Ghanshyam Pilania - Concepedia

Author

Ghanshyam Pilania

Also Known As

G. Pilania, Ghanshyam Pilania, Hartman, Steven T., Pandita, Piyush, Pilania Ghanshyam, Pilania, Ghanshyam, Pilania, Ghanshyam [Los Alamos National Laboratory]; Kocevski, Vancho [Los Alamos National Laboratory]; Uberuaga, Blas P. [Los Alamos National Laboratory]

173

Publications

8.2K

Citations

H-Index

110

Concepts

All Affiliations

Los Alamos National Laboratory University of Connecticut University of Michigan Columbia University

About

Ghanshyam Pilania is an author at Los Alamos National Laboratory specializing in engineering, materials science, and chemistry.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	30	47	4.2K
2	Applied Physics	19	24	1.3K
3	Natural Sciences	13	15	1.8K
4	Business	1	1	101
5	Medicine	1	1	23

Ghanshyam Pilania

Publications

7.6K

Citations

H-Index

Page 1

	Year	Citations
Machine learning in materials informatics: recent applications and prospects Rampi Ramprasad, Rohit Batra, Ghanshyam Pilania, npj Computational Materials	2017	1.7K
Accelerating materials property predictions using machine learning Ghanshyam Pilania, Chenchen Wang, Xun Jiang, Scientific Reports EngineeringMachine LearningMachine Learning ToolComputational ChemistryChemistry	2013	816
Machine Learning Strategy for Accelerated Design of Polymer Dielectrics Arun Mannodi‐Kanakkithodi, Ghanshyam Pilania, Tran Doan Huan, Scientific Reports	2016	384
Rational design of all organic polymer dielectrics Vinit Sharma, Chenchen Wang, Robert G. Lorenzini, Nature Communications Materials ScienceEngineeringFlexible ElectronicsOrganic ElectronicsRational Design	2014	329
Multi-fidelity machine learning models for accurate bandgap predictions of solids Ghanshyam Pilania, J. E. Gubernatis, Turab Lookman Computational Materials Science Materials ScienceEngineeringMachine LearningPhysicsAccurate Bandgap Predictions	2016	304
Machine learning in materials science: From explainable predictions to autonomous design Ghanshyam Pilania Computational Materials Science Materials ScienceArtificial IntelligenceEngineeringMachine LearningData Science	2021	230
From Organized High-Throughput Data to Phenomenological Theory using Machine Learning: The Example of Dielectric Breakdown Chiho Kim, Ghanshyam Pilania Chemistry of Materials DielectricsEngineeringMachine LearningMachine Learning ToolDielectric Insulators	2016	229
Finding New Perovskite Halides via Machine Learning Ghanshyam Pilania, Prasanna V. Balachandran, Chiho Kim, Frontiers in Materials EngineeringMachine LearningHalide PerovskitesComputational ChemistryChemistry	2016	202
A polymer dataset for accelerated property prediction and design Tran Doan Huan, Arun Mannodi‐Kanakkithodi, Chiho Kim, Scientific Data	2016	201
Machine Learning Assisted Predictions of Intrinsic Dielectric Breakdown Strength of ABX<sub>3</sub>Perovskites Chiho Kim, Ghanshyam Pilania, Rampi Ramprasad The Journal of Physical Chemistry C Materials ScienceMaterials EngineeringElectrical EngineeringEngineeringPerovskite Crystal Structure	2016	198

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