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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.
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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.
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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.
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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.
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![]() | Implemented a basic ray tracer for spheres and triangles with lighs, shading and reflection and antialiasing using distribution ray tracing. Developed using: C++ |
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![]() | Implemented a Smoothed Particle Hydrodynamics model on CUDA. Developed using: C++, CUDA |
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![]() | Long-term tracking of previously unknown objects in unconstrained environments. Developed using: C++, OpenCV |
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![]() | 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 |
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![]() | 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 |
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![]() | Trained three environments (Cart pole, Mountain car and Pendulum) from OpenAI Gym solving all environments in 3-5 generations trained in a few minutes on a GPU using a variant of Genetic Algorithms. Developed using: Python, OpenAi Gym, Neural networks, Genetic Algorithm Project report |
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![]() | 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 |
Published in Journal 1, 2009
This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1). http://academicpages.github.io/files/paper1.pdf
Published in Journal 1, 2010
This paper is about the number 2. The number 3 is left for future work.
Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2). http://academicpages.github.io/files/paper2.pdf
Published in Journal 1, 2015
This paper is about the number 3. The number 4 is left for future work.
Recommended citation: Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3). http://academicpages.github.io/files/paper3.pdf
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This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
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This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.