Ming Dao
Materials Chemistry · 2001–2022
A researcher in the Science corpus: 22 papers; trusts 21 researchers and is trusted by 29 researchers here, as inferred from the citation graph.
Subfields
- Materials Chemistry — 244 citations into it; #1,664 of 11,513 by trust here, #2,355 by citations
- Mechanical Engineering — 176 citations into it; #1,234 of 8,300 by trust here, #685 by citations
- Mechanics of Materials — 153 citations into it; #1,245 of 6,291 by trust here, #318 by citations
- Atomic and Molecular Physics, and Optics — 46 citations into it; #1,714 of 7,135 by trust here, #1,317 by citations
- Biomedical Engineering — 45 citations into it; #3,025 of 10,734 by trust here, #3,269 by citations
- Computational Mechanics — 29 citations into it; #9,766 of 10,001 by trust here, #3,908 by citations
- Statistical and Nonlinear Physics — 16 citations into it
- Artificial Intelligence — 13 citations into it
Whom Ming Dao trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- M. Sheetz
- Subra Suresh
- Lei Lu
- Evan Ma
- Yinmin M Wang
- Diederik P. Kingma
- Andrew Y. Ng
- Marvin M. Doyley
- G. Em Karniadakis
- H. Swygenhoven
Who trusts Ming Dao overall
- Subra Suresh
- Jonathan B. Freund
- J. Phadikar
- Ting Zhu
- Chwee Teck Lim
- Xi Chen
- Ligang Sun
- Lei Lu
- C. A. Schuh
- L. Freund
Papers from Ming Dao's perspective
Ordered by how strongly the researchers Ming Dao trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Going deeper with convolutions
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Modeling grain size dependent optimal twin spacing for achieving ultimate high strength and related high ductility in nanotwinned metals (2011) — 216 citations
- Fracture toughness and fatigue crack growth characteristics of nanotwinned copper (2011) — 183 citations
- Toward a quantitative understanding of mechanical behavior of nanocrystalline metals (2007) — 1,082 citations
- Some critical experiments on the strain-rate sensitivity of nanocrystalline nickel (2003) — 557 citations
- Nano-sized twins induce high rate sensitivity of flow stress in pure copper (2005) — 686 citations
- Computational modeling of the forward and reverse problems in instrumented sharp indentation (2001) — 1,462 citations
- Indentation across size scales and disciplines: Recent developments in experimentation and modeling (2007) — 464 citations
- Stress relaxation and the structure size-dependence of plastic deformation in nanotwinned copper (2009) — 189 citations
- Depth-sensing instrumented indentation with dual sharp indenters (2003) — 347 citations
- Strength, strain-rate sensitivity and ductility of copper with nanoscale twins (2006) — 518 citations
- Acoustic separation of circulating tumor cells (2015) — 709 citations
- Connections between single-cell biomechanics and human disease states: gastrointestinal cancer and malaria. (2005) — 896 citations
- Large deformation of living cells using laser traps (2004) — 174 citations
- Extraction of mechanical properties of materials through deep learning from instrumented indentation (2020) — 317 citations
- Analyses of internal structures and defects in materials using physics-informed neural networks (2022) — 369 citations
- Improved fatigue resistance of gradient nanograined Cu (2019) — 142 citations
- Isolation of exosomes from whole blood by integrating acoustics and microfluidics (2017) — 814 citations
- Cold spray coating: review of material systems and future perspectives (2014) — 636 citations
- Molecularly based analysis of deformation of spectrin network and human erythrocyte (2006) — 229 citations
- Strain rate sensitivity of Cu with nanoscale twins (2006) — 138 citations