ProxyMotes: Linux-based TinyOS Platform for Non-TinyOS Sensors and Actuators. - Tomasz Paczesny; Tomasz Tajmajer; Jaroslaw Domaszewicz; Aleksander Pruszkowski (ISPA, 2012)

CoAP and database integration for sleeping and non-routable nodes. - Tomasz Tajmajer; Tomasz Sadkowski; Wieslaw Winiecki (IDAACS, 2015)

Predicting annual average daily highway traffic from large data and very few measurements. - Tomasz Tajmajer; Malwina Splawinska; Piotr Wasilewski; Stan Matwin (IEEE BigData, 2016)

Node/Proxy portability: Designing for the two lives of your next WSAN middleware. - Tomasz Tajmajer; Spyros Lalis; Manos Koutsoubelias; Aleksander Pruszkowski; Jaroslaw Domaszewicz; Michele Nati; Alexander Gluhak (J. Syst. Softw., 2016)

Soft Actuation: Smart Home and Office with Human-in-the-Loop. - Jaroslaw Domaszewicz; Spyros Lalis; Aleksander Pruszkowski; Manos Koutsoubelias; Tomasz Tajmajer; Nasos Grigoropoulos; Michele Nati; Alexander Gluhak (IEEE Pervasive Comput., 2016)

Helping AI to Play Hearthstone: AAIA'17 Data Mining Challenge. - Andrzej Janusz; Tomasz Tajmajer; Maciej Swiechowski (FedCSIS, 2017)

Multi-Objective Deep Q-Learning with Subsumption Architecture. - Tomasz Tajmajer (CoRR, 2017)

Toward Machine Learning on Granulated Data - a Case of Compact Autoencoder-based Representations of Satellite Images. - Mateusz Przyborowski; Tomasz Tajmajer; Lukasz Grad; Andrzej Janusz; Piotr Biczyk; Dominik Slezak (IEEE BigData, 2018)

Improving Hearthstone AI by Combining MCTS and Supervised Learning Algorithms. - Maciej Swiechowski; Tomasz Tajmajer; Andrzej Janusz (CIG, 2018)

Toward an Intelligent HS Deck Advisor: Lessons Learned from AAIA'18 Data Mining Competition. - Andrzej Janusz; Tomasz Tajmajer; Maciej Swiechowski; Lukasz Grad; Jacek Puczniewski; Dominik Slezak (FedCSIS, 2018)

Modular Multi-Objective Deep Reinforcement Learning with Decision Values. - Tomasz Tajmajer (FedCSIS, 2018)

Integrated Human Tracking Based on Video and Smartphone Signal Processing within the Arahub System. - Jan Ludziejewski; Lukasz Grad; Lukasz Przebinda; Tomasz Tajmajer (FedCSIS, 2020)

A Practical Solution to Handling Randomness and Imperfect Information in Monte Carlo Tree Search. - Maciej Swiechowski; Tomasz Tajmajer (FedCSIS, 2021)