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


  • M. Yousefan, H. Esmaeili Najafabadi, H. Amirkhani, H. Leung and V. Hajihashemi. “Deep Anomaly Detection in Hyperspectral Images Based on Membership Maps and Object Area Filtering”. IEEE transactions on Geoscience and Remote sensing (Second Revision) (IF: 5.855, H-index: 236).
  • 2020
  • Hamid Esmaeili Najafabadi, Member, IEEE, Mahdi Yousefan, Member, IEEE, Amir Shayan Nasiri Majd. “Anomaly Detection Based on Sigmoid Metric and Object Area Filtering in Hyperspectral Images“. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (Under Revision).
  • 2020
  • Vahid Hajihashemi, Hamid Esmaeili Najafabadi, Abdorreza Alavi Gharahbagh, Henry Leung, Mahdi Yousefan, João Manuel R. S. Tavares. “Novel High-efficiency Holography Image Compression Method based on HEVC, Wavelet and Nearest-neighbor Interpolation”. Multimedia tools and application (Submitted).
  • 2020
  • Vahid Hajihashemi, Hamid Esmaeili Najafabadi, Abdorreza Alavi Gharahbagh, Henry Leung, Mahdi Yousefan, João Manuel R. S. Tavares. “Novel High-efficiency Holography Image Compression Method based on HEVC, Wavelet and Nearest-neighbor Interpolation”. Visual Communication and Image Representation (To be submitted).
  • 2020
  • M. Yousefan, H. Esmaeili Najafabadi, H.Amirkhani, H.Leung and V.Hajihashemi. “Supplementary material for deep anomaly detection in hyperspectral images based on membership maps and object area filtering”. 2020. (Technical Report)
  • 2020
  • M. Yousefan. “Privacy-Preserving Health Data Science Using Federated Learning, K-best Clients Selection and Deep Compression”. 2020. (In Progress)
  • Work Experience

    Head of FlowDeep project

    2019 - Present

    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.

    Technologies used:

    • Keras
    • Tensorflow
    • JavaScript
    • Android Studio
    • HTML/CSS
    • MySQL

    Member of R&D in Cheetah project (flight simulator)

    2018 - 2019

    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.

    Technologies used:

    • C#
    • Java

    Simulation of CNND paper (Transferred Deep Learning for Anomaly Detection in Hyperspectral Imagery):

    To-do Lists
    • 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.

    Technologies used:

    • Tensorflow
    • Keras
    • Python

    Startup Team Member (JIB project)

    Iran - Isfahan
    • 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.

    Technologies used:

    • Java
    • KryoNet

    UAV robot team member worked on the following projects

    Iran - Isfahan
    • 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.

    Technologies used:

    • Python
    • OpenCV
    • Altium Designer

    Skills & Tools

    Frameworks and libraries

    • Tensorflow and Keras
    • Open CV
    • BootStrap
    • MaterializeCSS
    • Socket.io

    Programming Languages

    • Python
    • Java
    • PHP
    • SQL
    • C#

    Web Dev

    • HTML
    • CSS
    • JavaScript
    • jQuery


    • Matlab
    • Latex
    • Git


    • BSc. in Software Engineering
      Yazd University
      2016 - present


    • 1st place
      2017 - Iran open international competition in UAV league
    • 1st place
      2015 - SharifCup, UAV league, Sharif University of Technology
    • Excellence team
      2015 - Certificate of Excellence team in Amirkabir University of Technology UAV league
    • 1st place
      2017 - 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)


    • Soccer
    • Ping-Pong
    • Swimming