Benjamin Ackerman

1.2k citations
22 papers · 389 · h-index 11

Impact in

Papers in

    • Advanced Causal Inference Techniques 11
    • Statistical Methods and Inference 6
    • Statistical Methods and Bayesian Inference 5
    • Statistical Methods in Clinical Trials 2
    • HIV/AIDS Research and Interventions 4

Benjamin Ackerman

19 papers receiving 385 citations

Peers

Benjamin Ackerman
Comparison fields: 5 of 85
  • Statistics and Probability 88
  • Infectious Diseases 166
  • Molecular Medicine 18
  • Social Psychology 72
  • Epidemiology 101
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Citations per year

Countries citing papers authored by Benjamin Ackerman

Since Specialization
Citations

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

Fields of papers citing papers by Benjamin Ackerman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017114
2 202173
3 201742
4 202023
5 201823
6 201619
7 201518
8 201817
9 201817
10 202110
11 201910
12 20207
13 20215
14
Global interruptions in HIV prevention and treatment services as a result of the response to COVID-19: Results from a social media-based sample of men who have sex with men
20204
15 20252
16 20192
17 20241
18 20201
19 20201
20 20240

About Benjamin Ackerman

Benjamin Ackerman is a scholar working on Statistics and Probability, Infectious Diseases, Artificial Intelligence, Economics and Econometrics and Sociology and Political Science, having authored 22 papers that have together received 389 indexed citations. Recurring topics across this work include Advanced Causal Inference Techniques (11 papers), Statistical Methods and Inference (6 papers), Statistical Methods and Bayesian Inference (5 papers), HIV/AIDS Research and Interventions (4 papers), Health Systems, Economic Evaluations, Quality of Life (4 papers), Immunotherapy and Immune Responses (3 papers), CAR-T cell therapy research (2 papers) and Statistical Methods in Clinical Trials (2 papers). The work is most often cited by research in Statistics and Probability (88 citations), Infectious Diseases (166 citations), Molecular Medicine (18 citations), Social Psychology (72 citations) and Epidemiology (101 citations). Benjamin Ackerman has collaborated with scholars based in United States, Japan and Eswatini. Frequent co-authors include Elizabeth A. Stuart, Stefan Baral, Daniel Westreich, Ian Schmid, Daouda Diouf, Gift Trapence, Henri Gautier Ouédraogo, Nuha Ceesay, Odette Ky‐Zerbo and Tonia Poteat. Their work appears in journals such as JAIDS Journal of Acquired Immune Deficiency Syndromes, PLoS Medicine, Journal of the International AIDS Society, Computational Statistics & Data Analysis and Research on Social Work Practice.

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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