Nonlinear microfluidics D Stoecklein, D Di Carlo Analytical chemistry 91 (1), 296-314, 2018 | 183 | 2018 |
A case study of deep reinforcement learning for engineering design: Application to microfluidic devices for flow sculpting XY Lee, A Balu, D Stoecklein, B Ganapathysubramanian, S Sarkar Journal of Mechanical Design 141 (11), 111401, 2019 | 89 | 2019 |
Deep learning for flow sculpting: Insights into efficient learning using scientific simulation data D Stoecklein, KG Lore, M Davies, S Sarkar, B Ganapathysubramanian Scientific reports 7 (1), 46368, 2017 | 87 | 2017 |
Shaped 3D microcarriers for adherent cell culture and analysis CY Wu, D Stoecklein, A Kommajosula, J Lin, K Owsley, ... Microsystems & nanoengineering 4 (1), 21, 2018 | 60 | 2018 |
Micropillar sequence designs for fundamental inertial flow transformations D Stoecklein, CY Wu, K Owsley, Y Xie, D Di Carlo, ... Lab on a Chip 14 (21), 4197-4204, 2014 | 53 | 2014 |
Optimization of micropillar sequences for fluid flow sculpting D Stoecklein, CY Wu, D Kim, D Di Carlo, B Ganapathysubramanian Physics of Fluids 28 (1), 2016 | 40 | 2016 |
Hierarchical feature extraction for efficient design of microfluidic flow patterns KG Lore, D Stoecklein, M Davies, B Ganapathysubramanian, S Sarkar Feature Extraction: Modern Questions and Challenges, 213-225, 2015 | 36 | 2015 |
Optimized design of obstacle sequences for microfluidic mixing in an inertial regime M Antognoli, D Stoecklein, C Galletti, E Brunazzi, D Di Carlo Lab on a Chip 21 (20), 3910-3923, 2021 | 35 | 2021 |
A deep learning framework for causal shape transformation KG Lore, D Stoecklein, M Davies, B Ganapathysubramanian, S Sarkar Neural Networks 98, 305-317, 2018 | 30 | 2018 |
Flow shape design for microfluidic devices using deep reinforcement learning XY Lee, A Balu, D Stoecklein, B Ganapathysubramanian, S Sarkar arXiv preprint arXiv:1811.12444, 2018 | 24 | 2018 |
Automated design for microfluid flow sculpting: multi-resolution approaches, efficient encoding, and CUDA implementation D Stoecklein, M Davies, N Wubshet, J Le, B Ganapathysubramanian Journal of Fluids Engineering, 2016 | 17* | 2016 |
FlowSculpt: Software for efficient design of inertial flow sculpting devices D Stoecklein, M Davies, JM de Rutte, CY Wu, D Di Carlo, ... Lab on a Chip 19 (19), 3277-3291, 2019 | 12 | 2019 |
uFlow: software for rational engineering of secondary flows in inertial microfluidic devices D Stoecklein, K Owsley, CY Wu, D Di Carlo, B Ganapathysubramanian Microfluidics and Nanofluidics 22, 1-12, 2018 | 12 | 2018 |
Pre-arranged sequences of micropillars for passive mixing control of water and ethanol M Antognoli, L Donato, C Galletti, D Stoecklein, D Di Carlo, E Brunazzi Chemical Engineering Journal 461, 141851, 2023 | 9 | 2023 |
Scanning two-photon continuous flow lithography for the fabrication of multi-functional microparticles S Chizari, S Udani, A Farzaneh, D Stoecklein, DD Carlo, JB Hopkins Optics Express 28 (26), 40088-40098, 2020 | 9 | 2020 |
Shape design for stabilizing microparticles in inertial microfluidic flows A Kommajosula, D Stoecklein, D Di Carlo, B Ganapathysubramanian Journal of Fluid Mechanics 886, A14, 2020 | 7 | 2020 |
Kin Gwn Lore, Michael Davies, Soumik Sarkar, and Baskar Ganapathysubramanian. Deep learning for flow sculpting: Insights into efficient learning using scientific simulation data D Stoecklein Scientific reports 7, 46368, 2017 | 6 | 2017 |
Flow sculpting enabled anaerobic digester for energy recovery from low-solid content waste S Ghanimeh, C Abou Khalil, D Stoecklein, A Kommasojula, ... Renewable Energy 154, 841-848, 2020 | 4 | 2020 |
Deep action sequence learning for causal shape transformation KG Lore, D Stoecklein, M Davies, B Ganapathysubramanian, S Sarkar arXiv preprint arXiv:1605.05368, 2016 | 3 | 2016 |
Micropillar sequence design for inertial fluid flow sculpting D Stoecklein, B Ganapathysubramanian, CY Wu, D Di Carlo Bulletin of the American Physical Society 60, 2015 | 1 | 2015 |