| Dynamic functional principal components S Hörmann, Ł Kidziński, M Hallin Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2015 | 99 | 2015 |
| MOOC video interaction patterns: What do they tell us? N Li, Ł Kidziński, P Jermann, P Dillenbourg Design for teaching and learning in a networked world, 197-210, 2015 | 53 | 2015 |
| How do in-video interactions reflect perceived video difficulty? N Li, L Kidzinski, P Jermann, P Dillenbourg Proceedings of the European MOOCs stakeholder summit 2015, 112-121, 2015 | 46 | 2015 |
| Translating head motion into attention-towards processing of student’s body-language M Raca, L Kidzinski, P Dillenbourg Proceedings of the 8th international conference on educational data mining, 2015 | 36 | 2015 |
| Introduction to smart learning analytics: foundations and developments in video-based learning MN Giannakos, DG Sampson, L Kidziński | 30 | 2016 |
| Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments Ł Kidziński, SP Mohanty, CF Ong, Z Huang, S Zhou, A Pechenko, ... The NIPS'17 Competition: Building Intelligent Systems, 121-153, 2018 | 21 | 2018 |
| Multimodal teaching analytics: Automated extraction of orchestration graphs from wearable sensor data LP Prieto, K Sharma, Ł Kidzinski, MJ Rodríguez‐Triana, P Dillenbourg Journal of computer assisted learning 34 (2), 193-203, 2018 | 18 | 2018 |
| A note on estimation in Hilbertian linear models S Hörmann, Ł Kidziński Scandinavian journal of statistics 42 (1), 43-62, 2015 | 17 | 2015 |
| Semi-Markov Model for Simulating MOOC Students. L Faucon, L Kidzinski, P Dillenbourg International Educational Data Mining Society, 2016 | 16 | 2016 |
| Learning to run challenge: Synthesizing physiologically accurate motion using deep reinforcement learning Ł Kidziński, SP Mohanty, CF Ong, JL Hicks, SF Carroll, S Levine, ... The NIPS'17 Competition: Building Intelligent Systems, 101-120, 2018 | 15 | 2018 |
| Orchestration load indicators and patterns: In-the-wild studies using mobile eye-tracking LP Prieto, K Sharma, Ł Kidzinski, P Dillenbourg IEEE Transactions on Learning Technologies 11 (2), 216-229, 2017 | 14 | 2017 |
| How to quantify student’s regularity? MS Boroujeni, K Sharma, Ł Kidziński, L Lucignano, P Dillenbourg European conference on technology enhanced learning, 277-291, 2016 | 14 | 2016 |
| A tutorial on machine learning in educational science Ł Kidziński, M Giannakos, DG Sampson, P Dillenbourg State-of-the-Art and Future Directions of Smart Learning, 453-459, 2016 | 14 | 2016 |
| Automated human-level diagnosis of dysgraphia using a consumer tablet T Asselborn, T Gargot, Ł Kidziński, W Johal, D Cohen, C Jolly, ... NPJ digital medicine 1 (1), 1-9, 2018 | 13 | 2018 |
| Semiautomatic annotation of mooc forum posts W Liu, Ł Kidziński, P Dillenbourg State-of-the-Art and Future Directions of Smart Learning, 399-408, 2016 | 11 | 2016 |
| Estimation in functional lagged regression S Hörmann, Ł Kidziński, P Kokoszka Journal of time series analysis 36 (4), 541-561, 2015 | 11 | 2015 |
| Automatic real-time gait event detection in children using deep neural networks Ł Kidziński, S Delp, M Schwartz PloS one 14 (1), 2019 | 10 | 2019 |
| On Generalizability of MOOC Models. L Kidzinsk, K Sharma, MS Boroujeni, P Dillenbourg International Educational Data Mining Society, 2016 | 6 | 2016 |
| Kidzinski Ł., Rodríguez-Triana M., Dillenbourg P. Multimodal teaching analytics: Automated extraction of orchestration graphs from wearable sensor data L Prieto, K Sharma J. Comput. Assist. Learn, 2018 | 5 | 2018 |
| Longitudinal data analysis using matrix completion Ł Kidziński, T Hastie arXiv preprint arXiv:1809.08771, 2018 | 4 | 2018 |
Pierre DillenbourgProfessor, School of Computer & Communication Sciences, Ecole Polytechnique Fedrale de LausanneVerified email at epfl.ch
