Daniel Stoecklein
Title
Cited by
Cited by
Year
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
412014
Nonlinear microfluidics
D Stoecklein, D Di Carlo
Analytical chemistry 91 (1), 296-314, 2018
382018
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, 46368, 2017
282017
Optimization of micropillar sequences for fluid flow sculpting
D Stoecklein, CY Wu, D Kim, D Di Carlo, B Ganapathysubramanian
Physics of Fluids 28 (1), 012003, 2016
262016
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
232015
A deep learning framework for causal shape transformation
KG Lore, D Stoecklein, M Davies, B Ganapathysubramanian, S Sarkar
Neural Networks 98, 305-317, 2018
162018
Shaped 3D microcarriers for adherent cell culture and analysis
CY Wu, D Stoecklein, A Kommajosula, J Lin, K Owsley, ...
Microsystems & nanoengineering 4 (1), 1-9, 2018
142018
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
102016
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 (7), 74, 2018
82018
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
62018
Deep action sequence learning for causal shape transformation
KG Lore, D Stoecklein, M Davies, B Ganapathysubramanian, S Sarkar
arXiv preprint arXiv:1605.05368, 2016
32016
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), 2019
22019
Shape-design for stabilizing micro-particles in inertial microfluidic flows
A Kommajosula, D Stoecklein, D Di Carlo, B Ganapathysubramanian
arXiv preprint arXiv:1902.05935, 2019
22019
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
12019
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
12015
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
2020
Deep Learning for Engineering Big Data Analytics
KG Lore, D Stoecklein, M Davies, B Ganapathysubramanian, S Sarkar
Big Data Analytics, 151-166, 2017
2017
Computational methods and software for the design of inertial microfluidic flow sculpting devices
DJ Stoecklein
2017
Deep Action Sequence Learning for Causal Shape Transformation
K Gwn Lore, D Stoecklein, M Davies, B Ganapathysubramanian, S Sarkar
arXiv, arXiv: 1605.05368, 2016
2016
Characterization of ultrasonically prepared γ-Fe2O3-Al2O3 shell-core nanocomposites
M Vannette, J Hugen, D Stoecklein, B McCarty, R Prozorov
APS, Z31. 008, 2009
2009
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Articles 1–20