Alqamah Sayeed

952 total citations
22 papers, 657 citations indexed

About

Alqamah Sayeed is a scholar working on Environmental Engineering, Atmospheric Science and Health, Toxicology and Mutagenesis. According to data from OpenAlex, Alqamah Sayeed has authored 22 papers receiving a total of 657 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Environmental Engineering, 15 papers in Atmospheric Science and 12 papers in Health, Toxicology and Mutagenesis. Recurrent topics in Alqamah Sayeed's work include Air Quality Monitoring and Forecasting (14 papers), Atmospheric chemistry and aerosols (13 papers) and Air Quality and Health Impacts (12 papers). Alqamah Sayeed is often cited by papers focused on Air Quality Monitoring and Forecasting (14 papers), Atmospheric chemistry and aerosols (13 papers) and Air Quality and Health Impacts (12 papers). Alqamah Sayeed collaborates with scholars based in United States, Nepal and South Korea. Alqamah Sayeed's co-authors include Yunsoo Choi, Yannic Lops, Ebrahim Eslami, Jia Jung, Ahmed Khan Salman, Anirban Roy, Arman Pouyaei, Masoud Ghahremanloo, Meisam Amani and Shuai Pan and has published in prestigious journals such as Geophysical Research Letters, Atmospheric Environment and Bulletin of the American Meteorological Society.

In The Last Decade

Alqamah Sayeed

20 papers receiving 648 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Alqamah Sayeed United States	14	491	376	340	163	73	22	657
Yannic Lops United States	15	591 1.2×	494 1.3×	415 1.2×	284 1.7×	72 1.0×	26	841
Jia Jung United States	17	393 0.8×	406 1.1×	463 1.4×	282 1.7×	98 1.3×	43	821
Suli Zhao China	12	419 0.9×	522 1.4×	245 0.7×	181 1.1×	141 1.9×	18	804
Fangwen Bao China	13	216 0.4×	348 0.9×	419 1.2×	258 1.6×	48 0.7×	27	698
Shuaiyi Shi China	16	261 0.5×	405 1.1×	425 1.3×	310 1.9×	61 0.8×	46	805
Ebrahim Eslami United States	8	288 0.6×	235 0.6×	196 0.6×	89 0.5×	74 1.0×	13	450
Anna Ripoll Spain	12	378 0.8×	552 1.5×	354 1.0×	169 1.0×	255 3.5×	15	786
Arman Pouyaei United States	13	263 0.5×	265 0.7×	326 1.0×	112 0.7×	34 0.5×	29	513
Mehdi Zamani China	5	317 0.6×	239 0.6×	112 0.3×	173 1.1×	60 0.8×	6	509
Andrew Morris United Kingdom	7	319 0.6×	271 0.7×	94 0.3×	82 0.5×	86 1.2×	14	438

Countries citing papers authored by Alqamah Sayeed

Since Specialization

Citations

This map shows the geographic impact of Alqamah Sayeed'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 Alqamah Sayeed with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alqamah Sayeed more than expected).

Fields of papers citing papers by Alqamah Sayeed

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alqamah Sayeed. 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 Alqamah Sayeed. The network helps show where Alqamah Sayeed may publish in the future.

Co-authorship network of co-authors of Alqamah Sayeed

This figure shows the co-authorship network connecting the top 25 collaborators of Alqamah Sayeed. A scholar is included among the top collaborators of Alqamah Sayeed 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 Alqamah Sayeed. Alqamah Sayeed is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Sayeed, Alqamah, et al.. (2025). GOES‐R PM_2.5 Evaluation and Bias Correction: A Deep Learning Approach. Earth and Space Science. 12(2). 3 indexed citations

Park, Seohui, et al.. (2025). Hour by Hour PM_2.5 Mapping Using Geostationary Satellites. ACS ES&T Air. 2(9). 1816–1830. 2 indexed citations

Anderson, Eric, Emil Cherrington, Amanda Markert, et al.. (2025). Using economic methods to assess impacts of earth observation-based services: Why and how?. Environmental Impact Assessment Review. 115. 107975–107975.

Sayeed, Alqamah, et al.. (2025). Insights on Building Capacity to Support the Integration of Earth Observations into Air Quality Operations in South Asia. Bulletin of the American Meteorological Society. 106(4). E649–E656.

Raysoni, Amit U., et al.. (2024). Review of agricultural biomass burning and its impact on air quality in the continental United States of America. Environmental Advances. 16. 100546–100546. 10 indexed citations

Choi, Yunsoo, et al.. (2024). Deep-BCSI: A deep learning-based framework for bias correction and spatial imputation of PM2.5 concentrations in South Korea. Atmospheric Research. 301. 107283–107283. 13 indexed citations

Salman, Ahmed Khan, Arman Pouyaei, Yunsoo Choi, Yannic Lops, & Alqamah Sayeed. (2022). Deep learning solver for solving advection–diffusion equation in comparison to finite difference methods. Communications in Nonlinear Science and Numerical Simulation. 115. 106780–106780. 10 indexed citations

Sayeed, Alqamah, et al.. (2022). Hourly and Daily PM_2.5 Estimations Using MERRA‐2: A Machine Learning Approach. Earth and Space Science. 9(11). 19 indexed citations

Sayeed, Alqamah, Ebrahim Eslami, Yannic Lops, & Yunsoo Choi. (2022). CMAQ-CNN: A new-generation of post-processing techniques for chemical transport models using deep neural networks. Atmospheric Environment. 273. 118961–118961. 28 indexed citations

10.

Jung, Jia, Yunsoo Choi, Amir H. Souri, et al.. (2022). The Impact of Springtime‐Transported Air Pollutants on Local Air Quality With Satellite‐Constrained NO_x Emission Adjustments Over East Asia. Journal of Geophysical Research Atmospheres. 127(5). 18 indexed citations

11.

Sayeed, Alqamah, Yunsoo Choi, Arman Pouyaei, et al.. (2022). CNN-based model for the spatial imputation (CMSI version 1.0) of in-situ ozone and PM2.5 measurements. Atmospheric Environment. 289. 119348–119348. 19 indexed citations

12.

Lops, Yannic, Arman Pouyaei, Yunsoo Choi, et al.. (2021). Application of a Partial Convolutional Neural Network for Estimating Geostationary Aerosol Optical Depth Data. Geophysical Research Letters. 48(15). 33 indexed citations

13.

Sayeed, Alqamah, Yunsoo Choi, Jia Jung, et al.. (2021). A Deep Convolutional Neural Network Model for Improving WRF Simulations. IEEE Transactions on Neural Networks and Learning Systems. 34(2). 750–760. 45 indexed citations

14.

Sayeed, Alqamah, Yannic Lops, Yunsoo Choi, Jia Jung, & Ahmed Khan Salman. (2021). Bias correcting and extending the PM forecast by CMAQ up to 7 days using deep convolutional neural networks. Atmospheric Environment. 253. 118376–118376. 58 indexed citations

15.

Choi, Yunsoo, et al.. (2021). Efficient PM2.5 forecasting using geographical correlation based on integrated deep learning algorithms. Neural Computing and Applications. 33(22). 15073–15089. 44 indexed citations

16.

Eslami, Ebrahim, Yunsoo Choi, Yannic Lops, Alqamah Sayeed, & Ahmed Khan Salman. (2020). Using wavelet transform and dynamic time warping to identify the limitations of the CNN model as an air quality forecasting system. Geoscientific model development. 13(12). 6237–6251. 11 indexed citations

17.

Choi, Yong‐Sang, Ebrahim Eslami, Alqamah Sayeed, & Yannic Lops. (2019). CAMQ-AI: A computationally efficient deep learning model to improve CMAQ performance over the United States. AGU Fall Meeting Abstracts. 2019. 1 indexed citations

18.

Eslami, Ebrahim, Yunsoo Choi, Yannic Lops, & Alqamah Sayeed. (2019). A real-time hourly ozone prediction system using deep convolutional neural network. Neural Computing and Applications. 32(13). 8783–8797. 81 indexed citations

19.

Sayeed, Alqamah, Yunsoo Choi, Ebrahim Eslami, et al.. (2019). Using a deep convolutional neural network to predict 2017 ozone concentrations, 24 hours in advance. Neural Networks. 121. 396–408. 121 indexed citations

20.

Eslami, Ebrahim, et al.. (2019). A data ensemble approach for real-time air quality forecasting using extremely randomized trees and deep neural networks. Neural Computing and Applications. 32(11). 7563–7579. 58 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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