S. Niezgoda
Materials Chemistry · 2008–2018
A researcher in the Science corpus: 8 papers; trusts 16 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Materials Chemistry — 64 citations into it; #3,537 of 11,513 by trust here, #7,154 by citations
- Mechanical Engineering — 59 citations into it; #2,408 of 8,300 by trust here, #3,471 by citations
- Mechanics of Materials — 43 citations into it; #5,967 of 6,291 by trust here, #4,794 by citations
- Biomaterials — 32 citations into it
- Aerospace Engineering — 29 citations into it; #5,831 of 6,421 by trust here, #3,644 by citations
- Computer Vision and Pattern Recognition — 8 citations into it; #20,820 of 21,575 by trust here, #18,266 by citations
- Computational Theory and Mathematics — 7 citations into it
- Artificial Intelligence — 6 citations into it
Whom S. Niezgoda trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ricardo A. Lebensohn
- Chih-Jen Lin
- X. Frank Xu
- Richard D. Gonzalez
- Irene J. Beyerlein
- Laurent Capolungo
- Ingo Steinwart
- C. Tomé
- David T. Fullwood
- Salvatore Torquato
Who trusts S. Niezgoda overall
- Surya R. Kalidindi
- Noah H. Paulson
- Akash Gupta
- Jitesh H. Panchal
- N. Kouraytem
- Ahmet Cecen
- David L. McDowell
- Rohit Batra
- M. Priddy
- A. Kanjarla
Papers from S. Niezgoda's perspective
Ordered by how strongly the researchers S. Niezgoda trusts endorse each paper. Same corpus, a different order for every researcher.
- A training algorithm for optimal margin classifiers
- LIBSVM: A library for support vector machines
- Support vector machines
- Basics of Applied Stochastic Processes
- Gradient-based learning applied to document recognition
- Introduction to Statistical Pattern Recognition
- Sparse grid collocation schemes for stochastic natural convection problems (Journal of Computational Physics)
- Microstructure Sensitive Design for Performance Optimization
- Random Heterogeneous Materials: Microstructure and Macroscopic Properties
- A comparison of methods for multiclass support vector machines (IEEE Trans. Neural Networks)
Their papers
- Understanding and visualizing microstructure and microstructure variance as a stochastic process (2011) — 145 citations
- Microstructure Sensitive Design for Performance Optimization (2012) — 458 citations
- Influence of deformation induced nanoscale twinning and FCC-HCP transformation on hardening and texture development in medium-entropy CrCoNi alloy (2018) — 188 citations
- Numerical study of the stress state of a deformation twin in magnesium (2015) — 217 citations
- Stochastic modeling of twin nucleation in polycrystals: An application in hexagonal close-packed metals (2014) — 155 citations
- Novel microstructure quantification framework for databasing, visualization, and analysis of microstructure data (2013) — 140 citations
- Microstructure reconstructions from 2-point statistics using phase-recovery algorithms (2008) — 281 citations
- Delineation of the space of 2-point correlations in a composite material system (2008) — 145 citations