🌌 Arman Asgharpoor Golroudbari
🎓 M.Sc. student of Space Engineering at the University of Tehran
🔧 Background in Avionics Engineering
🔭 Current Research Focus:
- Computer Vision | Vision-based Navigation
- Intelligent Estimation Theory
- Application for Robot Navigation
- State Estimation for Autonomous Vehicles
🔬 Researcher | 🚀 Space Enthusiast | 🧠 Deep Learning Enthusiast
I am Arman Asgharpoor Golroudbari, a researcher at Deep Space Initiatives. My passion lies in applying machine learning through interdisciplinary research encompassing flight dynamics, control theory, deep learning, and sensor fusion algorithms.
🌐 Research Collaborations:
I actively seek opportunities for academic research collaborations, aiming to foster interdisciplinary synergies and engage in innovative knowledge exchange. 🤝💡
🛰️ Research Highlights:
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Milky Way Program @ Deep Space Initiative: Contributed to space transportation system research, addressing pressing space-related issues.
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Oxford Machine Learning Summer School: Achieved top rank in the Health and Medicine OxML competition track, focusing on vision-based breast cancer detection.
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Fuzzy Logic Lab @ University of Tehran: Developed deep neural networks for visual odometry, enhancing accuracy and performance.
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Space Lab @ University of Tehran: Pioneered deep learning-based inertial odometry techniques, leveraging state-of-the-art datasets and optimization tools.
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Department of Aerospace Eng. @ University of Tehran: Explored the intriguing world of Quantum Computing and its applications in space.
🌍 Experience Beyond Research:
I believe in sharing knowledge and experiences:
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Mentor @ Space Generation Advisory Council: Providing personalized guidance and support to aspiring space enthusiasts.
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Martial Arts Instructor @ Iran Martial Arts Federation: Cultivating communication skills through teaching diverse students.
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Manager @ Arman Imen Passargad: Nurturing leadership and management skills in challenging work environments.
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Teaching Assistant @ University of Tehran: Imparting practical programming skills to graduate-level students.
