Yoni Halpern

1.8k total citations
16 papers, 838 citations indexed

About

Yoni Halpern is a scholar working on Artificial Intelligence, Health Information Management and Molecular Biology. According to data from OpenAlex, Yoni Halpern has authored 16 papers receiving a total of 838 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 6 papers in Health Information Management and 4 papers in Molecular Biology. Recurrent topics in Yoni Halpern's work include Machine Learning in Healthcare (4 papers), Biomedical Text Mining and Ontologies (4 papers) and Topic Modeling (4 papers). Yoni Halpern is often cited by papers focused on Machine Learning in Healthcare (4 papers), Biomedical Text Mining and Ontologies (4 papers) and Topic Modeling (4 papers). Yoni Halpern collaborates with scholars based in United States and Canada. Yoni Halpern's co-authors include David Sontag, Steven Horng, Abdulhakim Tlimat, Larry Nathanson, Yacine Jernite, Nathan I. Shapiro, Timothy D. Barfoot, D. Sculley, James Atwood and Hansa Srinivasan and has published in prestigious journals such as PLoS ONE, Scientific Reports and Communications of the ACM.

In The Last Decade

Yoni Halpern

16 papers receiving 819 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yoni Halpern United States 9 489 207 141 123 62 16 838
Marie‐Christine Jaulent France 20 540 1.1× 594 2.9× 92 0.7× 283 2.3× 25 0.4× 175 1.6k
Chao Yan United States 16 310 0.6× 46 0.2× 38 0.3× 94 0.8× 82 1.3× 76 878
Abhishek Pandey India 15 279 0.6× 257 1.2× 51 0.4× 76 0.6× 89 1.4× 70 915
Alberto Lavelli Italy 19 1.3k 2.6× 544 2.6× 47 0.3× 98 0.8× 82 1.3× 86 1.8k
Yacine Jernite United States 8 1.2k 2.4× 78 0.4× 107 0.8× 39 0.3× 57 0.9× 17 1.5k
Szymon Wilk Poland 19 447 0.9× 133 0.6× 99 0.7× 213 1.7× 34 0.5× 81 986
Ahmed M. Alaa United States 20 511 1.0× 83 0.4× 118 0.8× 250 2.0× 174 2.8× 60 1.4k
Matthew B. A. McDermott United States 12 1.0k 2.1× 327 1.6× 89 0.6× 154 1.3× 421 6.8× 23 1.6k
Stephen Wu United States 20 781 1.6× 612 3.0× 77 0.5× 153 1.2× 88 1.4× 49 1.3k
Andrea Campagner Italy 22 722 1.5× 42 0.2× 119 0.8× 147 1.2× 323 5.2× 67 1.6k

Countries citing papers authored by Yoni Halpern

Since Specialization
Citations

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

Fields of papers citing papers by Yoni Halpern

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yoni Halpern

This figure shows the co-authorship network connecting the top 25 collaborators of Yoni Halpern. A scholar is included among the top collaborators of Yoni Halpern based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yoni Halpern. Yoni Halpern is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
1.
D’Amour, Alexander, Hansa Srinivasan, James Atwood, et al.. (2020). Fairness is not static. 525–534. 85 indexed citations
2.
Risteski, Andrej, et al.. (2019). Benefits of Overparameterization in Single-Layer Latent Variable Generative Models.. arXiv (Cornell University). 1 indexed citations
3.
Greenbaum, Nathaniel R., Yacine Jernite, Yoni Halpern, et al.. (2019). Improving documentation of presenting problems in the emergency department using a domain-specific ontology and machine learning-driven user interfaces. International Journal of Medical Informatics. 132. 103981–103981. 25 indexed citations
4.
Tlimat, Abdulhakim, Yoni Halpern, Edward Ullman, et al.. (2019). Derivation and validation of a machine learning record linkage algorithm between emergency medical services and the emergency department. Journal of the American Medical Informatics Association. 27(1). 147–153. 16 indexed citations
5.
Halpern, Yoni, et al.. (2019). Empirical Study of the Benefits of Overparameterization in Learning Latent Variable Models. arXiv (Cornell University). 1. 1211–1219. 3 indexed citations
6.
Arora, Sanjeev, Rong Ge, Yoni Halpern, et al.. (2018). Learning topic models -- provably and efficiently. Communications of the ACM. 61(4). 85–93. 8 indexed citations
7.
Mitchell, Michael, et al.. (2018). Text Embeddings Contain Bias. Here's Why That Matters.. 3 indexed citations
8.
Halpern, Yoni, et al.. (2017). Learning a Health Knowledge Graph from Electronic Medical Records. Scientific Reports. 7(1). 5994–5994. 235 indexed citations
9.
Horng, Steven, David Sontag, Yoni Halpern, et al.. (2017). Creating an automated trigger for sepsis clinical decision support at emergency department triage using machine learning. PLoS ONE. 12(4). e0174708–e0174708. 202 indexed citations
10.
Banda, Juan M., Yoni Halpern, David Sontag, & Nigam H. Shah. (2017). Electronic phenotyping with APHRODITE and the Observational Health Sciences and Informatics (OHDSI) data network.. PubMed. 2017. 48–57. 44 indexed citations
11.
Ovadia, Yaniv, Yoni Halpern, Dilip Krishnan, et al.. (2017). Learning to Count Mosquitoes for the Sterile Insect Technique. 1943–1949. 3 indexed citations
12.
Halpern, Yoni, et al.. (2016). Electronic medical record phenotyping using the anchor and learn framework. Journal of the American Medical Informatics Association. 23(4). 731–740. 96 indexed citations
13.
Halpern, Yoni, et al.. (2016). Contextual Prediction Models for Speech Recognition. 2338–2342. 4 indexed citations
14.
Halpern, Yoni, et al.. (2014). Using Anchors to Estimate Clinical State without Labeled Data.. PubMed. 2014. 606–15. 32 indexed citations
15.
Halpern, Yoni & David Sontag. (2013). Unsupervised learning of noisy-or Bayesian networks. Uncertainty in Artificial Intelligence. 272–281. 7 indexed citations
16.
Halpern, Yoni, et al.. (2011). The UTIAS multi-robot cooperative localization and mapping dataset. The International Journal of Robotics Research. 30(8). 969–974. 74 indexed citations

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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