Christopher Ré

5.4k total citations · 2 hit papers
47 papers, 2.3k citations indexed

About

Christopher Ré is a scholar working on Artificial Intelligence, Molecular Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Christopher Ré has authored 47 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 9 papers in Molecular Biology and 8 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Christopher Ré's work include Topic Modeling (6 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and Data Quality and Management (6 papers). Christopher Ré is often cited by papers focused on Topic Modeling (6 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and Data Quality and Management (6 papers). Christopher Ré collaborates with scholars based in United States, United Kingdom and Canada. Christopher Ré's co-authors include Daniel L. Rubin, Russ B. Altman, M Snyder, Kun‐Hsing Yu, Gerald J. Berry, Ce Zhang, Ihab F. Ilyas, Theodoros Rekatsinas, Xu Chu and Jared Dunnmon and has published in prestigious journals such as Science, Nature Communications and Bioinformatics.

In The Last Decade

Christopher Ré

45 papers receiving 2.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features

2016 680 citations Kun‐Hsing Yu, Ce Zhang et al. Nature Communications profile →
Sequence modeling and design from molecular to genome scale with Evo

2024 127 citations Christopher Ré et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Christopher Ré United States	19	1.3k	677	398	260	244	47	2.3k
Ce Zhang Switzerland	28	2.0k 1.6×	423 0.6×	289 0.7×	232 0.9×	151 0.6×	103	3.3k
Themis P. Exarchos Greece	19	1.1k 0.9×	654 1.0×	719 1.8×	45 0.2×	285 1.2×	98	3.2k
Jie Tang China	34	1.1k 0.9×	498 0.7×	390 1.0×	221 0.8×	380 1.6×	172	4.2k
Κωνσταντίνα Κούρου Greece	10	905 0.7×	570 0.8×	574 1.4×	43 0.2×	240 1.0×	31	2.3k
William Hsu United States	24	561 0.4×	794 1.2×	260 0.7×	62 0.2×	714 2.9×	188	2.5k
Ashish Sharma United States	25	1.1k 0.9×	711 1.1×	196 0.5×	34 0.1×	392 1.6×	81	2.6k
Michal Rosen‐Zvi Israel	19	1.7k 1.3×	218 0.3×	281 0.7×	109 0.4×	64 0.3×	56	2.8k
Tahsin Kurç United States	34	2.0k 1.6×	1.3k 1.9×	613 1.5×	64 0.2×	273 1.1×	219	4.9k
Hongmin Cai China	27	912 0.7×	906 1.3×	398 1.0×	25 0.1×	149 0.6×	200	3.0k
Chen Lin China	27	984 0.8×	143 0.2×	976 2.5×	96 0.4×	114 0.5×	158	2.4k

Countries citing papers authored by Christopher Ré

Since Specialization

Citations

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

Fields of papers citing papers by Christopher Ré

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Christopher Ré

This figure shows the co-authorship network connecting the top 25 collaborators of Christopher Ré. A scholar is included among the top collaborators of Christopher Ré 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 Christopher Ré. Christopher Ré is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Ré, Christopher, Brian W. Roberts, Matthew Salzman, et al.. (2021). Injection Drug Use and Healthcare Utilization in Patients Newly Diagnosed With HIV. Journal of Addiction Medicine. 16(3). 340–345. 2 indexed citations

Goel, Karan, Albert Gu, Yixuan Li, & Christopher Ré. (2021). Model Patching: Closing the Subgroup Performance Gap with Data Augmentation. arXiv (Cornell University). 3 indexed citations

Chen, Beidi, et al.. (2021). Scatterbrain: Unifying Sparse and Low-rank Attention. neural information processing systems. 34. 14 indexed citations

Hooper, Sarah, Jared Dunnmon, Matthew P. Lungren, et al.. (2021). Impact of Upstream Medical Image Processing on Downstream Performance of a Head CT Triage Neural Network. Radiology Artificial Intelligence. 3(4). e200229–e200229. 7 indexed citations

Yu, Kun‐Hsing, Feiran Wang, Gerald J. Berry, et al.. (2020). Classifying non-small cell lung cancer types and transcriptomic subtypes using convolutional neural networks. Journal of the American Medical Informatics Association. 27(5). 757–769. 82 indexed citations

Córdova‐Palomera, Aldo, Catherine Tcheandjieu, Jason Fries, et al.. (2020). Cardiac Imaging of Aortic Valve Area From 34 287 UK Biobank Participants Reveals Novel Genetic Associations and Shared Genetic Comorbidity With Multiple Disease Phenotypes. Circulation Genomic and Precision Medicine. 13(6). e003014–e003014. 10 indexed citations

Chami, Ines, et al.. (2020). From Trees to Continuous Embeddings and Back: Hyperbolic Hierarchical Clustering.. arXiv (Cornell University). 33. 15065–15076. 1 indexed citations

Dunnmon, Jared, et al.. (2020). Comparison of segmentation-free and segmentation-dependent computer-aided diagnosis of breast masses on a public mammography dataset. Journal of Biomedical Informatics. 113. 103656–103656. 11 indexed citations

Saab, Khaled, Jared Dunnmon, Christopher Ré, Daniel L. Rubin, & Christopher Lee‐Messer. (2020). Weak supervision as an efficient approach for automated seizure detection in electroencephalography. npj Digital Medicine. 3(1). 59–59. 47 indexed citations

10.

Kuleshov, Volodymyr, Jialin Ding, Braden Hancock, et al.. (2019). A machine-compiled database of genome-wide association studies. Nature Communications. 10(1). 3341–3341. 12 indexed citations

11.

Fries, Jason, Paroma Varma, Ke Xiao, et al.. (2019). Weakly supervised classification of aortic valve malformations using unlabeled cardiac MRI sequences. Nature Communications. 10(1). 3111–3111. 56 indexed citations

12.

Ratner, Alexander, Braden Hancock, & Christopher Ré. (2019). The Role of Massively Multi-Task and Weak Supervision in Software 2.0.. Conference on Innovative Data Systems Research. 10 indexed citations

13.

Ratner, Alexander, Stephen H. Bach, Henry R. Ehrenberg, et al.. (2019). Snorkel: rapid training data creation with weak supervision. The VLDB Journal. 29(2-3). 709–730. 201 indexed citations

14.

Ratner, Alexander, et al.. (2019). Training Complex Models with Multi-Task Weak Supervision. Proceedings of the AAAI Conference on Artificial Intelligence. 33(1). 4763–4771. 76 indexed citations

15.

Ratner, Alexander, Stephen H. Bach, Henry R. Ehrenberg, et al.. (2017). Snorkel: A System for Lightweight Extraction.. Conference on Innovative Data Systems Research. 2 indexed citations

16.

Yu, Kun‐Hsing, Ce Zhang, Gerald J. Berry, et al.. (2016). Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features. Nature Communications. 7(1). 12474–12474. 680 indexed citations breakdown →

17.

Ré, Christopher, et al.. (2014). Feature Engineering for Knowledge Base Construction.. arXiv (Cornell University). 37. 26–40. 21 indexed citations

18.

Peters, Shanan E., Ce Zhang, Miron Livny, & Christopher Ré. (2014). A Machine Reading System for Assembling Synthetic Paleontological Databases. PLoS ONE. 9(12). e113523–e113523. 69 indexed citations

19.

Cafarella, Michael, et al.. (2013). Ringtail: Feature Selection For Easier Nowcasting.. 49–54. 7 indexed citations

20.

Zhang, Ce, et al.. (2013). Understanding Tables in Context Using Standard NLP Toolkits. Meeting of the Association for Computational Linguistics. 658–664. 20 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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