Career Profile
An Iranian curious student, widely known for his passion for learning and exploring new technologies. With a strong background in computer science and a keen interest in artificial intelligence, I am dedicated to expanding my knowledge and skills in the field. I am an active participant in online communities and enjoys sharing my insights and discoveries with others.
Education
- Highlighted Courses: Artificial Intelligence, Finite Element Analysis, Advanced Control Systems
- Thesis: explore Machine Learning models to refine Reconstructed ECT images (Electrical Capacitance Tomography)
- Thesis supported by Port & Maritime Organization of Iran
- Supervisor: Dr. Hossein Mousazadeh
- Advisors: Dr. Soleiman Hosseinpour and Dr. Hadi Karimi
- Highlighted Courses: Machanical Engineering Design, Maintenance Engineering, Computer Aided Design, Agricultural Machinery Design
- Projects:
- Design a mechanical scissor jack (Course: Mechanical Engineering Design)
- Design a basil harvesting machine (Course: Harvesting Machinary Design)
Experiences
Civilian National Service (Sarbazi Amrieh)
- Managed and maintained library IT systems, workstations, and networked devices
- Administered and updated institutional websites
- Provided technical support and troubleshooting for students and staff
- Created instructional materials (videos, slides, documentation, print guides)
- Conducted user orientation and introductory IT sessions
Conducted research in the field of Machine Learning to refine reconstructed Electrical Capacitance Tomography images.
- Developed and evaluated Machine Learning models for image refinement and noise reduction.
- Processed and analyzed ECT datasets using Python (Scikit-learn, Pandas, NumPy).
- Compared multiple Machine Learning algorithms to assess their advantages, limitations, and compatibility with ECT reconstruction methods.
- Studied tomography reconstruction techniques to enhance ECT imaging performance.
- Collaborated with academic supervisors and research team members on ML-based reconstruction pipeline development.
Assisted in the design and development of smart agricultural machinery systems, focusing on automation, embedded systems, and computer vision applications.
Supervised by Dr. Hossein Navid .
- Designed and implemented a computer vision–based pipe cutting system using Raspberry Pi to detect precise clipping points on PVC ducts by identifying flat surface regions for accurate cuts.
- Developed a lightweight, noise-adaptive vision system optimized for real-time performance and integration with high-speed industrial machinery.
- Built a wireless remote control system for a silage block cutting machine to improve operator safety and precision.
- Implemented full machine control via TCP/UDP local network communication using an Android application.
- Integrated control logic with pneumatic and hydraulic valve systems for precise actuation.
- Contributed to reducing operator injury risks and improving cutting accuracy through automation.
- Technologies & Tools: Python, Linux, Raspberry Pi, Arduino, C Programming, Electrical Circuit Design, Image Processing, TCP/UDP Networking
Certifications
You need to understand computers to work with them. This course extend my knowledge about computer a bit and it did not take me a long time. It was a good start point to continue taking CS50 bundle.
Build predictive models with scikit-learn and gain a practical understanding of the strengths and limitations of machine learning! (link to course)
After learning basics of Machine learning, now its time to hands-on experience and expand knowledge with practicing. The goal of this course is to teach machine learning with scikit-learn to beginners, even without a strong technical background.
Machine learning course taught by Prof. Andrew Ng, Associate professor at Stanford University.
I believe learning basics is the most important point of acquiring knowledge. This course tought me perfect ML basics alongside whatever I learnt from AI course by Dr. Mahmoud Omid in Univesity of Tehran. (There is a free Standford course in Youtube which is close to Coursera course but Youtube’s is a little harder and goes deeper in Mathematical details.)
Projects
Team projects lead to acquiring new knowledge while working on real projects lead to acquiring deeper knowledge. It's not all about knowledge, it's about personality, mentality and so on.
Collaborated with Ali Khalili .
Supervised by Dr. Hossein Navid .
Advised by Dr. Hadi Karimi .
Skills: Computer Vision, Raspberry Pi
Android application developed by Ali Khalili Based on React-native.
Supervised by Dr. Hossein Navid .
Advised by Dr. Hadi Karimi .
Skills: Arduino, Electrical Circuit Design, Adnroid Development
Team members: Anis Azarmikhah , Hadi Farahmand , Samira Komeili, Niloufar Rahimi.
Course: Design of Harvesting Machine
Team members: Anis Azarmikhah , Hadi Farahmand , Samira Komeili, Niloufar Rahimi.
Course: Mechanical Enginnering Design
OSS Contributions
Some of my contribution to Open Source projects.