Gabriel Lang

3.3k citations
78 papers · 1.7k · h-index 21

Impact in

  • Finance top 2%
    • Financial Risk and Volatility Modeling
    • Stochastic processes and financial applications
    • Statistical Methods and Inference

Papers in

Gabriel Lang

74 papers receiving 1.7k citations

Peers

Gabriel Lang
Comparison fields: 5 of 160
  • Finance 365
  • Statistics and Probability 191
  • Health, Toxicology and Mutagenesis 168
  • Economics and Econometrics 271
  • Anesthesiology and Pain Medicine 47
Replace Liqun Wang with:
Liqun Wang China
Amy Racine-Poon Switzerland
Donald A. Pierce United States
Eugene F. Schuster United States
Carlo Berzuini Italy
Fred Godtliebsen Norway
Dennis D. Cox United States
M. C. K. Tweedie United Kingdom
M. Bhaskara Rao United States
Jim E. Griffin United Kingdom
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Citations per field
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Citations per year

Countries citing papers authored by Gabriel Lang

Since Specialization
Citations

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

Fields of papers citing papers by Gabriel Lang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Gabriel Lang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Gabriel Lang Line = papers co-authored together Gabriel Lang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 78 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1997242
2 2007188
3 2012111
4 2008106
5 201793
6 200991
7 201862
8 200858
9 201457
10 201056
11 201354
12 201144
13 200044
14 201143
15 202133
16 201729
17 200829
18 201824
19 201922
20 200222

About Gabriel Lang

Gabriel Lang is a scholar working on Surgery, Pulmonary and Respiratory Medicine, Oncology, Finance and Economics and Econometrics, having authored 78 papers that have together received 1.7k indexed citations. Recurring topics across this work include Financial Risk and Volatility Modeling (9 papers), Gallbladder and Bile Duct Disorders (9 papers), Pancreatic and Hepatic Oncology Research (8 papers), Stochastic processes and financial applications (5 papers), Pancreatitis Pathology and Treatment (5 papers), Esophageal and GI Pathology (5 papers), Gastric Cancer Management and Outcomes (5 papers) and Complex Systems and Time Series Analysis (5 papers). The work is most often cited by research in Finance (365 citations), Statistics and Probability (191 citations), Health, Toxicology and Mutagenesis (168 citations), Economics and Econometrics (271 citations) and Anesthesiology and Pain Medicine (47 citations). Gabriel Lang has collaborated with scholars based in United States, France and French Guiana. Frequent co-authors include Jacques Istas, Paul Doukhan, Éric Marcon, Liliana Moreno‐Vinasco, Joe G. N. Garcia, Sana Louhichi, Clémentine Prieur, Jérôme Dedecker, Viswanathan Natarajan and Vladimir Kushnir. Their work appears in journals such as Gastrointestinal Endoscopy, PLoS ONE, Surgical Endoscopy, The American Journal of Gastroenterology and American Journal of Respiratory Cell and Molecular Biology.

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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