masoud masoumi moghadam

Dedicated graduated student in the field of computer science. Successful completion of advanced academic projects demonstrating engineering support capability. Aiming to improve and use my knowledge in data science, Big data, Backend engineering, computer vision, natural language processing in order to support senior managers and upper management in decision making for company.

Education

Master Computer Science

Branch Information technology

Institute/University: Urmia University if Technology

Bachelor Computer Science

Branch Information technology

Institute/University: Payam Noor University

Skills

machine learning

60%

data science

80%

Pytorch

100%

tensorflow

80%

deep learning

80%

pandas

100%

django rest framework

60%

opencv

80%

Linux

80%

sql

100%

rest api

80%

Git

100%

pycharm

100%

Work Experiences

computer vision expert

Company: Part software group

Back-end developer

Company: Negin Rayaneh Almas Khorasan

Data analyst

Company: Rajman

Languages

Persian

Reading Level

100%

Writing Level

100%

Speaking Level

100%

Listening Level

100%

English

Reading Level

100%

Writing Level

100%

Speaking Level

100%

Listening Level

100%

Turkish

Reading Level

60%

Writing Level

40%

Speaking Level

80%

Listening Level

80%

Projects

Title Project: Monte Carlo Tree Search master player in the game of HEX

Description: A General Game Player (GGP) designed engine which supports game of HEX right now. It uses reinforcement learning algorithm namely as Monte carlo tree search along with plenty of simulation strategies for improving search algorithm.

Title Project: CNN-based autonomous driver for the speed dreams game

Description: An autonomous driver for the game of speed dreams. In this project desktop screenshots are appended to keyboard keys and collected as data. The data is fed to a reception v3-type CNN and after training, CNN learned how to keep a driving car between road lines

Title Project: Genetic algorithm optimizer of trip travel

Description: The project splits in 2 parts. In first part initially we use data analysis and feature extraction for dataset. After that we define the best model that can use extracted features to predict the travel time with least possible error. In the second part we use genetic algorithm to find the path between random locations in test data which has the minimum distance.

Title Project: REST API contact-list manager project using django with docker

Description: This is a simple project to implement a restful api which can Retrive/Add/Remove/Modify contacts. We using MVC design pattern and Test-Driven-Development methodology.

Title Project: Neural Network designed for Kaggle glass classification method

Description: An analysis of kaggle glass dataset as well as building a neural network. In this work Neural Network is built with considering optimized parameters using hyperopt and hyperas libraries. We also investigated the impact of using NearMiss and Imblearn methods for undersampling and Oversampling dataset.

Title Project: Neshan application

Description: Neshan application is a unique iranian Intelligent Transportation System application which extract and estimate traffic and transportation data,and provides services like ITS and LBS to end-users. I was working with Rajman information structures to provide traffic data analysis services based on Urban ITS detectors/sensors.

Title Project: DigikalaNext comment summerizer

Description: It's a step by step tutorial for students who wants to build models for NLP. It includes wrangling data, creating word2vec model, and implementing various models for comparison.

Title Project: Pedestrian detection and tracking for surveillance system using pytorch

Description: In R&D process, this project was defined by senior manager to be used for both video surveillance and autonomous driving system. After researching through papers, github codes and other references, initial system were designed by using state-of-the-art Deepsort algorithm which is really fast and accurate.

Title Project: Face detection and recognition system for video surveillance cameras using RetinaNet

Description: A basic model for video surveillance system which makes use of RetinaNet algorithm for finding face landmarks. The code could be run on both gpu and cpu which is a cool feature of Pytorch library.

Title Project: Road lane-line segmenter for autonomous driving system using LaneNet and SCNN

Description: The role of lane detection system is really critical in autonomous driving system. 2 top algorithms for lane-line detection and segmentation are LaneNet and SCNN. we implemented initial version of both algorithms in our company.

Certificates

Advanced Image Processing with Python Track

Institute: https://www.datacamp.com/statement-of-accomplishment/track/5b98fb1fbc2a3ef9e089b8e6b6c3f967a0a0c7c7

Biomedical Image Analysis in Python

Institute: https://www.datacamp.com/statement-of-accomplishment/course/866d38aad02769ef389f93cd2467f7523ef33ce5

Data Manipulation with Python Track

Institute: https://www.datacamp.com/statement-of-accomplishment/track/07d93a6cde092eafa6b386431b2f5333c6f03306

Image Processing with Keras in Python

Institute: https://www.datacamp.com/statement-of-accomplishment/course/f62035d2a1599bc1bc46c4a95b7565be5fddd9a5

Introduction to Deep Learning with PyTorch

Institute: https://www.datacamp.com/statement-of-accomplishment/course/273e9233827221ec654fbf324d24424b2a7584ff

Machine Learning with Python

Institute: https://courses.cognitiveclass.ai/certificates/70c9c93d92034e63bb39e44986913247

Complete Machine Learning Course

Institute: https://www.udemy.com/certificate/UC-cd073dc1-129e-449c-8632-c362dda0239a/

Coding Best Practices with Python Track

Institute: https://www.datacamp.com/statement-of-accomplishment/track/f44977d2e3104e4b2a0e22bbd3f7b0880909d36c

Researches

Paper: IMPROVING MONTE CARLO TREE SEARCH BY COMBINING RAVE AND QUALITY-BASED REWARDS ALGORITHMS

Description: Enhancing the quality of simulations in Monte carlo tree search using quality-based rewards and considering simulation depth as a quality metric.

Other: An approach to Create a logging mechanism for real-time object detection using TDD

Publisher: Medium

Description: In this article, I explained how I managed to build a module for logging the detections in real-time application. I managed to cover concepts of software development, unit-testing (TDD) and making use of that in Machine learning applications.

Contact