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black0017/README.md

Why statement

I believe in/that:

  • sharing AI research experiences with blogs & open-source.
  • engineering is the big bottleneck of deep learning.
  • creating useful human-centered AI solutions.

Who am I?

I tend to love minimalism, simplicity and honesty. In sociatey terms, I am an Electrical and Biomedical Engineer (MEng + MSc) that is interested in the development of human-centered AI.

Research Interests

My AI research interests include 3D medical imaging, image and video analysis, graph-based deep learning models, and generative deep learning.

Publications:

  1. Multi-view adaptive graph convolutions for graph classification, Adaloglou et al. accepted at ECCV 2020

  2. A Comprehensive Study on Sign Language Recognition Methods, Adaloglou et al. accepted at IEEE Transactions on Multimedia Journal (shared first authorship)

  3. Self-Supervised Anomaly Detection by Self-Distillation and Negative Sampling, Under review

Core projects

  • Co-creator of the first ever interactive and 100% text-based deep learning course
  • Creator of the MedicalZoo, a PyTorch library that provides out of the box state of the art 3D segmentation models
  • AI science writer and co-founder at AI Summer
  • Author of the GAN in Computer Vision free ebook.
  • Responsible for the creation of the first large-scale RGB+D Greek sign language video dataset. arxiv link
  • Creator of self-attention-cv a python package (available via pip) with multiple self-attention modules for computer vision.

Github stats

black0017@'s top languages

Email remark

If you have an offer, opportunity, or introduction that might make my life more interesting, then definitely e-mail me at nikolas [at] theaisummer.com . I’ll only respond to those proposals that are a good match for my schedule and interests.

Pinned

  1. A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation

    Python 1k 216

  2. Implementation of various self-attention mechanisms focused on computer vision. Ongoing repository.

    Python 822 106

  3. Responsible implementation of 3D-GAN NIPS 2016 paper:Learning a Probabilistic Latent Space of ObjectShapes via 3D Generative-Adversarial Modeling,that can be found https://papers.nips.cc/paper/6096…

    Jupyter Notebook 80 14

  4. Introduction to medical image processing with Python: CT lung and vessel segmentation without labels https://theaisummer.com/medical-image-python/

    Jupyter Notebook 25 9

  5. Medical Deep Learning 2D high resolution image segmentation project: MICCAI 2019 Prostate Cancer segmentation challenge

    Python 13 7

  6. Fully connected Neural Network CUDA C Library. MEng Thesis implemented in 2016-2017 in pure C/CUDA 8.

    Cuda 2 1

397 contributions in the last year

May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Mon Wed Fri

Contribution activity

May 2022

Created 3 commits in 1 repository
13 contributions in private repositories May 4 – May 20

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