About me
Hello. My name is Nikola Janjušević. I am a third year PhD candidate in Electrical Engineering at New York University under the advisory of Professor Yao Wang, NYU VideoLab. I received my Bachelors in Electrical Engineering from The Cooper Union for Advancement of Science and Art in 2019.
My current interests are in interpretable deep-learning models for linear inverse-problems and low-level computer-vision/image-processing tasks. My background is in signal-processing and non-smooth, convex optimization. Outside of academia, I go skateboarding with my friends 🛹.
Updates
May 2022:
"Gabor is Enough" accepted into IVMSP 2022.
CDLNet + GDLNet PyTorch code publicly available here
April 2022:
"CDLNet: Noise-Adaptive Convolutional Dictionary Learning Network for Blind Denoising and Demosaicing" accepted in IEEE Open Journal of Signal Processing!
Preprint, "Gabor is Enough: Interpretable Deep Denoising with a Gabor Synthesis Dictionary Prior".
Recent blog posts
Welcome to an attempt at simultaneous learning, where I learn to separate skills (Julia programming and TV denoising) without prior knowledge of either! Starring Fabio, and Masa. 
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Zathura + latexmk -> :). Latest update: 17th January 2021. ...
I often find my downloads folder filling up with tons of research papers with nondescript (ID) names, such as "1909.05742.pdf". Keeping these PDFs open allows me to keep track of them, but once I close those windows they seem as good as lost. To remedy this, I've written a short Python script employing a wrapper for the arXiv.org API. ...
The iterative soft thresholding algorithm is one of the simplest algorithms for sparse coding (in this case, solving the basis-pursuit denoising functional). Understanding its derivation as a special case of the Proximal Gradient Method is a great introduction into the world of proximal methods. ...