About Me

Summary

Hello

! I'm David, a master student in machine learning at ÉTS and a software engineer bachelor.

My focus and ambitions in the field of ML is to make models more efficient in terms of data needed and training time necessary for the model to converge to a solution.

Following that axis, my thesis revolves around reducing the Transformer’s inference time during training. To achieve this, I am building a stochastic method to reduce the Self-Attention complexity.

While doing that I have developed an array of research and engineering skills related the science (which sometimes feels like an art) of machine learning. You'll see more on that in the Skills section below.

I'm not one-dimensional

Although I have focused my energy on ml, I have an extensive background as a backend dev since I have occupied this role in three companies as an intern already.

I have also developed the front end of a telemetry dashboard for Sonia, a scientific club during my time at school. I built a small video game, a real estate data web scrapper, an alpha beta prunning ai agent and a whole lot more. I learn very quickly and I can be an asset to any smaller software companies in need of somebody to contribute to a bit of everything.

Skills

Here is list of techonologies I have worked with and skills I possess:

• Machine Learning Skills: Data modelling, Data Preparing/Cleaning, Classification, Regression, Clustering, Object Detection, Implementing models from papers, Computer Vision using CNNs and Transformers
• Machine Learning Frameworks: Pytorch, Pandas, Numpy, JAX, Scikit-Learn, Matplotlib, Tensorflow, Keras
• Programming Languages: Python, Java, Scala, Javascript/Typescript, C/C++
• Web Tech Frameworks: HTML, CSS, React, VueJS, Django, SQL, Springboot, Scrapy, Postgres
• Tools and Frameworks: Jupyter, Eclipse, VS Code, IntelliJ, Visual Studio
• Operating Systems: Windows, Linux & MacOs