Ankit Agrawal

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	Toate	Din 2020
Referințe bibliografice	15412	11560
h-index	51	42
i10-index	154	109

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Alok ChoudharyProfessor Northwestern UniversityAdresă de e-mail confirmată pe eecs.northwestern.edu
Wei-keng LiaoNorthwestern UniversityAdresă de e-mail confirmată pe eecs.northwestern.edu
Chris WolvertonProfessor of Materials Science and Eng., Northwestern UniversityAdresă de e-mail confirmată pe northwestern.edu
Kamal ChoudharyNational Institute of Standards and TechnologyAdresă de e-mail confirmată pe nist.gov
Francesca TavazzaNational Institute of Standards and TechnologyAdresă de e-mail confirmată pe nist.gov
Logan WardArgonne National Laboratory, Data Science and Learning DivisionAdresă de e-mail confirmată pe anl.gov
Surya R. KalidindiGeorgia Institute of Technology, Atlanta, GAAdresă de e-mail confirmată pe me.gatech.edu
Carelyn CampbellNational Institute of Standards and TechnologyAdresă de e-mail confirmată pe nist.gov
Xiaoqiu HuangProfessor of Computer Science, Iowa State UniversityAdresă de e-mail confirmată pe iastate.edu
Simon J. L. BillingeColumbia University and Brookhaven National LaboratoryAdresă de e-mail confirmată pe columbia.edu
Brian L. DeCostNational Institute of Standards and TechnologyAdresă de e-mail confirmată pe nist.gov
Veera SundararaghavanUniversity of Michigan, Ann ArborAdresă de e-mail confirmată pe umich.edu
Jian CaoNorthwestern UniversityAdresă de e-mail confirmată pe northwestern.edu
Bryce MeredigTravertine Labs & Northwestern UniversityAdresă de e-mail confirmată pe northwestern.edu
Elizabeth A. HolmUniversity of MichiganAdresă de e-mail confirmată pe umich.edu
Shyue Ping OngUniversity of California San DiegoAdresă de e-mail confirmată pe ucsd.edu
Anubhav JainLawrence Berkeley National LabAdresă de e-mail confirmată pe lbl.gov
Pınar AcarAssociate Professor, Virginia TechAdresă de e-mail confirmată pe vt.edu
LC BrinsonDuke UniversityAdresă de e-mail confirmată pe duke.edu
Wei ChenNorthwestern UniversityAdresă de e-mail confirmată pe northwestern.edu

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Ankit Agrawal

Research Professor, Northwestern University

Adresă de e-mail confirmată pe eecs.northwestern.edu - Pagina de pornire

Artificial Intelligence High performance data mining Materials informatics Healthcare informatics Social media analytics


Titlu Sortați după descrierea bibliografică Sortați după an Sortați după titlu	Citat de Citat de	Anul
A general-purpose machine learning framework for predicting properties of inorganic materials L Ward, A Agrawal, A Choudhary, C Wolverton npj Computational Materials 2 (1), 1-7, 2016	1366	2016
Perspective: Materials informatics and big data: Realization of the “fourth paradigm” of science in materials science A Agrawal, A Choudhary Apl Materials 4 (5), 2016	1224	2016
Deep convolutional neural networks with transfer learning for computer vision-based data-driven pavement distress detection K Gopalakrishnan, SK Khaitan, A Choudhary, A Agrawal Construction and building materials 157, 322-330, 2017	1089	2017
Combinatorial screening for new materials in unconstrained composition space with machine learning B Meredig, A Agrawal, S Kirklin, JE Saal, JW Doak, A Thompson, K Zhang, ... Physical Review B 89 (9), 094104, 2014	788	2014
Recent advances and applications of deep learning methods in materials science K Choudhary, B DeCost, C Chen, A Jain, F Tavazza, R Cohn, CW Park, ... npj Computational Materials 8 (1), 59, 2022	605	2022
Twitter Trending Topic Classification K Lee, D Palsetia, R Narayanan, M Patwary, A Agrawal, A Choudhary Data Mining Workshops (ICDMW), 2011 IEEE 11th International Conference on …, 2011	489	2011
ElemNet: Deep Learning the Chemistry of Materials From Only Elemental Composition D Jha, L Ward, A Paul, W Liao, A Choudhary, C Wolverton, A Agrawal Scientific reports 8 (1), 17593, 2018	469	2018
A predictive machine learning approach for microstructure optimization and materials design R Liu, A Kumar, Z Chen, A Agrawal, V Sundararaghavan, A Choudhary Scientific reports 5 (1), 11551, 2015	427	2015
Including crystal structure attributes in machine learning models of formation energies via Voronoi tessellations L Ward, R Liu, A Krishna, VI Hegde, A Agrawal, A Choudhary, ... Physical Review B 96 (2), 024104, 2017	423	2017
The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design K Choudhary, KF Garrity, ACE Reid, B DeCost, AJ Biacchi, ... npj computational materials 6 (1), 173, 2020	377	2020
Deep learning approaches for mining structure-property linkages in high contrast composites from simulation datasets Z Yang, YC Yabansu, R Al-Bahrani, W Liao, AN Choudhary, SR Kalidindi, ... Computational Materials Science 151, 278-287, 2018	373	2018
Enhancing materials property prediction by leveraging computational and experimental data using deep transfer learning D Jha, K Choudhary, F Tavazza, W Liao, A Choudhary, C Campbell, ... Nature communications 10 (1), 5316, 2019	307	2019
Exploration of data science techniques to predict fatigue strength of steel from composition and processing parameters A Agrawal, PD Deshpande, A Cecen, GP Basavarsu, AN Choudhary, ... Integrating materials and manufacturing innovation 3 (1), 90-108, 2014	292	2014
Real-time disease surveillance using twitter data: demonstration on flu and cancer K Lee, A Agrawal, A Choudhary Proceedings of the 19th ACM SIGKDD international conference on Knowledge …, 2013	287	2013
Microstructural materials design via deep adversarial learning methodology Z Yang, X Li, L Catherine Brinson, AN Choudhary, W Chen, A Agrawal Journal of Mechanical Design 140 (11), 111416, 2018	269	2018
Deep materials informatics: Applications of deep learning in materials science A Agrawal, A Choudhary Mrs Communications 9 (3), 779-792, 2019	265	2019
A new scalable parallel DBSCAN algorithm using the disjoint-set data structure MMA Patwary, D Palsetia, A Agrawal, W Liao, F Manne, A Choudhary SC'12: Proceedings of the International Conference on High Performance …, 2012	243	2012
Predicting the outcome of startups: less failure, more success A Krishna, A Agrawal, A Choudhary 2016 IEEE 16th international conference on data mining workshops (ICDMW …, 2016	231	2016
Data-driven prediction of the high-dimensional thermal history in directed energy deposition processes via recurrent neural networks M Mozaffar, A Paul, R Al-Bahrani, S Wolff, A Choudhary, A Agrawal, ... Manufacturing letters 18, 35-39, 2018	210	2018
Establishing structure-property localization linkages for elastic deformation of three-dimensional high contrast composites using deep learning approaches Z Yang, YC Yabansu, D Jha, W Liao, AN Choudhary, SR Kalidindi, ... Acta Materialia 166, 335-345, 2019	177	2019

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