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Gaurav Sharma

Researcher at Shenzhen University

Publications -  1520
Citations -  40824

Gaurav Sharma is an academic researcher from Shenzhen University. The author has contributed to research in topics: Medicine & Chemistry. The author has an hindex of 82, co-authored 1244 publications receiving 31482 citations. Previous affiliations of Gaurav Sharma include Northeastern University & D. E. Shaw & Co..

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Journal ArticleDOI

Designing of an efficient algorithm for identifying Abbreviation definitions in biomedical Text

Shashank Singh, +3 more
- 30 Jun 2013 - 
TL;DR: A patternmatching method for mining acronyms and their definitions from biomedical text by considering the space reduction heuristic constraints has been proposed and implemented and is faster and more efficient than the previous approaches.
Proceedings ArticleDOI

The synthesis, characterization and application of cobalt ferrite nanoparticles in lipstick

Monika Vats, +6 more
TL;DR: The curcumin and ginger functionalized copper ferrite (CoFe2O4) nanoparticles have been synthesized sung a green method as mentioned in this paper and the size and the crystalline nature of the synthesized nanoparticles was analyzed by XRD pattern.
Journal ArticleDOI

Artistic Iris: A Case of Congenital Sectoral Heterochromia Iridis.

Mandeep Tomar, +3 more
- 01 Jul 2018 - 
TL;DR: Heterochromia iridis was present and involved both eyes, giving an artistic appearance to the iris, and among his two children, his daughter was affected, and his son was unaffected by this condition.
Journal ArticleDOI

Trimetallic@Cyclodextrin Nanocomposite: Photocatalyst for Degradation of Amoxicillin and Catalyst for Esterification Reactions

Gaurav Sharma, +6 more
- 07 Sep 2021 - 
TL;DR: In this paper, the preparation of new cyclodextrin supported Fe/La/Zn trimetallic nanocomposite by the micro-emulsion technique was performed for environmental remediation and catalytic activities.
Proceedings ArticleDOI

Comparative analysis of homologous buildings using range imaging

Li Ding, +6 more
TL;DR: A framework for comparing 3D point cloud representations of homologous buildings captured using lidar is developed, focusing on identifying similarities and differences, both among 3D scans of different buildings and between the3D scans and the design specifications of architectural drawings.