About me

  • Current View on Life: Work hard, Play Harder.
  • Favourite Movie Quote: Enjoy the little things - Rule #32, Zombieland
  • Currently Learning: Intricacies of Computer Vision
  • Last Book I read: 3 a.m. by Nicholas Pirog (Still reading, haven't finished)
  • Last Show I watched: October Faction on Netflix(I know, I have bad taste)
  • Last Movie I watched: You Don't Mess with the Zohan
  • Last Anime I watched: The Disastrous Life of Saiki K
  • Currently Playing: Neverwinter, Cs:GO, Witcher 3, Sekiro: Shadows die twice
  • Current favourite song: Neffex- Let me down

I Enjoy

Work Experience

  • Work Experience

  • Gratuate Teaching Assistant

    University of Alberta

    Since September 2019.

  • Jr. Software Engineer

    Astha IT Research & Consultancy Ltd.

    Since September 2017.

  • Software Engineer


    June 2017 - August 2017

  • Software Engineer


    May 2017 - June 2017

  • Student Tutor

    BRAC University

    January 2015 - December 2016

  • Education

  • Master of Science in Computing Science

    University of Alberta - 2019 - Ongoning
  • Bachelor of Science in Computer Science and Engineering(CSE)

    BRAC University - 2013 - 2016

    Graduated With High Distinction

    Recipient of Merit Based Scholarship

    Placed on Dean's List

    Placed on Vice Chancellor's List

  • Higher Secondary Certificate(HSC)

    Notre Dame College - 2012 - 2016

  • Secondary School Certificate(SSC)

    Savar Cantonment Public School and College - - 2010

    Recipient of Government Scholarship on 2004, 2008 and 2010

  • Publications

  • Abnormal event detection in crowded scenarios
    Tahjid Ashfaque Mostafa, Jia Uddin, Md. Haider Ali

    View in IEEE XPlore

    This paper proposes an autonomous video surveillance system which analyzes footages of extremely crowded scenes and detects abnormal events in the context of that particular scene. The model analyzes the local spatial-temporal motion pattern and detects abnormal motion variations and sudden changes and it can be divided into two major parts, selecting a set of Points of Interest (POI) from given frames and tracking them across multiple frames and dividing the input video frame in a number of cubes and track the motion patterns in each of the cubes for spatial-temporal statistical deviations. To evaluate the performance of proposed model we utilize several datasets and compare the acquired results of the proposed model with various state-of-the art models. Experimental results demonstrate that the proposed model outperforms the other models by exhibiting an average of 96.12% accuracy using Convolutional Neural Network.

What I do

  • Web Development

    Web Development

  • Responsive UX/UI Development

    Responsive UX/UI Development

  • Computer Vision/Image Processing

    Computer Vision/Image Processing

  • Machine Learning/ Deep Learning

    Machine Learning/ Deep Learning

  • Software Development

    Software Development

  • Database Management

    Database Management

Skills (Professional)


CodeIgniter 70%

ASP.Net Web API 85%

Laravel 50%

jQuery 85%

AngularJS 80%

Java Swing 65%

JOGL 60%

Arduino 70%

LINQ 85%

Vue JS 50%

RSpec 30%

Dapper 85%


Jasmine 40%

Web Sockets(SignalR, Fleck in C#, Socket in Python, Java) 70%

Bootstrap 90%

OpenCV 85%

Theano 75%

Tensorflow 75%

Pytorch 75%

Keras 75%

ScikitLearn 75%

Hybrid App Developer(Android+IOS)(React Native) 40%

LINUX Systems 80%


Entity Framework 85%


Some other things

  1. Volunteering and Organizing experience
    • Worked as a volunteer to raise money for relief materials during the tragic Rana Plaza Collapse of 2013 in Bangladesh, coordinated with hospital authorities and played active role in purchase and delivery of medicine and other supllies to appropriate authorities.
    • Worked as a volunteer for Prothom Alo Bondhusovha in organizing and coordinating various events and festivals.
    • Worked as a volunteer in various school and college functions
  2. Languages I speak three languages, Bangla, Hindi and English. Hoping to learn Japanese and French in the future