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.
She holds a master's degree in Mathematics with Statistics and Data Analysis specialization from Warsaw University of Technology. Andżelika is passionate about data analysis and machine learning realms, possessing significant expertise in explaining decisions of AI systems and diagnosing causes of errors they make.
Her research interest also focuses on computer vision, machine learning and deep learning, but particularly on explainable and interpretable AI.
Apart from explainable AI, her hobbies are cooking, traveling and fashion.