CV
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Contact Information
| Name | Alireza Dehghanzadeh |
| Professional Title | Graduate Student |
| dehghanzadeh98@gmail.com |
Professional Summary
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.
Experience
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2024/06 - 2026/04 Karaj, Alborz, Iran
IT Support & Systems Administrator (Library Services)
University of Tehran, Central Library of College of Agriculture and Natural Resources
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
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2021/10 - 2023/09 Karaj, Alborz, Iran
Researcher Assistant
University of Tehran
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.
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2019/03 - 2021/04 Tabriz, East Azerbaijan, Iran
Research Assistant – Automation & Computer Vision
Tabriz University, Precision Agriculture group
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 . Advised by Dr. Hadi Karimi .- 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
Education
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2020/10 - 2023/09 Tehran, Iran
Master's degree
University of Tehran
Biosystems Engineering
- Relevant Coursework: 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
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2016/09 - 2020/09 Tehran, Iran
Bachelor's degree
Tabriz University
Biosystems Engineering
- Relevant Coursework: Machanical Engineering Design, Maintenance Engineering, Computer Aided Design, Agricultural Machinery Design
- Project: Design a mechanical scissor jack (Course: Mechanical Engineering Design)
- Project: Design a basil harvesting machine (Course: Harvesting Machinary Design)
Skills
Languages
Interests
Certificates
- CS50 Understanding Technology - Harvard University (2023)
- Machine learning in Python with scikit-learn - France Université Numérique (2023)
- Machine Learning - Stanford University by Andrew Ng (2022)
Projects
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PVC Duct Cutting Machine Computer Vision System
This project used computer vision technology to identify clipping points within PVC ducts, focusing on detecting their flat areas for accurate cuts. Adaptable to ambient noise, the system ensured consistent performance, while its lightweight design enabled seamless integration with the machine’s high-speed operations. Utilizing a Raspberry Pi, this compact yet powerful computing platform was used to drive the entire system.
- Collaborated with Ali Khalili
- Supervised by Dr. Hossein Navid
- Advised by Dr. Hadi Karimi
- Skills: Computer Vision, Raspberry Pi
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Remote Controller for a Silage Block Cutting Machine
Due to operator injuries, while cutting stacked up silage blocks, a remote controlling system was developed and configured so that the operators be able to control the machine using wireless technology. The device was able to fully control the machine. The developed device controlled the system by manipulating the pneumatic and hydraulic valves of the machine using a TCP/UDP local network with an android application. Which in fact, the machine performs with more precision and offers product and safety measures. Android application developed by Eng. Ali Khalili Based on React-native.
- Collaborated with Ali Khalili
- Supervised by Dr. Hossein Navid
- Advised by Dr. Hadi Karimi
- Skills: Arduino, Electrical Circuit Design, Adnroid Development
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Basil Harvester
Design a machine to harvest basils as a successor to Scissor Jack since we got the best resualts and distinguished among other groups in related class. There are a large number of small agriculture farms around mid-to-big cities in Iran which they plant different basils alongside eachother in several section in their farms. This project aimed this businesses to help them increasing outcome and decreasing wastes. This machine was design by intelligence functionality in mind and using previous works and experiences.
- Team members: Anis Azarmikhah , Hadi Farahmand , Samira Komeili, Niloufar Rahimi
- Course: Design of Harvesting Machine
- Supervisor: Dr. Hossein Navid
- Skills: Team work, SolidWorks, Mechanical Engineering Design
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Scissor Jack
Apply Mechanical Engineering Design knowledge to Design a scissor jack as a course project. Design was done using Solidworks and the analysis which was additional, done through Ansys Mechanical.
- Team members: Anis Azarmikhah , Hadi Farahmand , Samira Komeili, Niloufar Rahimi
- Course: Mechanical Enginnering Design
- Supervisor: Dr. Hossein Navid
- Skills: Team work, SolidWorks, Mechanical Engineering Design