Richard Halpert

8 papers receiving 549 citations

Richard Halpert's Hit Papers

Automated optimized parameters for T-distributed stochastic neighbor embedding improve visualization and analysis of large datasets 2019 · 409 citations
4090+2+4Years since publication100200300400

Peers

Richard Halpert
Comparison fields: 5 of 135
  • Parasitology 47
  • Biophysics 37
  • Immunology 81
  • Artificial Intelligence 96
  • Genetics 20
Replace Jason Xu with:
Jason Xu United States
Shannon Quinn United States
Tony Sun United States
Nicola Pezzotti Netherlands
Josef Špidlen Canada
Paul Rosenthal Germany
Jennifer M. Hill United States
Jinming Zhao China
Lange Germany
Bahr Gf United States
Richard Halpert relative to Jason Xu United States Jason Xu's profile →
Citations per field
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Jason Xu · 1×
Citations per year

Countries citing papers authored by Richard Halpert

Since Specialization
Citations

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

Fields of papers citing papers by Richard Halpert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

8 of 8 papers shown
#Work
1
Automated optimized parameters for T-distributed stochastic neighbor embedding improve visualization and analysis of large datasets
Hit paper breakdown →
2019409
2 201675
3 198824
4 201424
5 202124
6 20164
7 20143
8 20161

About Richard Halpert

Richard Halpert is a scholar working on Computer Networks and Communications, Artificial Intelligence, Molecular Biology, Biophysics and Genetics, having authored 8 papers that have together received 564 indexed citations. Recurring topics across this work include Logic, Reasoning, and Knowledge (3 papers), Semantic Web and Ontologies (3 papers), Advanced Fluorescence Microscopy Techniques (2 papers), Advanced Database Systems and Queries (2 papers), Cell Image Analysis Techniques (2 papers), Single-cell and spatial transcriptomics (2 papers), Iron Metabolism and Disorders (1 paper) and Vector-borne infectious diseases (1 paper). The work is most often cited by research in Parasitology (47 citations), Biophysics (37 citations), Immunology (81 citations), Artificial Intelligence (96 citations) and Genetics (20 citations). Richard Halpert has collaborated with scholars based in United States, Belgium and United Kingdom. Frequent co-authors include Josef Špidlen, Anna C. Belkina, Jennifer Snyder‐Cappione, Rina Anno, Jean-Noël Billaud, Andrea Swei, Jérôme Bouquet, Chris Cheadle, John N. Aucott and Alison W. Rebman. Their work appears in journals such as Nature Communications, mBio, Gynecologic Oncology, American Journal of Obstetrics and Gynecology and Lecture notes in computer science.

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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