Łukasz Kidziński
Cited by
Cited by
Dynamic functional principal components
S Hörmann, Ł Kidziński, M Hallin
Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2015
Deep neural networks enable quantitative movement analysis using single-camera videos
Ł Kidziński, B Yang, JL Hicks, A Rajagopal, SL Delp, MH Schwartz
Nature communications 11 (1), 4054, 2020
Wearable sensors enable personalized predictions of clinical laboratory measurements
J Dunn, L Kidzinski, R Runge, D Witt, JL Hicks, ...
Nature medicine 27 (6), 1105-1112, 2021
OpenCap: Human movement dynamics from smartphone videos
SD Uhlrich, A Falisse, Ł Kidziński, J Muccini, M Ko, AS Chaudhari, ...
PLoS computational biology 19 (10), e1011462, 2023
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: 10th European …, 2015
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), 42, 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
Automatic real-time gait event detection in children using deep neural networks
Ł Kidziński, S Delp, M Schwartz
PloS one 14 (1), e0211466, 2019
Deep reinforcement learning for modeling human locomotion control in neuromechanical simulation
S Song, Ł Kidziński, XB Peng, C Ong, J Hicks, S Levine, CG Atkeson, ...
Journal of neuroengineering and rehabilitation 18, 1-17, 2021
Automated classification of radiographic knee osteoarthritis severity using deep neural networks
KA Thomas, Ł Kidziński, E Halilaj, SL Fleming, GR Venkataraman, ...
Radiology: Artificial Intelligence 2 (2), e190065, 2020
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
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
Introduction to smart learning analytics: foundations and developments in video-based learning
MN Giannakos, DG Sampson, L Kidziński
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
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
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
How to quantify student’s regularity?
MS Boroujeni, K Sharma, Ł Kidziński, L Lucignano, P Dillenbourg
Adaptive and Adaptable Learning: 11th European Conference on Technology …, 2016
Artificial intelligence for prosthetics: Challenge solutions
Ł Kidziński, C Ong, SP Mohanty, J Hicks, S Carroll, B Zhou, H Zeng, ...
The NeurIPS'18 Competition: From Machine Learning to Intelligent …, 2020
A neural network to predict the knee adduction moment in patients with osteoarthritis using anatomical landmarks obtainable from 2D video analysis
MA Boswell, SD Uhlrich, K Thomas, JA Kolesar, GE Gold, GS Beaupre, ...
Osteoarthritis and cartilage 29 (3), 346-356, 2021
Assessing inertial measurement unit locations for freezing of gait detection and patient preference
J O’Day, M Lee, K Seagers, S Hoffman, A Jih-Schiff, Ł Kidziński, S Delp, ...
Journal of neuroengineering and rehabilitation 19 (1), 20, 2022
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