Grant Buster

485 total citations
22 papers, 134 citations indexed

About

Grant Buster is a scholar working on Artificial Intelligence, Global and Planetary Change and Astronomy and Astrophysics. According to data from OpenAlex, Grant Buster has authored 22 papers receiving a total of 134 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 9 papers in Global and Planetary Change and 3 papers in Astronomy and Astrophysics. Recurrent topics in Grant Buster's work include Solar Radiation and Photovoltaics (9 papers), Atmospheric aerosols and clouds (3 papers) and Atmospheric and Environmental Gas Dynamics (3 papers). Grant Buster is often cited by papers focused on Solar Radiation and Photovoltaics (9 papers), Atmospheric aerosols and clouds (3 papers) and Atmospheric and Environmental Gas Dynamics (3 papers). Grant Buster collaborates with scholars based in United States. Grant Buster's co-authors include Michael Rossol, Galen Maclaurin, Manajit Sengupta, Yu Xie, Andrew Glaws, Aron Habte, Dylan Hettinger, Per F. Peterson, Anthony Lopez and Gregory Brinkman and has published in prestigious journals such as Environmental Science & Technology, Renewable and Sustainable Energy Reviews and Nature Energy.

In The Last Decade

Grant Buster

18 papers receiving 133 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Grant Buster United States	7	42	42	26	25	19	22	134
José Luis Torres Spain	9	55 1.3×	14 0.3×	27 1.0×	33 1.3×	10 0.5×	22	149
William Marion United States	6	82 2.0×	42 1.0×	42 1.6×	70 2.8×	7 0.4×	10	189
José Carlos Matos Portugal	5	18 0.4×	17 0.4×	22 0.8×	38 1.5×	58 3.1×	6	152
Travis Williams United States	7	22 0.5×	57 1.4×	20 0.8×	21 0.8×	5 0.3×	11	168
Dongliang Han China	7	8 0.2×	47 1.1×	28 1.1×	11 0.4×	21 1.1×	25	206
Evan Rosenlieb United States	5	47 1.1×	59 1.4×	7 0.3×	93 3.7×	2 0.1×	6	214
Jesús-Ignacio Prieto Spain	11	68 1.6×	37 0.9×	17 0.7×	65 2.6×	222 11.7×	27	348
H. Yokoyama Japan	6	50 1.2×	40 1.0×	3 0.1×	47 1.9×	11 0.6×	12	223
M.A.C. Chendo Nigeria	11	114 2.7×	165 3.9×	63 2.4×	180 7.2×	14 0.7×	31	382

Countries citing papers authored by Grant Buster

Since Specialization

Citations

This map shows the geographic impact of Grant Buster's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Grant Buster with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Grant Buster more than expected).

Fields of papers citing papers by Grant Buster

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Grant Buster. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Grant Buster. The network helps show where Grant Buster may publish in the future.

Co-authorship network of co-authors of Grant Buster

This figure shows the co-authorship network connecting the top 25 collaborators of Grant Buster. A scholar is included among the top collaborators of Grant Buster based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Grant Buster. Grant Buster is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Buster, Grant, et al.. (2025). Second-generation downscaled earth system model data using generative machine learning. Data in Brief. 61. 111774–111774.

Glaws, Andrew, Grant Buster, Xiangyu Zhang, et al.. (2025). Designing Future Energy Systems With Generative AI. Computing in Science & Engineering. 27(4). 8–18. 2 indexed citations

Buster, Grant, et al.. (2025). Estimating the impacts of increasing temperatures and the efficacy of climate adaptation strategies in urban microclimates with deep learning. Urban Climate. 64. 102603–102603.

Buster, Grant, et al.. (2024). Supporting energy policy research with large language models: A case study in wind energy siting ordinances. Energy and AI. 18. 100431–100431. 7 indexed citations

Xie, Yu, Manajit Sengupta, Jaemo Yang, et al.. (2024). The influence of cloud cover on the reliability of satellite-based solar resource data. Renewable and Sustainable Energy Reviews. 208. 115070–115070.

Buster, Grant, et al.. (2024). Bias Corrected NOAA HRRR Wind Resource Data for Grid Integration Applications. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1 indexed citations

Buster, Grant, et al.. (2024). High-resolution meteorology with climate change impacts from global climate model data using generative machine learning. Nature Energy. 9(7). 894–906. 24 indexed citations

Xie, Yu, Manajit Sengupta, Jaemo Yang, et al.. (2023). Integration of a physics-based direct normal irradiance (DNI) model to enhance the National Solar Radiation Database (NSRDB). Solar Energy. 266. 112195–112195. 3 indexed citations

Habte, Aron, Manajit Sengupta, Grant Buster, & Yu Xie. (2023). Development and Evaluation of Typical Plane of Array Year (TPY) for Solar Energy Systems Over the Americas. 1–1.

10.

Maclaurin, Galen, Cris Hein, Travis Williams, et al.. (2022). National‐scale impacts on wind energy production under curtailment scenarios to reduce bat fatalities. Wind Energy. 25(9). 1514–1529. 9 indexed citations

11.

Buster, Grant, Aron Habte, Dylan Hettinger, et al.. (2022). Physics-guided machine learning for improved accuracy of the National Solar Radiation Database. Solar Energy. 232. 483–492. 22 indexed citations

12.

Buster, Grant, et al.. (2021). A New Modeling Framework for Geothermal Operational Optimization with Machine Learning (GOOML). Energies. 14(20). 6852–6852. 20 indexed citations

13.

Buster, Grant, Michael Rossol, Patrick Duffy, et al.. (2021). NRWAL (NLR formerly known as NREL Wind Analysis Library) [SWR-21-26]. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1 indexed citations

14.

Rossol, Michael & Grant Buster. (2021). NREL/rex: TemporalStats move. Zenodo (CERN European Organization for Nuclear Research). 2 indexed citations

15.

Rossol, Michael, et al.. (2021). NREL/reV: Offshore Overhaul to use NRWAL and drop ORCA. Zenodo (CERN European Organization for Nuclear Research). 2 indexed citations

16.

Habte, Aron, Manajit Sengupta, Haoyu Yuan, Grant Buster, & Jin Tan. (2021). Simulation of PV Variability as a Function of PV Generation and Plant Size. 2136–2140. 1 indexed citations

17.

Buster, Grant, Aron Habte, Dylan Hettinger, et al.. (2021). Physics-Guided Machine Learning for Prediction of Cloud Properties in Satellite-Derived Solar Data. 335–338. 1 indexed citations

18.

Rossol, Michael, Gregory Brinkman, Grant Buster, et al.. (2019). An Analysis of Thermal Plant Flexibility Using a National Generator Performance Database. Environmental Science & Technology. 53(22). 13486–13494. 7 indexed citations

19.

Haneklaus, Nils, et al.. (2017). Ni Interlayer to Improve Low-Pressure Diffusion Bonding of 316L SS Press Fit Tube-to-Tubesheet Joints for Coiled Tube Gas Heaters. Journal of Nuclear Engineering and Radiation Science. 3(3). 5 indexed citations

20.

Buster, Grant, et al.. (2016). A scaled experimental study of control blade insertion dynamics in Pebble-Bed Fluoride-Salt-Cooled High-Temperature Reactors. Nuclear Engineering and Design. 303. 153–162. 5 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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