A highly innovative, hardworking individual who possess strong commitment to team environment dynamics with the ability to contribute expertise and follow leadership directives at appropriate times.

My main interests are Image Processing, Machine Learning, and in particular, the field of Deep Learning especially Convolutional Neural Networks. Using Big Data techniques to make it possible having large-scale intelligent applications.

I’m wildly enthusiastic about combining my knowledge in fields of Machine Learning and Computer Vision with my skills in software developing to produce intelligent applications.

Experienced in implementation of machine learning algorithms. Also in design, analysis and development of iOS applications, Java platform and .Net technology.

Research Interests

  • Deep Learning and Convolutional Neural Network

  • Computer Vision and Medical Image Processing

  • Pattern Recognition

  • Big Data techniques on Machine Learning Problems

  • Machine Learning Algorithms Enhancement

Current Study

Diagnosing Lung Disease using Convolutional Neural Network on HRCT Images. 

In Machine Vision and Medical Image Processing Lab. 

Prof. H. Abbrishami Moghaddam



Master of Science, Artificial Intelligence

Sep 2015 - Present
K.N.Toosi University of Technology

Relevant Coursework:

    •      Artificial Neural Network (GPA 4)
    •      Multi-agent Systems (GPA 4)
    •      Big Data and Hadoop (GPA 4)
    •      Digital Image Processing (Present)
    •      Evolutionary Computing (Present)
    •      Reinforcement Learning (Present)

Bachelor of Science, Computer Enginering

Sep 2011 - Aug 2015
K.N.Toosi University of Technology

Total GPA: 4

Relevant Coursework:

    •      Data Structures and Algorithms (GPA 4)
    •      Artificial Intelligence: Principles & Techniques (GPA 4)
    •      Operating Systems (GPA 4)
    •      Computer Architecture (GPA 4)
    •      Software Engineering: Principles & Techniques (GPA 4)
    •      Advanced Programming: Java (GPA 4)


High School Diploma in Mathematics and Physics

Sep 2007 - Aug 2011
Mofid High School

Total GPA: 4

Research Experience

Research Assistant

Finding patterns in HRCT images of lung disease. Building hight confident Convolution Neural Network to classify the diseases.

In Machine Vision and Medical Image Processing Lab. 

Prof. H. Abbrishami Moghaddam

Teaching Experience



Machine Learning

Sep 2015 - Jan 2016
Stanford University

Instructure: A/Proffessor Andrew Ng

 Grade: 96/100

Verifiable at:

Work History

Work History

iOS Developer

Oct 2015 - Present

Building all kind of iOS applications, from offline apps to social network app.

Software Engineer / Database Manager

Mar 2014 - Dec 2015
Iran Comprehensive Database of Construction Industry Co.

My responsibilities:

  • Design the comprehensive database of construction industry in Iran
  • Design and build Windows administrative application to manage the database from desktop
  • Design and build Windows client application with ability of search, license checking and auto update in both online and offline mode



Machine Learning

iOS Developing

Digital Image Processing

Artificial Neural Network

Big Data and Hadoop

Evolutionary Algorithms

Database Managment

Latest Projects

  • Implementation of Neural Network to Recognize MNIST Handwritten Digits

  • Design and Implementation of Plagiarism Detector Software

Undergraduate Final Project

Design and implementation of plagiarism detector software to detect and report plagiarism probability of a given document using Google Search Engine in C#.

  • Hoortash | Social Network App in iOS

As my capstone project in iOS and to show the world my abilities in development iOS apps, I developed a social network app called Hoortash.

There are some features of this app:

    1. Instantly updates Feeds whenever a user posts, likes or comments on a post.
    2. Cached image system to improve app performance.
    3.  2-way authentication, one-step Login / Sign Up and Facebook Authentication
    4.  Ability of leaving comment and like a post.
    5.  Ability of editing user profile
    6. ...

  • Building Recommender System based on Movie Ratings

From MovieLens 100k Dataset from GroupLens Research. This dataset consists of ratings on a scale of 1 to 5. The dataset has 943 users, and 1682 movies.

  • Anomaly Detection Application to Detect Anomalous Behavior in Server Computers

The features measure the throughput (mb/s) and latency (ms) of response of each server. Dataset consists of 307 examples.

  • Spam Filter using Support Vector Machine (SVM)

Implementation of a spam filter with Support Vector Machine (SVM) to classify spam (y=1) and non-spam(y=0) emails. The dataset is based on a a subset of the SpamAssassin Public Corpus, available at:

  • Image compression using K-Means Algorithm