Greg Grudic

885 total citations
25 papers, 638 citations indexed

About

Greg Grudic is a scholar working on Surgery, Cardiology and Cardiovascular Medicine and Computer Vision and Pattern Recognition. According to data from OpenAlex, Greg Grudic has authored 25 papers receiving a total of 638 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Surgery, 8 papers in Cardiology and Cardiovascular Medicine and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Greg Grudic's work include Hemodynamic Monitoring and Therapy (8 papers), Non-Invasive Vital Sign Monitoring (6 papers) and Heart Rate Variability and Autonomic Control (5 papers). Greg Grudic is often cited by papers focused on Hemodynamic Monitoring and Therapy (8 papers), Non-Invasive Vital Sign Monitoring (6 papers) and Heart Rate Variability and Autonomic Control (5 papers). Greg Grudic collaborates with scholars based in United States and Thailand. Greg Grudic's co-authors include Jane Mulligan, Víctor A. Convertino, Steven L. Moulton, Steve Moulton, Jane Mulligan, Camille L. Stewart, Carmen Hinojosa‐Laborde, Rajeev Alur, John Spletzer and Camillo J. Taylor and has published in prestigious journals such as The FASEB Journal, Journal of Applied Physiology and The International Journal of Robotics Research.

In The Last Decade

Greg Grudic

25 papers receiving 606 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Greg Grudic United States 12 246 217 168 142 126 25 638
Gregory Z. Grudić United States 13 146 0.6× 116 0.5× 103 0.6× 97 0.7× 68 0.5× 36 549
Yuichiro Toda Japan 15 75 0.3× 53 0.2× 79 0.5× 54 0.4× 113 0.9× 100 743
Dong Woo Seo South Korea 18 364 1.5× 245 1.1× 34 0.2× 59 0.4× 112 0.9× 63 1.1k
Steve Moulton United States 8 126 0.5× 78 0.4× 307 1.8× 63 0.4× 34 0.3× 21 810
Yeong Shiong Chiew New Zealand 24 213 0.9× 211 1.0× 462 2.8× 107 0.8× 308 2.4× 130 1.7k
Quan Ding United States 14 285 1.2× 25 0.1× 266 1.6× 200 1.4× 21 0.2× 49 830
Zhi Xiong Koh Singapore 16 127 0.5× 257 1.2× 129 0.8× 298 2.1× 34 0.3× 37 754
R. Ramanathan India 12 123 0.5× 28 0.1× 21 0.1× 64 0.5× 21 0.2× 69 845
Lloyd Greenwald United States 12 261 1.1× 302 1.4× 19 0.1× 26 0.2× 129 1.0× 43 861
Sandy Weininger United States 12 189 0.8× 38 0.2× 178 1.1× 76 0.5× 15 0.1× 38 509

Countries citing papers authored by Greg Grudic

Since Specialization
Citations

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

Fields of papers citing papers by Greg Grudic

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Greg Grudic

This figure shows the co-authorship network connecting the top 25 collaborators of Greg Grudic. A scholar is included among the top collaborators of Greg Grudic 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 Greg Grudic. Greg Grudic 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.
Metzger, Anja, Jane Mulligan, & Greg Grudic. (2018). Development of a Non-invasive Cerebrovascular Status Algorithm to Estimate Cerebral Perfusion Pressure and Intracranial Pressure in a Porcine Model of Focal Brain Injury. Military Medicine. 183(suppl_1). 119–123. 2 indexed citations
2.
Choi, Young Mee, et al.. (2017). Noninvasive monitoring of physiologic compromise in acute appendicitis: New insight into an old disease. Journal of Pediatric Surgery. 53(2). 241–246. 9 indexed citations
3.
Moulton, Steven L., Jane Mulligan, Anon Srikiatkhachorn, et al.. (2016). State-of-the-art monitoring in treatment of dengue shock syndrome: a case series. Journal of Medical Case Reports. 10(1). 233–233. 20 indexed citations
4.
Stewart, Camille L., et al.. (2016). The Compensatory Reserve Index Following Injury. Shock. 46(3S). 61–67. 33 indexed citations
5.
Stewart, Camille L., et al.. (2016). Compensatory Reserve for Early and Accurate Prediction of Hemodynamic Compromise: Case Studies for Clinical Utility in Acute Care and Physical Performance. Journal of Special Operations Medicine. 16(1). 6–6. 32 indexed citations
6.
Hinojosa‐Laborde, Carmen, Jane Mulligan, Greg Grudic, & Víctor A. Convertino. (2015). Comparison of Compensatory Reserve Index during Lower Body Negative Pressure and Hemorrhage. The FASEB Journal. 29(S1). 1 indexed citations
7.
Stewart, Camille L., Jane Mulligan, Greg Grudic, Víctor A. Convertino, & Steven L. Moulton. (2014). Detection of low-volume blood loss. The Journal of Trauma: Injury, Infection, and Critical Care. 77(6). 892–898. 55 indexed citations
8.
Stewart, Camille L., Jane Mulligan, Greg Grudic, Laura Pyle, & Steven L. Moulton. (2014). A Noninvasive Computational Method for Fluid Resuscitation Monitoring in Pediatric Burns. Journal of Burn Care & Research. 36(1). 145–150. 11 indexed citations
9.
Wampler, David, Craig Manifold, Greg Grudic, et al.. (2013). Promoting early diagnosis of hemodynamic instability during simulated hemorrhage with the use of a real-time decision-assist algorithm. The Journal of Trauma: Injury, Infection, and Critical Care. 75(2). S184–S189. 20 indexed citations
10.
Moulton, Steven L., Jane Mulligan, Greg Grudic, & Víctor A. Convertino. (2013). Running on empty? The compensatory reserve index. The Journal of Trauma: Injury, Infection, and Critical Care. 75(6). 1053–1059. 85 indexed citations
11.
Convertino, Víctor A., Greg Grudic, Jane Mulligan, & Steve Moulton. (2013). Estimation of individual-specific progression to impending cardiovascular instability using arterial waveforms. Journal of Applied Physiology. 115(8). 1196–1202. 99 indexed citations
12.
13.
Otte, Michael & Greg Grudic. (2009). Extracting paths from fields built with linear interpolation. 4406–4413. 5 indexed citations
14.
Mulligan, Jane, et al.. (2009). Learning terrain segmentation with classifier ensembles for autonomous robot navigation in unstructured environments. Journal of Field Robotics. 26(2). 145–175. 37 indexed citations
15.
Bauer, Kevin, Damon McCoy, Eric Anderson, et al.. (2009). The Directional Attack on Wireless Localization -or- How to Spoof Your Location with a Tin Can. 1–6. 13 indexed citations
16.
Mulligan, Jane, et al.. (2007). Long-Term learning using multiple models for outdoor autonomous robot navigation. 14. 3158–3165. 10 indexed citations
17.
Bates, Adam, et al.. (2007). Using Binary Classifiers to Augment Stereo Vision for Enhanced Autonomous Robot Navigation ; CU-CS-1027-07. CU Scholar (University of Colorado Boulder). 4 indexed citations
18.
Grudic, Greg & Jane Mulligan. (2005). Topological Mapping with Multiple Visual Manifolds. 9 indexed citations
19.
Fierro, Rafael, Aveek Das, John Spletzer, et al.. (2002). A Framework and Architecture for Multi-Robot Coordination. The International Journal of Robotics Research. 21(10). 977–995. 8 indexed citations
20.
Grudic, Greg & Lyle Ungar. (2001). Exploiting multiple secondary reinforcers in policy gradient reinforcement learning. 965–970. 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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