Python Developers paikassa Pakistan

Portfolio

Portfolio

11070147
These are 10 video games I developed in a single month at the beginning of my unity career.
Game Development in Unity
11062682
This project showcases my expertise in aerospace engineering and orbital mechanics through simulating and analyzing the aerobraking maneuver of the Mars Climate Orbiter using STK (Systems Tool Kit). By accurately modeling the spacecraft's trajectory during aerobraking, considering atmospheric conditions and intricate dynamics, I provided valuable insights and recommendations for optimal parameters. This project demonstrates my proficiency in aerospace engineering and problem-solving abilities.
STK: Mars Climate Orbiter Aero-braking Simulation & Analysis
This project showcases my expertise in aerospace engineering and orbital mechanics through simulating and analyzing the aerobraking maneuver of the Mars Climate Orbiter using STK (Systems Tool Kit). By accurately modeling the spacecraft's trajectory during aerobraking, considering atmospheric conditions and intricate dynamics, I provided valuable insights and recommendations for optimal parameters. This project demonstrates my proficiency in aerospace engineering and problem-solving abilities.
STK: Mars Climate Orbiter Aero-braking Simulation & Analysis
This project showcases my expertise in aerospace engineering and orbital mechanics through simulating and analyzing the aerobraking maneuver of the Mars Climate Orbiter using STK (Systems Tool Kit). By accurately modeling the spacecraft's trajectory during aerobraking, considering atmospheric conditions and intricate dynamics, I provided valuable insights and recommendations for optimal parameters. This project demonstrates my proficiency in aerospace engineering and problem-solving abilities.
STK: Mars Climate Orbiter Aero-braking Simulation & Analysis
11062620
I tackled the Sokoban puzzle game using a model-free reinforcement learning (RL) approach. Sokoban requires strategic box movement to designated spots while avoiding obstacles. I employed Q-learning, an RL algorithm, to learn and update expected rewards for actions in different states. The success of my RL agent highlights the immense potential of RL in solving complex optimization problems. Through trial and error, the agent acquired problem-solving, path planning, and pattern recognition skills, without any prior knowledge of the game. This indicates RL's applicability in domains like planning, scheduling, and robotics.
Sokoban Solver: RL for Complex Optimization
I tackled the Sokoban puzzle game using a model-free reinforcement learning (RL) approach. Sokoban requires strategic box movement to designated spots while avoiding obstacles. I employed Q-learning, an RL algorithm, to learn and update expected rewards for actions in different states. The success of my RL agent highlights the immense potential of RL in solving complex optimization problems. Through trial and error, the agent acquired problem-solving, path planning, and pattern recognition skills, without any prior knowledge of the game. This indicates RL's applicability in domains like planning, scheduling, and robotics.
Sokoban Solver: RL for Complex Optimization
I tackled the Sokoban puzzle game using a model-free reinforcement learning (RL) approach. Sokoban requires strategic box movement to designated spots while avoiding obstacles. I employed Q-learning, an RL algorithm, to learn and update expected rewards for actions in different states. The success of my RL agent highlights the immense potential of RL in solving complex optimization problems. Through trial and error, the agent acquired problem-solving, path planning, and pattern recognition skills, without any prior knowledge of the game. This indicates RL's applicability in domains like planning, scheduling, and robotics.
Sokoban Solver: RL for Complex Optimization
I tackled the Sokoban puzzle game using a model-free reinforcement learning (RL) approach. Sokoban requires strategic box movement to designated spots while avoiding obstacles. I employed Q-learning, an RL algorithm, to learn and update expected rewards for actions in different states. The success of my RL agent highlights the immense potential of RL in solving complex optimization problems. Through trial and error, the agent acquired problem-solving, path planning, and pattern recognition skills, without any prior knowledge of the game. This indicates RL's applicability in domains like planning, scheduling, and robotics.
Sokoban Solver: RL for Complex Optimization
11070147
These are 10 video games I developed in a single month at the beginning of my unity career.
Game Development in Unity
11062682
This project showcases my expertise in aerospace engineering and orbital mechanics through simulating and analyzing the aerobraking maneuver of the Mars Climate Orbiter using STK (Systems Tool Kit). By accurately modeling the spacecraft's trajectory during aerobraking, considering atmospheric conditions and intricate dynamics, I provided valuable insights and recommendations for optimal parameters. This project demonstrates my proficiency in aerospace engineering and problem-solving abilities.
STK: Mars Climate Orbiter Aero-braking Simulation & Analysis
This project showcases my expertise in aerospace engineering and orbital mechanics through simulating and analyzing the aerobraking maneuver of the Mars Climate Orbiter using STK (Systems Tool Kit). By accurately modeling the spacecraft's trajectory during aerobraking, considering atmospheric conditions and intricate dynamics, I provided valuable insights and recommendations for optimal parameters. This project demonstrates my proficiency in aerospace engineering and problem-solving abilities.
STK: Mars Climate Orbiter Aero-braking Simulation & Analysis
This project showcases my expertise in aerospace engineering and orbital mechanics through simulating and analyzing the aerobraking maneuver of the Mars Climate Orbiter using STK (Systems Tool Kit). By accurately modeling the spacecraft's trajectory during aerobraking, considering atmospheric conditions and intricate dynamics, I provided valuable insights and recommendations for optimal parameters. This project demonstrates my proficiency in aerospace engineering and problem-solving abilities.
STK: Mars Climate Orbiter Aero-braking Simulation & Analysis
11062620
I tackled the Sokoban puzzle game using a model-free reinforcement learning (RL) approach. Sokoban requires strategic box movement to designated spots while avoiding obstacles. I employed Q-learning, an RL algorithm, to learn and update expected rewards for actions in different states. The success of my RL agent highlights the immense potential of RL in solving complex optimization problems. Through trial and error, the agent acquired problem-solving, path planning, and pattern recognition skills, without any prior knowledge of the game. This indicates RL's applicability in domains like planning, scheduling, and robotics.
Sokoban Solver: RL for Complex Optimization
I tackled the Sokoban puzzle game using a model-free reinforcement learning (RL) approach. Sokoban requires strategic box movement to designated spots while avoiding obstacles. I employed Q-learning, an RL algorithm, to learn and update expected rewards for actions in different states. The success of my RL agent highlights the immense potential of RL in solving complex optimization problems. Through trial and error, the agent acquired problem-solving, path planning, and pattern recognition skills, without any prior knowledge of the game. This indicates RL's applicability in domains like planning, scheduling, and robotics.
Sokoban Solver: RL for Complex Optimization
I tackled the Sokoban puzzle game using a model-free reinforcement learning (RL) approach. Sokoban requires strategic box movement to designated spots while avoiding obstacles. I employed Q-learning, an RL algorithm, to learn and update expected rewards for actions in different states. The success of my RL agent highlights the immense potential of RL in solving complex optimization problems. Through trial and error, the agent acquired problem-solving, path planning, and pattern recognition skills, without any prior knowledge of the game. This indicates RL's applicability in domains like planning, scheduling, and robotics.
Sokoban Solver: RL for Complex Optimization
I tackled the Sokoban puzzle game using a model-free reinforcement learning (RL) approach. Sokoban requires strategic box movement to designated spots while avoiding obstacles. I employed Q-learning, an RL algorithm, to learn and update expected rewards for actions in different states. The success of my RL agent highlights the immense potential of RL in solving complex optimization problems. Through trial and error, the agent acquired problem-solving, path planning, and pattern recognition skills, without any prior knowledge of the game. This indicates RL's applicability in domains like planning, scheduling, and robotics.
Sokoban Solver: RL for Complex Optimization
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Kokemus
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My startup deals in all kinds of aerospace, mechanical, electrical, avionics, and software engineering as well as AI, app, and game development projects.
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As an accomplished game developer with a passion for creating immersive gaming experiences, I specialize in developing captivating 2D and 3D games for Android and PC platforms. With a particular focus on flight simulators. Key Skills: Unity, C#, Lua, C++, Python
tammik., 2023 - Esittää
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1 , 11 kuukautta
Koulutus
Institute of Space Technology
2018 - 2022
•
4 vuotta
BS Aerospace Engineering
Maan lippu
Pakistan
2018 - 2022
•
4 vuotta
Pätevyydet
BS Aerospace Engineering
2018
Institute of Space Technology
Completed my bachelor's degree with an award-winning final year project!
2018
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