David Newman

1.5k total citations · 1 hit paper
29 papers, 1.1k citations indexed

About

David Newman is a scholar working on Animal Science and Zoology, Analytical Chemistry and Small Animals. According to data from OpenAlex, David Newman has authored 29 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Animal Science and Zoology, 7 papers in Analytical Chemistry and 4 papers in Small Animals. Recurrent topics in David Newman's work include Meat and Animal Product Quality (12 papers), Spectroscopy and Chemometric Analyses (7 papers) and Animal Behavior and Welfare Studies (4 papers). David Newman is often cited by papers focused on Meat and Animal Product Quality (12 papers), Spectroscopy and Chemometric Analyses (7 papers) and Animal Behavior and Welfare Studies (4 papers). David Newman collaborates with scholars based in United States, China and United Kingdom. David Newman's co-authors include George Em Karniadakis, Timothy Baldwin, Jey Han Lau, Xin Sun, J. M. Young, G. E. Karniadakis, Xiaochan Wang, Yinyan Shi, Zhichao Hu and Weimin Ding and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Fluid Mechanics and Journal of Nutrition.

In The Last Decade

David Newman

29 papers receiving 988 citations

Hit Papers

align trajectories

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.

Machine Reading Tea Leaves: Automatically Evaluating Topic Coherence and Topic Model Quality

2014 325 citations Jey Han Lau, David Newman et al. profile →

Peers

David Newman

CM

AI

CSE

EE

ASZ

Yunfei Xu China

Douglas G. Simpson United States

Dimitris C. Psichogios United States

Lu Jiang China

Hui‐Fuang Ng Malaysia

A.P. de Weijer Netherlands

Wu Ai China

Hans‐Georg Müller United States

Robert P. Cogdill United States

Geurt Jongbloed Netherlands

Yunfei Xu China

David Newman

20 ×0.1

CM

232 ×0.8

AI

57 ×0.3

CSE

64 ×0.4

EE

22 ×0.2

ASZ

Citations per year, relative to David Newman David Newman (= 1×) peers Yunfei Xu

Countries citing papers authored by David Newman

Since Specialization

Citations

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

Fields of papers citing papers by David Newman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Newman

This figure shows the co-authorship network connecting the top 25 collaborators of David Newman. A scholar is included among the top collaborators of David Newman 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 David Newman. David Newman 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

1.

Shi, Yinyan, Xiaochan Wang, Md Saidul Borhan, et al.. (2021). A Review on Meat Quality Evaluation Methods Based on Non-Destructive Computer Vision and Artificial Intelligence Technologies. Food Science of Animal Resources. 41(4). 563–588. 61 indexed citations

2.

Young, J. M., et al.. (2020). A ramp in nursery housing affects nursery pig behavior and speeds loading of market hogs. Applied Animal Science. 36(4). 574–581. 4 indexed citations

3.

Shi, Yinyan, Xin Sun, Xiaochan Wang, et al.. (2019). Numerical simulation and field tests of minimum-tillage planter with straw smashing and strip laying based on EDEM software. Computers and Electronics in Agriculture. 166. 105021–105021. 71 indexed citations

4.

Newman, David, S. Beauchamp, J. M. Young, et al.. (2019). National Retail Benchmarking for Pork 2018. Meat and Muscle Biology. 3(2). 1 indexed citations

5.

Sun, Xin, et al.. (2018). Predicting pork loin intramuscular fat using computer vision system. Meat Science. 143. 18–23. 40 indexed citations

6.

Sun, Xin, et al.. (2018). Prediction of pork loin quality using online computer vision system and artificial intelligence model. Meat Science. 140. 72–77. 69 indexed citations

7.

Sun, Xin, et al.. (2016). Prediction of Pork Color Grade using Image Two-tone Color Ratio Features and Support Vector Machine. Advance Journal of Food Science and Technology. 11(9). 593–598. 3 indexed citations

8.

Sun, Xin, et al.. (2016). 143 Predicting pork color scores using machine vision and support vector machine technologies. Journal of Animal Science. 94(suppl_2). 67–67. 1 indexed citations

9.

Moeller, S. J., et al.. (2016). 127 Pork quality: 2015 national retail benchmarking study. Journal of Animal Science. 94(suppl_2). 59–60. 5 indexed citations

10.

Sun, Xin, et al.. (2015). Prediction of pork color attributes using computer vision system. Meat Science. 113. 62–64. 39 indexed citations

11.

Shappell, Nancy W., et al.. (2014). Consumption of Ground Beef Obtained from Cattle That Had Received Steroidal Growth Promotants Does Not Trigger Early Onset of Estrus in Prepubertal Pigs. Journal of Nutrition. 144(11). 1718–1724. 3 indexed citations

12.

Newman, David, et al.. (2014). Effect of Season, Transport Length, Deck Location, and Lairage Length on Pork Quality and Blood Cortisol Concentrations of Market Hogs. Animals. 4(4). 627–642. 4 indexed citations

13.

Lau, Jey Han, David Newman, & Timothy Baldwin. (2014). Machine Reading Tea Leaves: Automatically Evaluating Topic Coherence and Topic Model Quality. 530–539. 325 indexed citations breakdown →

14.

Newman, David, et al.. (2000). How silent is perioperative myocardial ischemia? a hemodynamic, electrocardiographic, and biochemical study in patients undergoing coronary artery bypass graft surgery. Journal of Cardiothoracic and Vascular Anesthesia. 14(2). 144–150. 7 indexed citations

15.

Price, Christopher P., et al.. (1999). A Rapid and Sensitive Automated Light Scattering Immunoassay for Serum C-Reactive Protein and the Definition of a Reference Range in Healthy Blood Donors. Clinical Chemistry and Laboratory Medicine (CCLM). 37(2). 109–113. 10 indexed citations

16.

Thakkar, Hansa, et al.. (1997). A Simple, Automated, Nonextraction Assay for Serum Digoxin Using Particle-Enhanced Immunoassay. Therapeutic Drug Monitoring. 19(1). 108–111. 3 indexed citations

17.

Newman, David & George Em Karniadakis. (1997). A direct numerical simulation study of flow past a freely vibrating cable. Journal of Fluid Mechanics. 344. 95–136. 223 indexed citations

18.

Thompson, J., et al.. (1997). Kinetics and proposed mechanism of the reaction of an immunoinhibition, particle-enhanced immunoassay. Clinical Chemistry. 43(12). 2384–2389. 18 indexed citations

19.

Newman, David & G. E. Karniadakis. (1996). SIMULATIONS OF FLOW OVER A FLEXIBLE CABLE: A COMPARISON OF FORCED AND FLOW-INDUCED VIBRATION. Journal of Fluids and Structures. 10(5). 439–453. 64 indexed citations

20.

Newman, David, et al.. (1974). The influence of the solvent on organic reactivity. Part I. Kinetics and mechanism of the reactions of carboxylic acids with diazodiphenylmethane in donor aprotic solvents. Journal of the Chemical Society Perkin Transactions 2. 962–962. 22 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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