Matthew D. Bailey

671 total citations
20 papers, 382 citations indexed

About

Matthew D. Bailey is a scholar working on Control and Systems Engineering, Management Science and Operations Research and Artificial Intelligence. According to data from OpenAlex, Matthew D. Bailey has authored 20 papers receiving a total of 382 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Control and Systems Engineering, 4 papers in Management Science and Operations Research and 3 papers in Artificial Intelligence. Recurrent topics in Matthew D. Bailey's work include Scheduling and Timetabling Solutions (3 papers), Military Defense Systems Analysis (3 papers) and Military Strategy and Technology (3 papers). Matthew D. Bailey is often cited by papers focused on Scheduling and Timetabling Solutions (3 papers), Military Defense Systems Analysis (3 papers) and Military Strategy and Technology (3 papers). Matthew D. Bailey collaborates with scholars based in United States, Canada and United Kingdom. Matthew D. Bailey's co-authors include Andrew J. Schaefer, Steven M. Shechter, Mark S. Roberts, Jorge Valenzuela, Lizhi Wang, M. Mazumdar, Lisa M. Maillart, Madjid Tavana, John Bulger and Kenneth E. Wood and has published in prestigious journals such as European Journal of Operational Research, Operations Research and Decision Support Systems.

In The Last Decade

Matthew D. Bailey

19 papers receiving 366 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matthew D. Bailey United States 10 91 90 56 46 46 20 382
Xuan Vinh Doan United Kingdom 10 18 0.2× 37 0.4× 33 0.6× 78 1.7× 57 1.2× 19 375
Yongjia Song United States 16 140 1.5× 20 0.2× 24 0.4× 165 3.6× 83 1.8× 45 745
Hamed Rahimian United States 8 15 0.2× 60 0.7× 32 0.6× 139 3.0× 51 1.1× 19 612
Nilay Tanık Argon United States 15 18 0.2× 113 1.3× 261 4.7× 44 1.0× 142 3.1× 39 742
Matthew J. Robbins United States 16 28 0.3× 66 0.7× 29 0.5× 97 2.1× 125 2.7× 38 641
John A. Sokolowski United States 12 80 0.9× 37 0.4× 26 0.5× 55 1.2× 9 0.2× 56 749
Osman Y. Özaltın United States 13 17 0.2× 58 0.6× 38 0.7× 68 1.5× 107 2.3× 44 524
Lisa M. Maillart United States 17 13 0.1× 197 2.2× 87 1.6× 108 2.3× 24 0.5× 56 1.4k
Daniel Duque Colombia 12 61 0.7× 20 0.2× 7 0.1× 42 0.9× 19 0.4× 21 379

Countries citing papers authored by Matthew D. Bailey

Since Specialization
Citations

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

Fields of papers citing papers by Matthew D. Bailey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew D. Bailey. 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 Matthew D. Bailey. The network helps show where Matthew D. Bailey may publish in the future.

Co-authorship network of co-authors of Matthew D. Bailey

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew D. Bailey. A scholar is included among the top collaborators of Matthew D. Bailey 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 Matthew D. Bailey. Matthew D. Bailey 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.
Bailey, Matthew D., et al.. (2025). Muscle oxidative capacity but not specific force is greater in aerobic versus resistance trained young adults. European Journal of Applied Physiology. 125(8). 2103–2116.
2.
Clark, Andrew L., et al.. (2024). Predictive value of perfusion index (PI) on the discrepancy between oxygen saturation measurement via pulse oximetry and blood gas analysis. Journal of Emergency and Critical Care Medicine. 8. 21–21. 1 indexed citations
3.
Bailey, Matthew D., et al.. (2020). Daily Tutor Scheduling Support at Hopeful Journeys Educational Center. Bucknell Digital Commons (Bucknell University). 50(5). 287–297. 2 indexed citations
4.
Bailey, Matthew D. & David Michaels. (2019). An optimization-based DSS for student-to-teacher assignment: Classroom heterogeneity and teacher performance measures. Decision Support Systems. 119. 60–71. 10 indexed citations
5.
Bailey, Matthew D. & Maciek Nowak. (2018). MeetOpt: A multi-event coaching decision support system. Decision Support Systems. 112. 60–75. 6 indexed citations
6.
Bailey, Matthew D., et al.. (2017). Game—Introduction to Reverse Auctions: The BucknellAuto Game. INFORMS Transactions on Education. 18(2). 116–126. 2 indexed citations
7.
Bailey, Matthew D., et al.. (2015). StratBAM: A Discrete-Event Simulation Model to Support Strategic Hospital Bed Capacity Decisions. Journal of Medical Systems. 39(10). 130–130. 38 indexed citations
8.
Bailey, Matthew D. & Michael J. Fry. (2010). What Are the Odds? A Structured Approach for Unstructured Problems. INFORMS Transactions on Education. 10(2). 45–52. 2 indexed citations
9.
Bailey, Matthew D., et al.. (2010). Eliciting Patients' Revealed Preferences: An Inverse Markov Decision Process Approach. Decision Analysis. 7(4). 358–365. 31 indexed citations
10.
Tavana, Madjid, et al.. (2009). Dynamic air tasking evaluation in a simulated network-centric battlespace. International Journal of Operational Research. 5(1). 1–1. 4 indexed citations
11.
Bailey, Matthew D., et al.. (2008). Modeling hospital discharge policies for patients with pneumonia-related sepsis. IIE Transactions. 40(9). 853–860. 11 indexed citations
12.
Shechter, Steven M., Matthew D. Bailey, & Andrew J. Schaefer. (2008). A modeling framework for replacing medical therapies. IIE Transactions. 40(9). 861–869. 9 indexed citations
13.
Shechter, Steven M., Matthew D. Bailey, Andrew J. Schaefer, & Mark S. Roberts. (2008). The Optimal Time to Initiate HIV Therapy Under Ordered Health States. Operations Research. 56(1). 20–33. 106 indexed citations
14.
Shechter, Steven M., Matthew D. Bailey, & Andrew J. Schaefer. (2008). Replacing nonidentical vital components to extend system life. Naval Research Logistics (NRL). 55(7). 700–703. 3 indexed citations
15.
Bailey, Matthew D., et al.. (2008). Shortest path network interdiction with asymmetric information. Networks. 52(3). 133–140. 85 indexed citations
16.
Tavana, Madjid, et al.. (2008). A multi-criteria vehicle-target allocation assessment model for network-centric Joint Air Operations. International Journal of Operational Research. 3(3). 235–235. 11 indexed citations
17.
Bailey, Matthew D., et al.. (2006). Communication Role Allocation for Joint Air Operations in a Network-Centric Environment. SSRN Electronic Journal. 3 indexed citations
18.
Wang, Lizhi, M. Mazumdar, Matthew D. Bailey, & Jorge Valenzuela. (2006). Oligopoly models for market price of electricity under demand uncertainty and unit reliability. European Journal of Operational Research. 181(3). 1309–1321. 35 indexed citations
19.
Mazumdar, M., et al.. (2005). A stochastic cournot model for market price of electricity. IEEE Power Engineering Society General Meeting, 2005. 2479–2483. 2 indexed citations
20.
Bailey, Matthew D., Steven M. Shechter, & Andrew J. Schaefer. (2005). SPAR: stochastic programming with adversarial recourse. Operations Research Letters. 34(3). 307–315. 21 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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