X
Xiang Zhang
Researcher at Baylor College of Medicine
Publications - 3483
Citations - 144843
Xiang Zhang is an academic researcher from Baylor College of Medicine. The author has contributed to research in topics: Medicine & Computer science. The author has an hindex of 154, co-authored 1733 publications receiving 117576 citations. Previous affiliations of Xiang Zhang include University of California, Berkeley & University of Texas MD Anderson Cancer Center.
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Dispersion of magnetic plasmon polaritons in perforated trilayer metamaterials
TL;DR: In this paper, the dispersion properties of MPP modes were investigated in a trilayer metamaterial with rectangular hole arrays, and the results provided a definite polarization-dependent dispersion property.
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Disease gene prioritization by integrating tissue-specific molecular networks using a robust multi-network model
TL;DR: This paper develops a robust and flexible method to integrate tissue-specific molecular networks for disease gene prioritization and provides rigorous theoretical foundations for the algorithms in terms of their optimality and convergence properties.
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Emergence of an enslaved phononic bandgap in a non-equilibrium pseudo-crystal
Nicolas Bachelard,Chad Ropp,Marc Dubois,Rongkuo Zhao,Yuan Wang,Yuan Wang,Xiang Zhang,Xiang Zhang,Xiang Zhang +8 more
TL;DR: This work realizes a non-equilibrium material characterized by a bandgap whose edge is enslaved to the wavelength of an external coherent drive that dynamically self-assembles into an unconventional pseudo-crystal geometry that equally distributes momentum across elements.
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Influence of spark plasma sintering temperature on the microstructure and strengthening mechanisms of discontinuous three-dimensional graphene-like network reinforced Cu matrix composites
TL;DR: In this article, the influence of the spark plasma sintering (SPS) temperature on the microstructure and mechanical properties of the in-situ synthesized discontinuous three-dimensional graphene-like network (3D GN) reinforced copper matrix composites was investigated.
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Is deep learning the new agent for map generalization
TL;DR: This paper poses the controversial question of the title: is deep learning the new agent, i.e. the technique that will make generalization research bridge the gap to fully automated generalization processes?