The client was building a non-invasive glucose monitoring system. One of the first steps was to calibrate the physical device in order to transform the raw signal measurements to glucose levels. The preliminary work involved analyzing chronoamperometry data in order to find optimal parameters for the device and a way to calibrate the device.
This project aimed at providing means to compute how likely it is that two bitcoin addresses belong to the same entity.
The goal of this project was to develop a Generative Adversarial Network (GAN) capable of generating unique logotypes for teams on a gaming platform. The trained GAN architecture enabled the creation of 1M unique logotypes for the players of the platform.
This project aimed at analyzing customers' bitcoin transactions in order to provide their liquidity estimation and spending analysis.
The client was facing trouble collecting and analyzing data on customers using their API platform. I was requested to research and develop a solution to enable data analytics and visualization on their platform. The delivered solution allowed my client to understand their clients' behavior.
The goal of this project was to research and evaluate deep reinforcement learning methods to improve order placement in limit order markets.
This project aimed at analyzing bitcoin graph data and providing sophisticated information on bitcoin transaction data and aggregate on-chain statistics derived from graph data. The outcome statistics in the form of time series were later used in predictive machine learning models.
The goal of this project was to develop a Deep Learning powered solution detecting a disease on medical X-ray images. The model I have developed achieved an AUC of 0.98. The solution is part of a bigger system which is developed to assist medical doctors in their daily work.
The goal of this project was to develop a machine learning backed investment strategy based on multiple binary positive and negative signals sourced from price, market, and environmental analysis. The strategy I have developed performed 4x better than the baseline.
The goal of this project was to build an ETL system processing live online bitcoin transactional data and loading it to Neo4J graph database on the fly. The data included not only block chains but all details about transactions and interactions between addresses.