Who am I?
I have always had a profound passion and fascination for areas requiring an analytical approach. Ever since I was young, I have enjoyed dabbling with computers and experimenting with different applications. Because my own life has essentially coincided with the rise of the modern computing industry, I can sense that there are still tremendous developments to come in this field. Right from the early days at school, Mathematics has intrigued me. The most challenging of all problems were my favorites, and obtaining solutions to them would leave me with a sheer feeling of ecstasy. I always did and always would thrive on solving the most challenging problems. With a compelling desire to excel, hard work became my second nature
Head of FlowDeep project
FlowDeep is an AI tool that can recognize various flowers based on machine learning principles, I accomplished the following tasks:
- Network architecture: To design FlowDeep deep learning network, I used transfer learning method because there was not sufficient training data. Also, I employed VGG16 architecture to train the network model. In this project Tensorflow and Keras libraries were used.
- FlowDeep website and server: I designed FlowDeep website, also desined FlowDeep server via python language.
- Android Studio
Member of R&D in Cheetah project (flight simulator)
worked on the following tasks:
- Cheetah Main Software: A software to extract airplane game’s data such as airplane roll and pitch from RAM. It connects to the cheetah cabin board and sends extracted data every 100 ms through a serial port. I am a contributor to this project and designed UI and back-end via C# language to make it easy to use.
- Cheetah Wireless Application (an android application to control cabin wirelessly): This application can connect to the cabin board via Bluetooth and control the cabin. In addition, it is capable of rotating the cabin via 3-D videos, so that the application can play 3-D videos like roller-coaster. I’m the main and the only developer of this project and designed a live stream to send data fast.
Simulation of CNND paper (Transferred Deep Learning for Anomaly Detection in Hyperspectral Imagery):
- CNN-based detection (CNND):A novel anomaly detection framework with transferred deep convolutional neural network (CNN). The framework is designed by considering the following facts: 1) A reference data with labeled samples are utilized because no prior information is available about the image scene for anomaly detection. 2) Pixel pairs are generated to enlarge the sample size as the advantage of CNN can be realized only if the number of training samples is sufficient.
Startup Team Member (JIB project)
- Developing the android application for client and customer separately.
- Research on utilizing the best components to ensure the quality and determine the best market strategy for the market.
- Designing the server back-end and parts of the two applications; the development is based on the Java, where various Java packages like Kyronet are utilized to accomplish a fast and secure performance.
- Utilizing symmetric and public key encryptions to ensure the security of the app.
UAV robot team member worked on the following projects
- QR-Code Detector Application (a software to decode QR-codes and save the target image): It connects to the robot and receives captured images from its camera. Being placed on top of the robot, it is capable of detecting QR-codes. I developed this application in Python language and used a library called Z-bar to detect QR-codes fast.
- Robot flight controller PCB design: Robot flight controller is the main board of UAV robots that can sync the rotation of all motors using a PID controller.
- Altium Designer
Skills & Tools
Frameworks and libraries
Tensorflow and Keras
BSc. in Software EngineeringYazd University2016 - present
1st place2017 - Iran open international competition in UAV league
1st place2015 - SharifCup, UAV league, Sharif University of Technology
Excellence team2015 - Certificate of Excellence team in Amirkabir University of Technology UAV league
1st place2017 - Certificate of 1st place in Nooshiravani university of technology UAV league.
- Persian (Native)
- English IELTS Academic (Overall: 7 L(7.5) R(7.5) S(6.5) W(6.5))
- Arabic (Beginner)