Min Sun

1.2k total citations
41 papers, 800 citations indexed

About

Min Sun is a scholar working on Education, Information Systems and Management and Molecular Biology. According to data from OpenAlex, Min Sun has authored 41 papers receiving a total of 800 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Education, 11 papers in Information Systems and Management and 7 papers in Molecular Biology. Recurrent topics in Min Sun's work include School Choice and Performance (16 papers), Teacher Education and Leadership Studies (14 papers) and Educational Assessment and Improvement (11 papers). Min Sun is often cited by papers focused on School Choice and Performance (16 papers), Teacher Education and Leadership Studies (14 papers) and Educational Assessment and Improvement (11 papers). Min Sun collaborates with scholars based in United States, China and India. Min Sun's co-authors include Kenneth A. Frank, William R. Penuel, H. Alix Gallagher, Peter Youngs, Yongmei Ni, Susanna Loeb, Jason A. Grissom, Spyros Konstantopoulos, Nate Stockham and Maya Varma and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Scientific Reports.

In The Last Decade

Min Sun

39 papers receiving 754 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Min Sun United States 18 564 166 93 80 63 41 800
Todd D. Reeves United States 19 559 1.0× 219 1.3× 56 0.6× 133 1.7× 11 0.2× 40 913
Tracy M. Sweet United States 12 325 0.6× 79 0.5× 112 1.2× 48 0.6× 17 0.3× 32 591
M. Suzanne Donovan United States 9 730 1.3× 70 0.4× 225 2.4× 324 4.0× 29 0.5× 12 1.1k
Kara Jackson United States 18 968 1.7× 261 1.6× 106 1.1× 230 2.9× 12 0.2× 31 1.2k
Simon Lygo‐Baker United Kingdom 15 807 1.4× 64 0.4× 104 1.1× 264 3.3× 10 0.2× 46 1.2k
Nancy Kober 14 512 0.9× 94 0.6× 57 0.6× 91 1.1× 9 0.1× 59 684
Julia H. Kaufman United States 17 1.1k 1.9× 143 0.9× 187 2.0× 207 2.6× 10 0.2× 98 1.4k
Naomi Chudowsky United States 12 980 1.7× 177 1.1× 81 0.9× 393 4.9× 13 0.2× 29 1.3k
Tessa C. Andrews United States 15 540 1.0× 34 0.2× 50 0.5× 171 2.1× 11 0.2× 29 786
Beth A. Scarloss United States 6 886 1.6× 103 0.6× 91 1.0× 334 4.2× 17 0.3× 8 1.1k

Countries citing papers authored by Min Sun

Since Specialization
Citations

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

Fields of papers citing papers by Min Sun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Min Sun

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

All Works

20 of 20 papers shown
1.
Eulalio, Tiffany, Min Sun, Olivier Gevaert, et al.. (2025). regionalpcs improve discovery of DNA methylation associations with complex traits. Nature Communications. 16(1). 368–368.
2.
Savy, Thierry, et al.. (2025). Cancer evolution: from Darwin to the Extended Evolutionary Synthesis. Trends in cancer. 11(3). 204–215. 5 indexed citations
3.
Lozano, Alejandro, Min Sun, Jeffrey Nirschl, et al.. (2025). BIOMEDICA: An Open Biomedical Image-Caption Archive, Dataset, and Vision-Language Models Derived from Scientific Literature. 19724–19735. 3 indexed citations
4.
Wang, Qiankun, Le Dang, Xianzhi Duan, et al.. (2025). Implementation and maintenance of breast cancer screening among Chinese rural women: a mixed-methods evaluation based on RE-AIM framework. BMC Public Health. 25(1). 2502–2502. 1 indexed citations
5.
Li, Sen, Jingyi Lu, Ke Feng, et al.. (2024). The complexity of glucose time series is associated with short- and long-term mortality in critically ill adults: a multi-center, prospective, observational study. Journal of Endocrinological Investigation. 47(12). 3091–3099. 1 indexed citations
6.
7.
Washington, Peter, Haik Kalantarian, John Kent, et al.. (2022). Improved Digital Therapy for Developmental Pediatrics Using Domain-Specific Artificial Intelligence: Machine Learning Study. JMIR Pediatrics and Parenting. 5(2). e26760–e26760. 17 indexed citations
8.
Varma, Maya, Peter Washington, Brianna Chrisman, et al.. (2022). Identification of Social Engagement Indicators Associated With Autism Spectrum Disorder Using a Game-Based Mobile App: Comparative Study of Gaze Fixation and Visual Scanning Methods. Journal of Medical Internet Research. 24(2). e31830–e31830. 30 indexed citations
9.
Chrisman, Brianna, Kelley Paskov, Nate Stockham, et al.. (2021). Indels in SARS-CoV-2 occur at template-switching hotspots. BioData Mining. 14(1). 20–20. 24 indexed citations
10.
Paskov, Kelley, Jae-Yoon Jung, Brianna Chrisman, et al.. (2021). Estimating sequencing error rates using families. BioData Mining. 14(1). 27–27. 6 indexed citations
11.
Washington, Peter, Émilie Leblanc, Kaitlyn Dunlap, et al.. (2020). Precision Telemedicine through Crowdsourced Machine Learning: Testing Variability of Crowd Workers for Video-Based Autism Feature Recognition. Journal of Personalized Medicine. 10(3). 86–86. 24 indexed citations
12.
Sun, Min, Stefano Moretti, Kelley Paskov, et al.. (2020). Game theoretic centrality: a novel approach to prioritize disease candidate genes by combining biological networks with the Shapley value. BMC Bioinformatics. 21(1). 356–356. 11 indexed citations
13.
Sun, Min, et al.. (2020). The implementation and potential effects of teacher evaluation under local control. School Effectiveness and School Improvement. 32(2). 279–305. 5 indexed citations
14.
Washington, Peter, Émilie Leblanc, Kaitlyn Dunlap, et al.. (2020). Selection of trustworthy crowd workers for telemedical diagnosis of pediatric autism spectrum disorder. PubMed. 26. 14–25. 17 indexed citations
15.
Sun, Min, et al.. (2020). The multidimensionality of school performance: Using multiple measures for school accountability and improvement. Education Policy Analysis Archives. 28. 89–89. 1 indexed citations
16.
Bastian, Kevin C., et al.. (2019). What Do Surveys of Program Completers Tell Us About Teacher Preparation Quality?. Journal of Teacher Education. 72(1). 11–26. 8 indexed citations
17.
18.
Gupta, Anika, Min Sun, Kelley Paskov, et al.. (2017). Coalitional game theory as a promising approach to identify candidate autism genes. PubMed. 23. 436–447. 3 indexed citations
19.
Sun, Min, Anne Garrison Wilhelm, Christine Larson, & Kenneth A. Frank. (2014). Exploring Colleagues’ Professional Influence on Mathematics Teachers’ Learning. Teachers College Record The Voice of Scholarship in Education. 116(6). 1–30. 44 indexed citations
20.
Konstantopoulos, Spyros & Min Sun. (2013). Are teacher effects larger in small classes?. School Effectiveness and School Improvement. 25(3). 312–328. 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Todd D. Reeves Breakdown of academic impact, for papers by Tracy M. Sweet Breakdown of academic impact, for papers by M. Suzanne Donovan Breakdown of academic impact, for papers by Kara Jackson Breakdown of academic impact, for papers by Simon Lygo‐Baker Breakdown of academic impact, for papers by Nancy Kober Breakdown of academic impact, for papers by Julia H. Kaufman Breakdown of academic impact, for papers by Naomi Chudowsky Breakdown of academic impact, for papers by Tessa C. Andrews Breakdown of academic impact, for papers by Beth A. Scarloss
Rankless by CCL
2026