City Research Online

Items where Author is "Chugh, S."

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Verma, S., Chugh, S., Ghosh, S. (2023). A comprehensive deep learning method for empirical spectral prediction and its quantitative validation of nano-structured dimers. Scientific Reports, 13(1), article number 1129. doi: 10.1038/s41598-023-28076-3

Verma, S., Chugh, S., Ghosh, S. (2022). Artificial Neural Network Modelling for Optimizing the Optical Parameters of Plasmonic Paired Nanostructures. Nanomaterials (Basel), 12(1), article number 170. doi: 10.3390/nano12010170

Roth, G. A., Mensah, G. A., Johnson, C. O. (2020). Global Burden of Cardiovascular Diseases and Risk Factors, 1990–2019: Update From the GBD 2019 Study. Journal of the American College of Cardiology, 76(25), pp. 2982-3021. doi: 10.1016/j.jacc.2020.11.010

Chugh, S. (2020). Machine learning modelling, optimisation and thermal compensation of photonic waveguides. (Unpublished Doctoral thesis, City, University of London)

Chugh, S., Gulistan, A., Ghosh, S. ORCID: 0000-0002-1992-2289 (2019). Machine learning approach for computing optical properties of a photonic crystal fiber. Optics Express, 27(25), pp. 36414-36425. doi: 10.1364/oe.27.036414

Chugh, S., Ghosh, S. ORCID: 0000-0002-1992-2289, Gulistan, A. (2019). Machine Learning Regression Approach to the Nanophotonic Waveguide Analyses. Journal of Lightwave Technology, 37(24), pp. 6080-6089. doi: 10.1109/jlt.2019.2946572

Gulistan, A., Ghosh, S. ORCID: 0000-0002-1992-2289, Chugh, S. (2019). Air-holes induced multimodal fiber design to increase the effective index difference between higher order guided modes. Optical Fiber Technology, 53, article number 102023. doi: 10.1016/j.yofte.2019.102023

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