Mohammad Mushfequr Rahman

I am a student in Computer Science who is passionate about Mobile Application Development, Backend Development, and Machine Learning


Experience

Software Developer Coop

OPG

Contributed to existing javascript codebase and created and analysed complex SQL quries.

May 2019 - Present

Computer Vision Research Assistant

Vc Lab

Investigated machine learning and deep learning techniques to fulfill Computer Vision tasks such as crowd counting, Image Classification and Object Detection and tracking. Created custom machine learning models that reached 90% testing accuracy.

May 2019 - Present

Computer Lab Linux Support

Ontario Tech University

Debugged different Linux distributions using bash scripts and provided technical support to various stakeholders

September 2018 - April 2019

Software Engineer Intern

Bashundhara Group

Designed android applications using Java and Android SDK. Modified existing codebases such that they could track employess dynamically. Implemented and troubleshot web scraper APIs that were build in collaboration with senior engineers.

May 2018 - August 2018

Education

Ontario Tech University

Bachelor of Science
Computer Science - Data Science Specialization

GPA: 3.87

September 2017 - Present

North South University

Bachelor of Science
Computer Science and Engineering

GPA: 3.6

August 2015 - August 2017

Skills

Programming Languages
  • Python
  • C/C++
  • Java
  • Dart
  • Clojure
  • Javascript
Mobile Development
  • Android SDK
  • Flutter
  • Swift and Xcode (iOS)
Machine Learning
  • Sklearn
  • Pytorch
  • Keras
Web Development
  • Node Js
  • Vue JS
  • d3
  • HTML 5, CSS and Javascript
  • Pug
Databases
  • MongoDB
  • SQLite
  • MySQL
  • PostgreSQL

Projects

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Few Shot Image Classification

Character Classification on the Omniglot dataset which consists of over 900 symbols from over 50 languages. Used Few Shot learning techniques to reach over 90% accuracy from only one/five training images.

Code
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LoveL text Classification

A web application to classify your LoveL using an AI text classifier that was portotyped in python and runs on the browser with tensorflow js

Code
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World Happiness Analysis

An indepth analysis into the 2015 happiness dataset. We analysed key attributes about the data set and created custom random forest models that predicted the happiness score for different countries and reached 94.2% testing accuracy

Code
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Toronto Fire Visualization

A web application built using d3 and javascript that visualizes all the fire incidents in Toronto from 2014-2017

Code Live Demo
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Chats App

A custom chatting application inspired by whatapp built using Java. It has a custom backend server capable of handling multiple clients and a front end built using JavaFx and CSS.

Code
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Towards Real Time MOT

An experiment in running the Towards Real Time MOT paper to train on our custom dataset and evaluate application of the network in real life scenarios.

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News Detector

An android application that is capable of taking a picture and analyzing it to get the most relevant information and display related news articles and videos.

Code
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NoteTakR

NoteTakR is a crossplatform mobile application built using dart and flutter and has several unqiue features such as assignment tracking and custom voice to text recording.

Code
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Fifa 2018 Schedule

Fifa 2018 Schedule is a mobile application built using Java and Android SDK. It features a unqiue UI and a user authntification system with facebook integration.

Code

Resume