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@danielathome19

Daniel J. Szelogowski

danielathome19
Wisconsin

Hi! I'm Daniel, a high school computer science and music teacher and Ph.D. in Artificial Intelligence from Wisconsin.

I have done a lot of work as both a software engineer and researcher, and a lot of my research has focused on fields with very little prior research, such as signal processing and machine learning for classical music, data structures/algorithms, and optimized data visualization for web and mobile platforms.

I have been programming most of my life and recently completed a Master's in Computer Science (my thesis, FormNN, is publicly available on my profile along with all of my other major CS research).

I have completely self-funded all of my research, including paying for textbooks, electronic testing devices, and computer hardware. However, after completing the Ph.D., my goal is to start my own research lab to advance computer science and artificial intelligence.

As such, all sponsorship funds will be placed in a separate savings account specifically for purchasing research materials, publication fees for conference/journal papers and books, and saving up to start my own research lab. All support is extremely appreciated, as my income as a teacher is difficult to disperse between trying to save, pay bills, and pay for my financial aid and other materials for school.

My goal is to constantly work toward advancing computer science and AI, all research of which will always be publicly available on GitHub. I hope to develop collegiate-level curricula for online classes and textbooks for those who lack access or want to continue their education.

I also run a podcast (MECS - Research Today), which discusses recent, upcoming, and ongoing research in the fields of Music, Education, Computing/Technology, and the Sciences/Math.

You can learn more about me here!

@danielathome19

Any and all help is appreciated!

Featured work

  1. danielathome19/Choral-GTN

    Doctoral dissertation project - a hybrid Neural Network system and dataset for compositionally realistic choral music generation (Generative Transformer Network).

    Python 1
  2. danielathome19/Form-NN

    Master thesis project - a hybrid Neural Network-Decision Tree system and dataset for classical music form recognition and analysis.

    Python 8
  3. danielathome19/Sung-EmotioNN-Detector

    A convolutional neural network trained to classify emotions in singing voices.

    Python 1
  4. danielathome19/ProteiNN-Structure-Predictor

    A transformer network trained to predict end-to-end single sequence protein structure as a set of angles given amino acid sequences.

    Python 2
  5. danielathome19/OLAP-Cube-Visualizer

    This repository contains multiple variants of this project; the primary algorithm allows for data cube operations to be performed using lightweight functions with ease of usability to provide speed…

    C# 1
  6. danielathome19/Chunk-List

    A Chunk List is a new, concurrent, chunk-based data structure that is easily modifiable and allows for fast run-time operations.

    C# 5

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