John Dagdelen

2.8k total citations · 2 hit papers
11 papers, 1.7k citations indexed

About

John Dagdelen is a scholar working on Materials Chemistry, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, John Dagdelen has authored 11 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Materials Chemistry, 4 papers in Artificial Intelligence and 3 papers in Molecular Biology. Recurrent topics in John Dagdelen's work include Machine Learning in Materials Science (6 papers), Topic Modeling (4 papers) and Biomedical Text Mining and Ontologies (3 papers). John Dagdelen is often cited by papers focused on Machine Learning in Materials Science (6 papers), Topic Modeling (4 papers) and Biomedical Text Mining and Ontologies (3 papers). John Dagdelen collaborates with scholars based in United States, Spain and India. John Dagdelen's co-authors include Kristin A. Persson, Anubhav Jain, Gerbrand Ceder, Alexander Dunn, Vahe Tshitoyan, Olga Kononova, Leigh Weston, Ziqin Rong, Joseph H. Montoya and Nicholas Walker and has published in prestigious journals such as Nature, Nature Communications and PLoS ONE.

In The Last Decade

John Dagdelen

11 papers receiving 1.6k 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.

Unsupervised word embeddings capture latent knowledge from materials science literature

2019 698 citations Vahe Tshitoyan, John Dagdelen et al. Nature profile →
Structured information extraction from scientific text with large language models

2024 225 citations John Dagdelen, Alexander Dunn et al. Nature Communications profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
John Dagdelen United States	9	1.0k	392	232	221	146	11	1.7k
Vahe Tshitoyan United States	10	954 1.0×	336 0.9×	271 1.2×	248 1.1×	82 0.6×	12	1.5k
Alexander Dunn United States	11	1.4k 1.4×	335 0.9×	357 1.5×	304 1.4×	132 0.9×	14	2.0k
Kevin Huang United States	17	741 0.7×	446 1.1×	240 1.0×	225 1.0×	130 0.9×	70	1.6k
Olga Kononova United States	21	1.3k 1.3×	458 1.2×	531 2.3×	310 1.4×	142 1.0×	62	2.6k
Leigh Weston United States	11	1.1k 1.1×	248 0.6×	384 1.7×	158 0.7×	59 0.4×	16	1.5k
Haoyan Huo United States	15	880 0.9×	232 0.6×	206 0.9×	212 1.0×	52 0.4×	18	1.1k
Tanjin He United States	19	1.1k 1.1×	177 0.5×	315 1.4×	178 0.8×	103 0.7×	27	1.7k
Mário R. G. Marques Germany	4	1.1k 1.1×	157 0.4×	350 1.5×	215 1.0×	288 2.0×	6	1.8k
Jiandong Wang China	26	417 0.4×	516 1.3×	327 1.4×	120 0.5×	86 0.6×	128	2.0k
Edward O. Pyzer‐Knapp United Kingdom	19	947 0.9×	120 0.3×	248 1.1×	354 1.6×	106 0.7×	44	1.6k

Countries citing papers authored by John Dagdelen

Since Specialization

Citations

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

Fields of papers citing papers by John Dagdelen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John Dagdelen

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

All Works

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11 of 11 papers shown

Dagdelen, John, Alexander Dunn, Sang‐Hoon Lee, et al.. (2024). Structured information extraction from scientific text with large language models. Nature Communications. 15(1). 1418–1418. 225 indexed citations breakdown →

Walker, Nicholas, Sanghoon Lee, John Dagdelen, et al.. (2023). Extracting structured seed-mediated gold nanorod growth procedures from scientific text with LLMs. Digital Discovery. 2(6). 1768–1782. 14 indexed citations

Dagdelen, John, Amalie Trewartha, Haoyan Huo, et al.. (2023). COVIDScholar: An automated COVID-19 research aggregation and analysis platform. PLoS ONE. 18(2). e0281147–e0281147. 6 indexed citations

Trewartha, Amalie, Nicholas Walker, Haoyan Huo, et al.. (2022). Quantifying the advantage of domain-specific pre-training on named entity recognition tasks in materials science. Patterns. 3(4). 100488–100488. 108 indexed citations

Dagdelen, John, Amalie Trewartha, Gerbrand Ceder, et al.. (2021). Online Interactive Platform for COVID-19 Literature Visual Analytics: Platform Development Study. Journal of Medical Internet Research. 23(7). e26995–e26995. 1 indexed citations

Walker, Nicholas, Amalie Trewartha, Haoyan Huo, et al.. (2021). The Impact of Domain-Specific Pre-Training on Named Entity Recognition Tasks in Materials Science. SSRN Electronic Journal. 18 indexed citations

Dagdelen, John, Matteo Bianchini, Alex M. Ganose, et al.. (2020). Enumeration as a Tool for Structure Solution: A Materials Genomic Approach to Solving the Cation-Ordered Structure of Na₃V₂(PO₄)₂F₃. Chemistry of Materials. 32(20). 8981–8992. 14 indexed citations

Tshitoyan, Vahe, John Dagdelen, Leigh Weston, et al.. (2019). Unsupervised word embeddings capture latent knowledge from materials science literature. Nature. 571(7763). 95–98. 698 indexed citations breakdown →

Weston, Leigh, Vahe Tshitoyan, John Dagdelen, et al.. (2019). Named Entity Recognition and Normalization Applied to Large-Scale Information Extraction from the Materials Science Literature. Journal of Chemical Information and Modeling. 59(9). 3692–3702. 197 indexed citations

10.

Mathew, Kiran, Joseph H. Montoya, Alireza Faghaninia, et al.. (2017). Atomate: A high-level interface to generate, execute, and analyze computational materials science workflows. Computational Materials Science. 139. 140–152. 259 indexed citations

11.

Dagdelen, John, Joseph H. Montoya, Maarten de Jong, & Kristin A. Persson. (2017). Computational prediction of new auxetic materials. Nature Communications. 8(1). 323–323. 117 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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