Michael D. Lieberman

56 papers receiving 3.0k citations

Michael D. Lieberman's Hit Papers

TwitterStand 2009 · 473 citations
4730+5+11Years since publication100200300400

Peers

Michael D. Lieberman
Comparison fields: 5 of 160
  • Geography, Planning and Development 626
  • Signal Processing 672
  • Oncology 693
  • Transportation 182
  • Statistical and Nonlinear Physics 312
Replace Pascal Poncelet with:
Pascal Poncelet France
Nicholas Blumm United States
Kevin Y. Yip Hong Kong
Panpan Xu China
Jie Liang China
Christopher Ré United States
Xinyu Dai China
Cristina Ribeiro Portugal
Kirk Roberts United States
Zhenhua Dong China
Michael D. Lieberman relative to Pascal Poncelet France Pascal Poncelet's profile →
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Citations per year

Countries citing papers authored by Michael D. Lieberman

Since Specialization
Citations

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

Fields of papers citing papers by Michael D. Lieberman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael D. Lieberman. 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 Michael D. Lieberman. The network helps show where Michael D. Lieberman may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 57 papers — load more, or switch the sort, to bring in the rest.

#Work
1
TwitterStand
Hit paper breakdown →
2009473
2 1995465
3 1998195
4 2008150
5 2008134
6 1999131
7 1998104
8 2010100
9 199585
10 201184
11 200077
12 200876
13 200775
14 201271
15 200363
16 201160
17 201457
18 201053
19 199749
20 200345

About Michael D. Lieberman

Michael D. Lieberman is a scholar working on Signal Processing, Geography, Planning and Development, Information Systems, Oncology and Surgery, having authored 57 papers that have together received 3.1k indexed citations. Recurring topics across this work include Data Management and Algorithms (19 papers), Geographic Information Systems Studies (15 papers), Web Data Mining and Analysis (9 papers), Semantic Web and Ontologies (7 papers), Pancreatic and Hepatic Oncology Research (7 papers), Cancer Research and Treatments (5 papers), Clinical Nutrition and Gastroenterology (5 papers) and Nutrition and Health in Aging (4 papers). The work is most often cited by research in Geography, Planning and Development (626 citations), Signal Processing (672 citations), Oncology (693 citations), Transportation (182 citations) and Statistical and Nonlinear Physics (312 citations). Michael D. Lieberman has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include Hanan Samet, Jagan Sankaranarayanan, Jon Sperling, Benjamin E. Teitler, Michael A. Lindsey, Murray F. Brennan, Harold Kilburn, J.M. Daly, Thomas J. Fahey and Denis Evoy. Their work appears in journals such as Annals of Surgery, Journal of Surgical Research, Journal of Neuroscience, Journal of Thoracic and Cardiovascular Surgery and Surgery.

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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