Daniel Q. Duffy

819 total citations
33 papers, 538 citations indexed

About

Daniel Q. Duffy is a scholar working on Computer Networks and Communications, Information Systems and Management and Global and Planetary Change. According to data from OpenAlex, Daniel Q. Duffy has authored 33 papers receiving a total of 538 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Networks and Communications, 10 papers in Information Systems and Management and 10 papers in Global and Planetary Change. Recurrent topics in Daniel Q. Duffy's work include Distributed and Parallel Computing Systems (11 papers), Meteorological Phenomena and Simulations (8 papers) and Scientific Computing and Data Management (8 papers). Daniel Q. Duffy is often cited by papers focused on Distributed and Parallel Computing Systems (11 papers), Meteorological Phenomena and Simulations (8 papers) and Scientific Computing and Data Management (8 papers). Daniel Q. Duffy collaborates with scholars based in United States, Australia and Germany. Daniel Q. Duffy's co-authors include Chaowei Yang, John L. Schnase, Manzhu Yu, Qian Liu, Tsengdar Lee, Fei Hu, Michael Little, Long S. Chiu, William P. Webster and Zhenlong Li and has published in prestigious journals such as The Science of The Total Environment, Sensors and Bulletin of the American Meteorological Society.

In The Last Decade

Daniel Q. Duffy

33 papers receiving 520 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Daniel Q. Duffy United States	13	210	97	94	89	87	33	538
Yaniss Guigoz Switzerland	12	139 0.7×	23 0.2×	82 0.9×	42 0.5×	21 0.2×	26	405
Martin Sudmanns Austria	15	176 0.8×	37 0.4×	67 0.7×	25 0.3×	34 0.4×	37	635
Baoxuan Jin China	11	108 0.5×	68 0.7×	40 0.4×	11 0.1×	63 0.7×	27	353
Lan You China	9	123 0.6×	51 0.5×	19 0.2×	23 0.3×	75 0.9×	33	445
Haidong Zhong China	13	253 1.2×	45 0.5×	115 1.2×	56 0.6×	88 1.0×	57	785
Ana‐Maria Olteanu‐Raimond France	12	171 0.8×	24 0.2×	40 0.4×	26 0.3×	33 0.4×	33	724
L. Cinquini United States	15	262 1.2×	247 2.5×	227 2.4×	20 0.2×	158 1.8×	38	722
Manmeet Singh India	16	280 1.3×	158 1.6×	249 2.6×	28 0.3×	173 2.0×	39	883
Jibo Xie China	12	105 0.5×	74 0.8×	75 0.8×	6 0.1×	56 0.6×	31	472

Countries citing papers authored by Daniel Q. Duffy

Since Specialization

Citations

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

Fields of papers citing papers by Daniel Q. Duffy

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Q. Duffy. 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 Daniel Q. Duffy. The network helps show where Daniel Q. Duffy may publish in the future.

Co-authorship network of co-authors of Daniel Q. Duffy

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Q. Duffy. A scholar is included among the top collaborators of Daniel Q. Duffy 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 Daniel Q. Duffy. Daniel Q. Duffy 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

Lagarde, Sjoerd M., Jianglai Liu, Jia Xu, et al.. (2025). A Systematic Study of Popular Software Packages and AI/ML Models for Calibrating In Situ Air Quality Data: An Example with Purple Air Sensors. Sensors. 25(4). 1028–1028. 1 indexed citations

Wang, Zifu, Yun Li, Kevin Wang, et al.. (2023). Adopting GPU computing to support DL-based Earth science applications. International Journal of Digital Earth. 16(1). 2660–2680. 5 indexed citations

Liu, Qian, Hui Xu, Dexuan Sha, et al.. (2020). Hyperspectral Infrared Sounder Cloud Detection Using Deep Neural Network Model. IEEE Geoscience and Remote Sensing Letters. 19. 1–5. 9 indexed citations

Liu, Qian, Long S. Chiu, Donglian Sun, et al.. (2020). Spatiotemporal impacts of COVID-19 on air pollution in California, USA. The Science of The Total Environment. 750. 141592–141592. 96 indexed citations

Yu, Manzhu, Myra Bambacus, Guido Cervone, et al.. (2020). Spatiotemporal event detection: a review. International Journal of Digital Earth. 13(12). 1339–1365. 62 indexed citations

Liu, Qian, Dexuan Sha, Manzhu Yu, et al.. (2020). PreciPatch: A Dictionary-based Precipitation Downscaling Method. Remote Sensing. 12(6). 1030–1030. 8 indexed citations

Maxwell, Thomas, et al.. (2019). The Earth Data Analytic Services Framework. AGU Fall Meeting Abstracts. 2019. 1 indexed citations

Hu, Fei, Jingchao Yang, Michael Little, et al.. (2018). Evaluating the Open Source Data Containers for Handling Big Geospatial Raster Data. ISPRS International Journal of Geo-Information. 7(4). 144–144. 19 indexed citations

Potter, Gerald L., et al.. (2017). Enabling Reanalysis Research Using the Collaborative Reanalysis Technical Environment (CREATE). Bulletin of the American Meteorological Society. 99(4). 677–687. 16 indexed citations

10.

Das, Kunal, et al.. (2015). Evaluation of Big Data Containers for Popular Storage, Retrieval, and Computation Primitives in Earth Science Analysis. AGU Fall Meeting Abstracts. 2015. 1 indexed citations

11.

Williams, D. N., V. Balaji, L. Cinquini, et al.. (2015). A Global Repository for Planet-Sized Experiments and Observations. Bulletin of the American Meteorological Society. 97(5). 803–816. 29 indexed citations

12.

Schnase, John L., et al.. (2014). MERRA Analytic Services: Meeting the Big Data challenges of climate science through cloud-enabled Climate Analytics-as-a-Service. Computers Environment and Urban Systems. 61. 198–211. 81 indexed citations

13.

Schnase, John L., et al.. (2013). MERRA Analytic Services: Meeting the Big Data Challenges of Climate Science through Cloud-Enabled Climate Analytics-as-a-Service. AGU Fall Meeting Abstracts. 2013. 2 indexed citations

14.

Duffy, Daniel Q., et al.. (2012). Introduction to the Boost C++ libraries : vol. II - advanced libraries. Medical Entomology and Zoology. 1 indexed citations

15.

Schnase, John L., et al.. (2012). The Virtual Climate Data Server (vCDS): An iRODS-Based Data Management Software Appliance Supporting Climate Data Services and Virtualization-as-a-Service in the NASA Center for Climate Simulation. 3 indexed citations

16.

Schnase, John L., et al.. (2011). iRODS-Based Climate Data Services and Virtualization-as-a-Service in the NASA Center for Climate Simulation. AGU Fall Meeting Abstracts. 2011. 1 indexed citations

17.

Duffy, Daniel Q., et al.. (2011). Preliminary Evaluation of MapReduce for High-Performance Climate Data Analysis. NASA STI Repository (National Aeronautics and Space Administration). 2011. 2 indexed citations

18.

Zhou, Shujia, Daniel Q. Duffy, Thomas L. Clune, et al.. (2009). The impact of IBM Cell technology on the programming paradigm in the context of computer systems for climate and weather models. Concurrency and Computation Practice and Experience. 21(17). 2176–2186. 5 indexed citations

19.

Metter, Darlene, F. Ross Woolley, Yong Bradley, et al.. (2006). Teaching Radiology Resident Didactics Using Videoconferencing. Academic Radiology. 13(10). 1276–1285. 6 indexed citations

20.

Goldsby, Kenneth A., et al.. (1995). More Chemistry in a Soda Bottle: A Conservation of Mass Activity. Journal of Chemical Education. 72(8). 734–734. 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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