The goal of this project was to develop an AI backend engine for an intelligent decision support system which asses an ischemic stroke risk. The system was developed in collaboration with a health insurer to allow preventive interventions for patients with high risk of a stroke.
The goal of this project was to build an ETL system collecting and computing data about trades and trading positions for various cryptocurrencies. The data about trades and trading positions were integrated on the fly from multiple trading platforms via REST APIs and web socket.
The goal of this project was to develop a rules-based decision support system. The solution was assisting medical doctors to make a fast decision about blood transfusion. The project was conducted in collaboration with medical doctors as domain experts.
The goal of this project was to develop an AI-backed decision support system helping medical doctors to decide about blood transfusion. In collaboration with multiple hospitals, we collected historical data about blood transfusions, patients, and medical tests relevant to blood transfusion.
The goal of this project was to build an ETL system collecting, normalizing, and aggregating data about the popularity index (search volume) of various keywords from Google Trends. The system had two subsystems one for pulling historical data in bulk, the other for current data.
SolarData is a platform allowing to simulate the amount of energy produced by a photovoltaic energy system in a specified geographic location weather data and parameters of the photovoltaic system like number and type of solar panels, the angle of the installation, etc.
The goal of this project was to develop an AI backend for a frequently asked questions chatbot. A client had collected a significant amount of questions and answers that were used to train machine learning natural language processing models.
The goal of this project was to build an ETL system collecting and aggregating data about various crypto assets. The data about blocks and transactions on the crypto assets was fetched and integrated on-the-fly from multiple data sources via REST APIs.
The goal of this project was to develop an anomaly detection pipeline for business intelligence systems in order to trigger a BI report distribution - via slack or e-mail - when an anomalous situation was detected or send an alert to predefined groups of managers.
TripleProv is an in-memory RDF database capable to store, trace, and query provenance information in processing Linked Data queries. TripleProv returns an understandable description, at multiple levels of granularity, of the way, the results of a SPARQL query were derived.