Dave Higdon

3.3k total citations · 1 hit paper
36 papers, 1.9k citations indexed

About

Dave Higdon is a scholar working on Artificial Intelligence, Atmospheric Science and Statistics, Probability and Uncertainty. According to data from OpenAlex, Dave Higdon has authored 36 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 9 papers in Atmospheric Science and 9 papers in Statistics, Probability and Uncertainty. Recurrent topics in Dave Higdon's work include Probabilistic and Robust Engineering Design (9 papers), Meteorological Phenomena and Simulations (7 papers) and Gaussian Processes and Bayesian Inference (6 papers). Dave Higdon is often cited by papers focused on Probabilistic and Robust Engineering Design (9 papers), Meteorological Phenomena and Simulations (7 papers) and Gaussian Processes and Bayesian Inference (6 papers). Dave Higdon collaborates with scholars based in United States, United Kingdom and Italy. Dave Higdon's co-authors include Brian J. Williams, James Gattiker, Maria Rightley, Marc C. Kennedy, Robert D. Ryne, John A. Cafeo, James C. Cavendish, Bryan Lewis, Madhav Marathe and Jiangzhuo Chen and has published in prestigious journals such as Nature Communications, Journal of the American Statistical Association and The Astrophysical Journal.

In The Last Decade

Dave Higdon

32 papers receiving 1.8k citations

Hit Papers

Computer Model Calibration Using High-Dimensional Output 2008 2026 2014 2020 2008 100 200 300 400 500
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Computer Model Calibration Using High-Dimensional Output
    2008 574 citations Dave Higdon, James Gattiker et al. Journal of the American Statistical Association profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dave Higdon United States 17 646 460 344 266 214 36 1.9k
Michael Goldstein United Kingdom 26 500 0.8× 326 0.7× 640 1.9× 417 1.6× 99 0.5× 123 2.6k
Antonietta Mira Switzerland 18 340 0.5× 104 0.2× 650 1.9× 139 0.5× 173 0.8× 97 2.6k
James Gattiker United States 12 394 0.6× 284 0.6× 247 0.7× 162 0.6× 43 0.2× 26 1.1k
Robert B. Gramacy United States 30 588 0.9× 1.1k 2.5× 1.4k 4.0× 734 2.8× 62 0.3× 91 3.4k
Ivano Azzini Italy 8 879 1.4× 210 0.5× 130 0.4× 128 0.5× 41 0.2× 17 2.4k
Houman Owhadi United States 22 935 1.4× 651 1.4× 445 1.3× 103 0.4× 36 0.2× 102 2.5k
Rolland L. Hardy United States 8 227 0.4× 346 0.8× 196 0.6× 114 0.4× 245 1.1× 17 2.9k
Dan Gabriel Cacuci United States 26 1.2k 1.9× 178 0.4× 79 0.2× 121 0.5× 40 0.2× 183 3.4k
Michael Sørensen Denmark 30 124 0.2× 87 0.2× 299 0.9× 189 0.7× 99 0.5× 68 2.7k
Marko Laine Finland 22 258 0.4× 70 0.2× 257 0.7× 51 0.2× 167 0.8× 75 2.8k

Countries citing papers authored by Dave Higdon

Since Specialization
Citations

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

Fields of papers citing papers by Dave Higdon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dave Higdon

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

All Works

20 of 20 papers shown
1.
Parikh, Nidhi, et al.. (2025). Evaluation of Seismic Artificial Intelligence with Uncertainty. Seismological Research Letters. 97(1). 471–486.
2.
Higdon, Dave, et al.. (2023). Novel application of a process convolution approach for calibrating output from numerical models. Environmetrics. 34(8). 1 indexed citations
3.
Beckage, Brian, et al.. (2022). Robust bias-correction of precipitation extremes using a novel hybrid empirical quantile-mapping method. Theoretical and Applied Climatology. 149(1-2). 863–882. 45 indexed citations
4.
Venkatramanan, Srinivasan, Adam Sadilek, Christopher L. Barrett, et al.. (2021). Forecasting influenza activity using machine-learned mobility map. Nature Communications. 12(1). 726–726. 47 indexed citations
5.
Venkatramanan, Srinivasan, Jiangzhuo Chen, Sandeep Gupta, et al.. (2019). Optimizing spatial allocation of seasonal influenza vaccine under temporal constraints. PLoS Computational Biology. 15(9). e1007111–e1007111. 33 indexed citations
6.
Higdon, Dave, Katrin Heitmann, Charles Nakhleh, & Salman Habib. (2018). Combining simulations and physical observations to estimate cosmological parameters. Oxford University Press eBooks.
7.
Venkatramanan, Srinivasan, Bryan Lewis, Jiangzhuo Chen, et al.. (2017). Using data-driven agent-based models for forecasting emerging infectious diseases. Epidemics. 22. 43–49. 118 indexed citations
8.
Osthus, Dave, Kyle S. Hickmann, Petruţa C. Caragea, Dave Higdon, & Sara Y. Del Valle. (2017). Forecasting seasonal influenza with a state-space SIR model. The Annals of Applied Statistics. 11(1). 202–224. 93 indexed citations
9.
Goldstein, Joshua, Dave Higdon, Gizem Korkmaz, et al.. (2017). A Bayesian simulation approach for supply chain synchronization. 2017 Winter Simulation Conference (WSC). 1571–1582. 3 indexed citations
10.
Chýlek, Petr, Timothy J. Vogelsang, James D. Klett, et al.. (2015). Indirect Aerosol Effect Increases CMIP5 Models’ Projected Arctic Warming. Journal of Climate. 29(4). 1417–1428. 19 indexed citations
11.
Pratola, Matthew T. & Dave Higdon. (2015). Bayesian Additive Regression Tree Calibration of Complex High-Dimensional Computer Models. Technometrics. 58(2). 166–179. 16 indexed citations
12.
McDonnell, Jordan, N. Schunck, W. Nazarewicz, et al.. (2014). Uncertainty Quantification for Nuclear Density Functional Theory. Bulletin of the American Physical Society. 2014. 2 indexed citations
13.
Higdon, Dave, James Gattiker, Earl Lawrence, et al.. (2013). Computer Model Calibration Using the Ensemble Kalman Filter. Technometrics. 55(4). 488–500. 20 indexed citations
14.
Funsten, H. O., R. Demajistre, P. C. Frisch, et al.. (2013). CIRCULARITY OF THEINTERSTELLAR BOUNDARY EXPLORERRIBBON OF ENHANCED ENERGETIC NEUTRAL ATOM (ENA) FLUX. The Astrophysical Journal. 776(1). 30–30. 102 indexed citations
15.
16.
Vrugt, Jasper A., et al.. (2009). Accelerating Markov chain Monte Carlo simulation by differential evolution with self-adaptive randomized subspace sampling. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 3 indexed citations
17.
Morris, Max D. & Dave Higdon. (2008). Comments on Goldstein and Rougier. Journal of Statistical Planning and Inference. 139(3). 1249–1250.
18.
Lee, Herbert K. H., et al.. (2002). Markov Random Field Models for High-Dimensional Parameters in Simulations of Fluid Flow in Porous Media. Technometrics. 44(3). 230–241. 60 indexed citations
19.
Higdon, Dave. (2001). Discussion. Journal of Computational and Graphical Statistics. 10(1). 69–74. 1 indexed citations
20.
Higdon, Dave. (2000). A Bayesian Time-Course Model for Functional Magnetic Resonance Imaging Data: Comment. Journal of the American Statistical Association. 95(451). 705–705. 1 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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