Kamil Kanclerz has been involved in research in the field of natural language analysis at the Wrocław University of Technology since 2019. He specializes in natural language processing in the following areas: sentiment analysis, information extraction, transfer learning, document embeddings, grammatical error correction and multiword expression recognition.

He participated in many research projects and is a co-creator of many innovative solutions in the field of natural language processing, such as the Sentimenti project, focused on automatic analysis of sentiment and emotions in the text. In order to obtain a large dataset for analysis and model preparation, an extensive survey was conducted involving more than 20 thousand people. The research resulted in the collection of over 18 million annotations about emotions. He was responsible for conducting research aimed at increasing the effectiveness of knowledge transfer between models generating vector representations and deep neural models specialized in the classification of texts in terms of polarization and emotion recognition. He was also responsible for developing and conducting research on the innovative combination of individual deep neural network models to increase their overall effectiveness.

He was also responsible for development of MeWeX tool for recognizing multi-track lexical units. Moreover he actively participated in the following natural language engineering projects: CLARIN-PL, AZON and CLARIN-PL 2.0. Currently he is focused on cross-language transfer learning using deep neural networks and deep language models. He is also takes an active part in the project “CLARIN - Common Language Resources and Technology Infrastructure” worth over 130 million PLN.