Welcome to my GitHub page! 👋
I am a software engineer and data scientist with a background in electrical engineering, physics, and computer science (CV here). I have worked in academia and industry and I am always looking to solve interesting, research-type problems with high social and environmental impact. I have extensive experience with signal processing and algorithm development for software and hardware. Besides academia, I was previously involved in technology transfer, co-authored two patents (one on structural health monitoring sensor, the other on a machine learning pipeline), served as a data science consultant, and developed production-level software for indoor localization at a localization startup. Most recently I worked as a research and integration engineer in the Innovation department of iKnowHow, developing machine learning and computer vision applications. Now I work at UMG, where I am building and productionizing music and audio ML applications.
Projects:
- Check out my new app for wildfire smoke detection, powered by YOLOv5.
- Have a look at this automated cryptocurrency trading bot which uses handcrafted features and random forests for predicting whether to buy, sell, or hold a particular asset.
- A toy React Native app
- RoboWeldAR project. There I coordinated and co-developed a software component for 3D reconstruction and detection of candidate welding seams. Here you can find a dev tutorial for it.
- An article on using deep conv nets for sorting and picking nuclear waste,
- An online algorithm for computing moving averages and standard deviations
- Some useful coding tips and tricks I picked up along the way.
My list of buzzwords: neural networks, data scientist, artificial intelligence, deep learning, data science, python, scikit-learn, scipy, numpy, pandas, anaconda, jupyter notebook, keras, conda, venv, MATLAB, C++, React, React Native, databases, MongoDB, PostgreSQL, Linux, Git, Docker, Kubernetes, AWS, Azure, unit test, acceptance test, localization, sensors, robotics, IoT, supervised learning, unsupervised learning, dimensionality reduction, mathematics, linear algebra, optimization, statistics, decision trees, random forests, convolutional neural networks, signal processing, algorithms
