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Pages

Salik Nadeem

Posts

Future Blog Post

less than 1 minute read

Published:

This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.

Blog Post number 4

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 3

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 2

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

portfolio

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++

SPH Particle Simulation

Published:

Implemented a Smoothed Particle Hydrodynamics model on CUDA.

Developed using: C++, CUDA

TLD long-term tracking algorithm

Published:

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

Developed using: C++, OpenCV

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

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

publications

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.