Douglas Allaire

1.9k total citations
91 papers, 1.3k citations indexed

About

Douglas Allaire is a scholar working on Computational Theory and Mathematics, Statistics, Probability and Uncertainty and Artificial Intelligence. According to data from OpenAlex, Douglas Allaire has authored 91 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Computational Theory and Mathematics, 40 papers in Statistics, Probability and Uncertainty and 20 papers in Artificial Intelligence. Recurrent topics in Douglas Allaire's work include Advanced Multi-Objective Optimization Algorithms (39 papers), Probabilistic and Robust Engineering Design (39 papers) and Machine Learning in Materials Science (15 papers). Douglas Allaire is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (39 papers), Probabilistic and Robust Engineering Design (39 papers) and Machine Learning in Materials Science (15 papers). Douglas Allaire collaborates with scholars based in United States, Germany and Switzerland. Douglas Allaire's co-authors include Karen Willcox, Raymundo Arróyave, Danial Khatamsaz, Ankit Srivastava, Prashant Singh, D. D. Johnson, Brent Vela, Sam Friedman, Seyede Fatemeh Ghoreishi and Rémi Lam and has published in prestigious journals such as PLoS ONE, Journal of Applied Physics and Acta Materialia.

In The Last Decade

Douglas Allaire

84 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Douglas Allaire United States 24 429 415 299 259 201 91 1.3k
Zan Yang China 19 534 1.2× 445 1.1× 50 0.2× 104 0.4× 334 1.7× 112 1.2k
Roberto Schirru Brazil 23 199 0.5× 228 0.5× 224 0.7× 208 0.8× 449 2.2× 99 1.8k
Jianqiao Chen China 20 378 0.9× 609 1.5× 90 0.3× 127 0.5× 74 0.4× 57 1.3k
Sunil Gupta Australia 18 233 0.5× 50 0.1× 154 0.5× 187 0.7× 286 1.4× 70 1.2k
Joel A. Paulson United States 25 181 0.4× 194 0.5× 196 0.7× 140 0.5× 178 0.9× 95 1.8k
Zhiguo Zhou China 19 107 0.2× 104 0.3× 201 0.7× 137 0.5× 298 1.5× 86 1.3k
Yi Gao China 15 167 0.4× 262 0.6× 89 0.3× 160 0.6× 61 0.3× 72 863
Jian‐Bo Yang United Kingdom 23 98 0.2× 74 0.2× 155 0.5× 145 0.6× 234 1.2× 71 1.4k
R. T. Haftka United States 16 656 1.5× 470 1.1× 38 0.1× 258 1.0× 87 0.4× 35 1.7k
Cláudio M.N.A. Pereira Brazil 21 120 0.3× 207 0.5× 104 0.3× 187 0.7× 233 1.2× 58 1.3k

Countries citing papers authored by Douglas Allaire

Since Specialization
Citations

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

Fields of papers citing papers by Douglas Allaire

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Douglas Allaire

This figure shows the co-authorship network connecting the top 25 collaborators of Douglas Allaire. A scholar is included among the top collaborators of Douglas Allaire 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 Douglas Allaire. Douglas Allaire 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.
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Janßen, Jan, et al.. (2025). Hierarchical Gaussian process-based Bayesian optimization for materials discovery in high entropy alloy spaces. Acta Materialia. 289. 120908–120908. 6 indexed citations
3.
Ahmed, Faez, Wei Chen, Christopher McComb, et al.. (2025). Special Issue: Design by Data: Cultivating Datasets for Engineering Design. Journal of Mechanical Design. 147(4). 1 indexed citations
4.
Attari, Vahid, Danial Khatamsaz, Douglas Allaire, & Raymundo Arróyave. (2023). Towards inverse microstructure-centered materials design using generative phase-field modeling and deep variational autoencoders. Acta Materialia. 259. 119204–119204. 27 indexed citations
5.
Khatamsaz, Danial, Brent Vela, Prashant Singh, et al.. (2023). Bayesian optimization with active learning of design constraints using an entropy-based approach. npj Computational Materials. 9(1). 64 indexed citations
6.
Zhang, Guanglu, Douglas Allaire, & Jonathan Cagan. (2022). Reducing the Search Space for Global Minimum: A Focused Regions Identification Method for Least Squares Parameter Estimation in Nonlinear Models. Journal of Computing and Information Science in Engineering. 23(2). 3 indexed citations
7.
Khatamsaz, Danial, et al.. (2021). Bayesian Optimization of Multiobjective Functions Using Multiple Information Sources. AIAA Journal. 59(6). 1964–1974. 12 indexed citations
8.
Khatamsaz, Danial, et al.. (2021). Efficiently exploiting process-structure-property relationships in material design by multi-information source fusion. Acta Materialia. 206. 116619–116619. 24 indexed citations
9.
Allaire, Douglas, et al.. (2020). Utilizing Gaussian processes to fit high dimension thermodynamic data that includes estimated variability. Computational Materials Science. 188. 110133–110133. 4 indexed citations
10.
Zhang, Guanglu, Douglas Allaire, Venkatesh Shankar, & Daniel A. McAdams. (2019). A case against the trickle-down effect in technology ecosystems. PLoS ONE. 14(6). e0218370–e0218370. 5 indexed citations
11.
Arróyave, Raymundo, et al.. (2019). Efficient use of multiple information sources in material design. Acta Materialia. 180. 260–271. 25 indexed citations
12.
Attari, Vahid, et al.. (2019). Uncertainty propagation in a multiscale CALPHAD-reinforced elastochemical phase-field model. Acta Materialia. 183. 452–470. 23 indexed citations
13.
Allaire, Douglas, et al.. (2018). A Fusion-Based Multi-Information Source Optimization Approach using Knowledge Gradient Policies. 2018 AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference. 23 indexed citations
14.
Srivastava, Ankit, et al.. (2018). Multi-Information Source Fusion and Optimization to Realize ICME: Application to Dual-Phase Materials. Journal of Mechanical Design. 140(11). 35 indexed citations
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Korobenko, Artem, Hyonny Kim, Douglas Allaire, et al.. (2016). Dynamic-Data-Driven Damage Prediction in Aerospace Composite Structures. 2 indexed citations
18.
Allaire, Douglas & Karen Willcox. (2013). A MATHEMATICAL AND COMPUTATIONAL FRAMEWORK FOR MULTIFIDELITY DESIGN AND ANALYSIS WITH COMPUTER MODELS. International Journal for Uncertainty Quantification. 4(1). 1–20. 37 indexed citations
19.
Allaire, Douglas & Karen Willcox. (2012). Fusing information from multifidelity computer models of physical systems. International Conference on Information Fusion. 2458–2465. 11 indexed citations
20.
Allaire, Douglas & Karen Willcox. (2010). Distributional sensitivity analysis. Procedia - Social and Behavioral Sciences. 2(6). 7595–7596. 2 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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