Our products are used to:
_reduce the uncertainty of Machine Learning models,
_prioritize enterprise data efforts,
_support experts in the ML loop,
_improve the quality of ML models, especially in multi-class settings with complex ontologies,
_reduce data footprint and compactify ML models so as to be used by the Internet of Things applications,
_improve gaming experience via more challenging and realistic AI in games,
_create intelligent advisory systems from pre-compiled building blocks.
Daniel joined QED Software in 2018. At QED Software he is leading both internal and external projects, guiding the teams with his technical skills and theoretical knowledge.
He graduated from University of Warsaw with a masters degree in Computer Science. Now he is pursuing a PhD at the same university researching the usage of neural networks in active learning. His main fields of specialization are machine learning and active learning.
In his career he has gained developer experience in several technologies and languages, going through C++, Java, Python. Now he sticks to Python from a pragmatic point of view, but he is still hoping that statically typed language e. g. Rust will take the world by storm
Personally he is a passionate fantasy books reader and gaming enthusiast. He is also expanding his knowledge in physics and computational biology hoping to use his computer science proficiency in new fields.