Emily Reif

42 total papers · 4.2k total citations
16 papers, 775 citations indexed

About

Emily Reif is a scholar working on Artificial Intelligence, Information Systems and Molecular Biology. According to data from OpenAlex, Emily Reif has authored 16 papers receiving a total of 775 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 3 papers in Information Systems and 2 papers in Molecular Biology. Recurrent topics in Emily Reif's work include Topic Modeling (9 papers), Natural Language Processing Techniques (6 papers) and Explainable Artificial Intelligence (XAI) (3 papers). Emily Reif is often cited by papers focused on Topic Modeling (9 papers), Natural Language Processing Techniques (6 papers) and Explainable Artificial Intelligence (XAI) (3 papers). Emily Reif collaborates with scholars based in United States and United Kingdom. Emily Reif's co-authors include Ann Yuan, Andy Coenen, Adam Pearce, Daphne Ippolito, Martin Wattenberg, Been Kim, Benjamín Sánchez-Lengeling, Fernanda Viégas, Michael Terry and Daniel Smilkov and has published in prestigious journals such as IEEE Transactions on Visualization and Computer Graphics, Computational Brain & Behavior and Neural Information Processing Systems.

In The Last Decade

Emily Reif

16 papers receiving 745 citations

Hit Papers

normalize citations (0→100%) normalize lifespan (0→100%) sort by overperformance

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Emily Reif	446	108	87	70	69	16	775
Nikica Hlupić	453 1.0×	68 0.6×	79 0.9×	61 0.9×	69 1.0×	17	705
Tejal Shah	338 0.8×	84 0.8×	56 0.6×	94 1.3×	30 0.4×	31	879
Vivian Liu	183 0.4×	155 1.4×	36 0.4×	62 0.9×	36 0.5×	20	640
Tarek R. Besold	447 1.0×	61 0.6×	54 0.6×	37 0.5×	56 0.8×	42	656
Anna Saranti	406 0.9×	93 0.9×	97 1.1×	55 0.8×	32 0.5×	27	766
Supriyo Chakraborty	534 1.2×	166 1.5×	40 0.5×	114 1.6×	72 1.0×	32	880
Khan Muhammad	390 0.9×	81 0.8×	131 1.5×	50 0.7×	49 0.7×	11	774
Eduardo Mosqueira-Rey	233 0.5×	57 0.5×	58 0.7×	115 1.6×	31 0.4×	31	638
Tianyu Wu	327 0.7×	47 0.4×	230 2.6×	74 1.1×	59 0.9×	8	776
Owain Evans	329 0.7×	42 0.4×	76 0.9×	57 0.8×	132 1.9×	12	686

Countries citing papers authored by Emily Reif

Since Specialization

Citations

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

Fields of papers citing papers by Emily Reif

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Emily Reif

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

All Works

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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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