Ondrej Beluský

As a bachelor's project, I created a visual simulator and debugger of neural networks. The application has an Edit mode, where you can design and connect the layers. The Next mode is a simulation, which can be run or executed step-by-step, visualizing how the weights are changed.

I created a library for forecasting a time series as my Master's project. Forecasts are based directly or indirectly on the information derived from historical data. This data may include different patterns such as trend, horizontal, and cyclical or seasonal patterns. Most methods are based on the recognition of these patterns, their projection into the future, and thus, a forecast is created. I used statistical methods as well as neural networks for creating the forecast. I also used a combination of those methods and evolution algorithms to determine the final decision.

I was part of the core team working on this feature. I also developed tools for easier and unified manipulation of the segments to be used by other developers.

KeePassXC is a password manager application. It uses a secure protocol for communicating with the browser extension to provide the username and password for a particular website. For many Python scripts, I needed a password and token to log in to a particular service which I did not want to expose in plaintext. I wrote a Python script which would associate and connect to the running KeePassXC instance.
When the Python script needed a password, it would get it from the KeePassXC.

The application connects to the broker via an API, fetches current positions, and stores it in the database. Break-even points, dividend yields, P/Ls, and estimated earnings dates are then computed from the data. It also obtains earnings dates (from multiple sources), ex-dividend and payment dates, and provides a projection for future dividend dates.
All positions and related data are then stored in a Google sheet, which is used as the main UI. I coded it in Python and used MongoDB as the database.