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.
An active and experienced researcher in the fields of science related to data exploration, machine learning, and artificial intelligence. In 2014 Andrzej received his PhD in computer science from the University of Warsaw, where he currently holds a position of assistant professor.
He participated in several R&D projects funded by NCBR, related to such topics as semantic indexing of scientific publications, assessment of threats during fire&rescue operations performed by the State Fire Service and active monitoring of safety conditions in underground coal mines. In his research, Andrzej cooperated with scientists from several academic centers in Poland and abroad, such as e.g., the Silesian University of Technology, Main School of Fire Service, the University of Granada and Dalhousie University.
His professional career also involves cooperation with such companies as AdgaM Solutions and Zoined Oy. His publication record consists of over 20 articles on topics related to applications of machine learning techniques. For his publications Andrzej received three best paper awards at international conferences.
A co-founder of Knowledge Pit – an online platform where Andrzej organizes open data mining challenges aimed at solving complex real-life problems. Currently he serves as Program Co-Chair of the 12th International Symposium on Advances in Artificial Intelligence and Applications.