Hani Doss

2.5k citations
45 papers · 1.7k indexed · h-index 19

Impact in

Papers in

    • Statistical Methods and Inference 23
    • Statistical Methods and Bayesian Inference 16
    • Statistical Distribution Estimation and Applications 9
    • Markov Chains and Monte Carlo Methods 5
    • Bayesian Methods and Mixture Models 19
    • Gaussian Processes and Bayesian Inference 3

Hani Doss

44 papers receiving 1.6k citations

Peers

Hani Doss
Comparison fields: 5 of 170
  • Geriatrics and Gerontology 252
  • Statistics and Probability 515
  • Artificial Intelligence 401
  • Pharmacology 198
  • Physiology 264
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Citations per field
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Citations per year

Countries citing papers authored by Hani Doss

Since Specialization
Citations

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

Fields of papers citing papers by Hani Doss

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Hani Doss, 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 Hani Doss Line = papers co-authored together Hani Doss links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005337
2 2014264
3 2000166
4 200587
5 200579
6 201475
7 199462
8 200559
9 200351
10 199649
11 199346
12 199245
13 199538
14 201836
15 200032
16 198528
17 198920
18 198520
19 199319
20 199917

About Hani Doss

Hani Doss is a scholar working on Statistics and Probability, Artificial Intelligence, Statistics, Probability and Uncertainty, Demography and Molecular Biology, having authored 45 papers that have together received 1.7k indexed citations. Recurring topics across this work include Statistical Methods and Inference (23 papers), Bayesian Methods and Mixture Models (19 papers), Statistical Methods and Bayesian Inference (16 papers), Statistical Distribution Estimation and Applications (9 papers), Markov Chains and Monte Carlo Methods (5 papers), Gaussian Processes and Bayesian Inference (3 papers), Insurance, Mortality, Demography, Risk Management (3 papers) and Reliability and Maintenance Optimization (2 papers). The work is most often cited by research in Geriatrics and Gerontology (252 citations), Statistics and Probability (515 citations), Artificial Intelligence (401 citations), Pharmacology (198 citations) and Physiology (264 citations). Hani Doss has collaborated with scholars based in United States, Taiwan and Netherlands. Frequent co-authors include Randall E. Harris, Deborah Doss, Dennis K. Pearl, Shuying Li, Deborah Burr, Todd M. Manini, Richard D. Gill, Yufeng Liu, Xiaotong Shen and Gang Li. Their work appears in journals such as The Annals of Statistics, Journal of the American Statistical Association, Journal of Computational and Graphical Statistics, Journal of Applied Probability and Journal of the Royal Statistical Society Series B (Statistical Methodology).

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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