Emma Strubell

3.4k total citations · 3 hit papers
40 papers, 1.1k citations indexed

About

Emma Strubell is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Emma Strubell has authored 40 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Artificial Intelligence, 8 papers in Computer Vision and Pattern Recognition and 3 papers in Information Systems. Recurrent topics in Emma Strubell's work include Topic Modeling (24 papers), Natural Language Processing Techniques (18 papers) and Multimodal Machine Learning Applications (6 papers). Emma Strubell is often cited by papers focused on Topic Modeling (24 papers), Natural Language Processing Techniques (18 papers) and Multimodal Machine Learning Applications (6 papers). Emma Strubell collaborates with scholars based in United States, United Kingdom and Germany. Emma Strubell's co-authors include Andrew McCallum, Ananya Ganesh, Alexandra Sasha Luccioni, Lynn H. Kaack, Priya L. Donti, David Rolnick, George Kamiya, Felix Creutzig, Yacine Jernite and Elsa Olivetti and has published in prestigious journals such as Nature, Nature Climate Change and Journal of Theoretical Biology.

In The Last Decade

Emma Strubell

34 papers receiving 1.1k 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.

Energy and Policy Considerations for Modern Deep Learning Research

2020 323 citations Emma Strubell, Andrew McCallum et al. profile →
Aligning artificial intelligence with climate change mitigation

2022 238 citations Lynn H. Kaack, Priya L. Donti et al. Nature Climate Change profile →
Power Hungry Processing: Watts Driving the Cost of AI Deployment?

2024 92 citations Alexandra Sasha Luccioni, Yacine Jernite et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Emma Strubell United States	11	369	219	212	100	89	40	1.1k
Xianghua Li China	24	323 0.9×	208 0.9×	118 0.6×	116 1.2×	49 0.6×	115	1.4k
Silvano Cincotti Italy	26	110 0.3×	302 1.4×	72 0.3×	65 0.7×	18 0.2×	115	2.2k
John Li United States	16	469 1.3×	146 0.7×	267 1.3×	124 1.2×	7 0.1×	43	1.1k
Shuo Xu China	19	562 1.5×	42 0.2×	58 0.3×	185 1.9×	67 0.8×	100	1.5k
Jingping Liu China	12	514 1.4×	39 0.2×	46 0.2×	118 1.2×	19 0.2×	64	1.2k
Zhifu Tao China	24	331 0.9×	224 1.0×	161 0.8×	41 0.4×	329 3.7×	73	1.5k
Changchang Liu China	16	277 0.8×	40 0.2×	86 0.4×	142 1.4×	26 0.3×	50	903
Qing Zhu China	18	213 0.6×	268 1.2×	31 0.1×	85 0.8×	16 0.2×	81	1.2k
Jesse Dodge United States	11	1.1k 3.0×	159 0.7×	22 0.1×	133 1.3×	28 0.3×	27	1.8k

Countries citing papers authored by Emma Strubell

Since Specialization

Citations

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

Fields of papers citing papers by Emma Strubell

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Emma Strubell

This figure shows the co-authorship network connecting the top 25 collaborators of Emma Strubell. A scholar is included among the top collaborators of Emma Strubell 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 Emma Strubell. Emma Strubell 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

1.

Zhang, Zhisong, et al.. (2025). Text Mining for Process–Structure–Properties Relationships in Metals. Integrating materials and manufacturing innovation. 14(4). 643–656.

2.

Brooks, David, Arthur van Benthem, Udit Gupta, et al.. (2025). A view of the sustainable computing landscape. Patterns. 6(7). 101296–101296. 1 indexed citations

3.

Strubell, Emma, et al.. (2024). Scalable Data Ablation Approximations for Language Models through Modular Training and Merging. 21125–21141.

4.

Luccioni, Alexandra Sasha, Yacine Jernite, & Emma Strubell. (2024). Power Hungry Processing: Watts Driving the Cost of AI Deployment?. 85–99. 92 indexed citations breakdown →

5.

Strubell, Emma, et al.. (2024). Challenges in End-to-End Policy Extraction from Climate Action Plans. 156–167.

6.

Lucy, Li, Suchin Gururangan, Luca Soldaini, et al.. (2024). AboutMe: Using Self-Descriptions in Webpages to Document the Effects of English Pretraining Data Filters. 7393–7420. 1 indexed citations

7.

Dua, Dheeru, et al.. (2023). To Adapt or to Annotate: Challenges and Interventions for Domain Adaptation in Open-Domain Question Answering. 14429–14446. 2 indexed citations

8.

Gupta, Jai Prakash, Yi Tay, Mostafa Dehghani, et al.. (2023). DSI++: Updating Transformer Memory with New Documents. 8198–8213. 8 indexed citations

9.

Bisk, Yonatan, et al.. (2023). The Framework Tax: Disparities Between Inference Efficiency in NLP Research and Deployment. 1588–1600. 5 indexed citations

10.

Widder, David Gray, et al.. (2023). To Build Our Future, We Must Know Our Past: Contextualizing Paradigm Shifts in Natural Language Processing. 13310–13325. 3 indexed citations

11.

Wang, Xiaorong, et al.. (2023). Energy and Carbon Considerations of Fine-Tuning BERT. 9058–9069. 4 indexed citations

12.

Kaack, Lynn H., Priya L. Donti, Emma Strubell, et al.. (2022). Aligning artificial intelligence with climate change mitigation. Nature Climate Change. 12(6). 518–527. 238 indexed citations breakdown →

13.

Zhang, Zhisong, Emma Strubell, & Eduard Hovy. (2022). Transfer Learning from Semantic Role Labeling to Event Argument Extraction with Template-based Slot Querying. 2627–2647. 2 indexed citations

14.

Strubell, Emma, et al.. (2022). Train Flat, Then Compress: Sharpness-Aware Minimization Learns More Compressible Models. 4909–4936. 2 indexed citations

15.

Zhang, Zhisong, Emma Strubell, & Eduard Hovy. (2022). A Survey of Active Learning for Natural Language Processing. 6166–6190. 23 indexed citations

16.

Strubell, Emma, et al.. (2022). Bridging Fairness and Environmental Sustainability in Natural Language Processing. 7817–7836. 6 indexed citations

17.

Kaack, Lynn H., Priya L. Donti, Emma Strubell, & David Rolnick. (2021). Artificial Intelligence and Climate Change: Opportunities, considerations, and policy levers to align AI with climate change goals. OPUS 4 (Zuse Institute Berlin). 4 indexed citations

18.

Strubell, Emma, Patrick Verga, David Belanger, & Andrew McCallum. (2017). Fast and Accurate Sequence Labeling with Iterated Dilated Convolutions.. arXiv (Cornell University). 14 indexed citations

19.

Chang, Haw-Shiuan, et al.. (2016). Extracting Multilingual Relations under Limited Resources: TAC 2016 Cold-Start KB construction and Slot-Filling using Compositional Universal Schema.. Theory and applications of categories. 3 indexed citations

20.

Roth, Benjamin, et al.. (2015). Building Knowledge Bases with Universal Schema: Cold Start and Slot-Filling Approaches.. Theory and applications of categories. 4 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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