About me

I am a Computer Science graduate student under the supervision of Dr. Faisal Qureshi and a member of the Visual Computing Lab in the Faculty of Science at Ontario Tech University. My research is focused on cross-view human action recognition using unsupervised motion representation learning.

My research interests are: Computer Vision, Deep Learning, Image Processing, Deep Reinforcement Learning, Generative Models, Scene Understanding.

I also love the art of storytelling and work as an animation artist in my free time. Demo Reel

Select projects

Social distance tool with depth

Published:

Highlighting people in a crowd violating social distancing protocol using detection and depth. Using an unconstrained input video we can infer depth and detect people who are close together.

Developed using: Python, Pytorch, Detectron2, Faster-RCNN, OpenCV, monocular depth estimation
Github link

Twitter network analysis

Published:

Creates a network graph of all users involved in the dissemination of a query (keyword, hashtag, meme, etc.) and analyzes trends/connections between the users.

Developed using: Python, Tweepy (Twitter API), Ploty, Geopy and NetworkX
Project report

Concolic testing for deep neural networks

Published:

Made neural networks more robust to adversarial attacks and increased their neuron activation coverage resulting in more comprehensive testing on popular toy datasets MNIST, Fashion-MNIST and Cifar10.

Developed using: Python, Tensorflow, CNNs
Project report

TLD long-term tracking algorithm

Published:

Long-term tracking of previously unknown objects in unconstrained environments.

Developed using: C++, OpenCV

SPH Particle Simulation

Published:

Implemented a Smoothed Particle Hydrodynamics model on CUDA.

Developed using: C++, CUDA

Ray tracer

Published:

Implemented a basic ray tracer for spheres and triangles with lighs, shading and reflection and antialiasing using distribution ray tracing.

Developed using: C++