Serina Chang

2.0k total citations · 1 hit paper
16 papers, 1.1k citations indexed

About

Serina Chang is a scholar working on Artificial Intelligence, Epidemiology and Transportation. According to data from OpenAlex, Serina Chang has authored 16 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 4 papers in Epidemiology and 4 papers in Transportation. Recurrent topics in Serina Chang's work include COVID-19 epidemiological studies (4 papers), Human Mobility and Location-Based Analysis (3 papers) and Topic Modeling (3 papers). Serina Chang is often cited by papers focused on COVID-19 epidemiological studies (4 papers), Human Mobility and Location-Based Analysis (3 papers) and Topic Modeling (3 papers). Serina Chang collaborates with scholars based in United States, Japan and Singapore. Serina Chang's co-authors include Jure Leskovec, Emma Pierson, David B. Grusky, Beth Redbird, Pang Wei Koh, Jaline Gerardin, Kathy McKeown, Ran Abramitzky, Leah Platt Boustan and Dan Jurafsky and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Serina Chang

14 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.

Mobility network models of COVID-19 explain inequities and inform reopening

2020 958 citations Serina Chang, Emma Pierson et al. Nature profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Serina Chang United States	7	625	291	246	208	135	16	1.1k
Beth Redbird United States	6	617 1.0×	316 1.1×	241 1.0×	273 1.3×	162 1.2×	7	1.1k
Alberto Aleta Spain	16	755 1.2×	119 0.4×	255 1.0×	205 1.0×	142 1.1×	34	1.2k
Benjamin F. Maier Germany	10	631 1.0×	134 0.5×	172 0.7×	294 1.4×	97 0.7×	21	983
Ge Xu China	5	412 0.7×	201 0.7×	173 0.7×	205 1.0×	106 0.8×	8	817
Giovanni Bonaccorsi Italy	9	433 0.7×	213 0.7×	114 0.5×	301 1.4×	156 1.2×	14	911
Jayson S. Jia Hong Kong	8	413 0.7×	189 0.6×	175 0.7×	200 1.0×	149 1.1×	12	807
Jianmin Jia China	7	418 0.7×	196 0.7×	177 0.7×	231 1.1×	106 0.8×	8	724
Jessica Floyd United Kingdom	9	848 1.4×	195 0.7×	294 1.2×	367 1.8×	108 0.8×	10	1.4k
Ensheng Dong United States	7	501 0.8×	158 0.5×	215 0.9×	224 1.1×	76 0.6×	12	841
Andrea Flori Italy	15	398 0.6×	168 0.6×	92 0.4×	631 3.0×	153 1.1×	49	1.3k

Countries citing papers authored by Serina Chang

Since Specialization

Citations

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

Fields of papers citing papers by Serina Chang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Serina Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Serina Chang. A scholar is included among the top collaborators of Serina Chang 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 Serina Chang. Serina Chang 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:

16 of 16 papers shown

1.

Hwang, Angel Hsing‐Chi, Michael S. Bernstein, S. Shyam Sundar, et al.. (2025). Human Subjects Research in the Age of Generative AI: Opportunities and Challenges of Applying LLM-Simulated Data to HCI Studies. 1–7. 2 indexed citations

2.

Chang, Serina, et al.. (2025). LLMs Generate Structurally Realistic Social Networks but Overestimate Political Homophily. Proceedings of the International AAAI Conference on Web and Social Media. 19. 341–371. 2 indexed citations

3.

Chang, Serina, et al.. (2025). Learning Production Functions for Supply Chains with Graph Neural Networks. Proceedings of the AAAI Conference on Artificial Intelligence. 39(27). 27878–27886.

4.

Chang, Serina, et al.. (2025). Language Model Fine-Tuning on Scaled Survey Data for Predicting Distributions of Public Opinions. 21147–21170. 1 indexed citations

5.

Chang, Serina, Adam Fourney, & Eric Horvitz. (2024). Measuring vaccination coverage and concerns of vaccine holdouts from web search logs. Nature Communications. 15(1). 6496–6496. 1 indexed citations

6.

Chang, Serina, et al.. (2023). Estimating Geographic Spillover Effects of COVID-19 Policies from Large-Scale Mobility Networks. Proceedings of the AAAI Conference on Artificial Intelligence. 37(12). 14161–14169. 6 indexed citations

7.

Card, Dallas, Serina Chang, Rob Voigt, et al.. (2022). Computational analysis of 140 years of US political speeches reveals more positive but increasingly polarized framing of immigration. Proceedings of the National Academy of Sciences. 119(31). e2120510119–e2120510119. 35 indexed citations

8.

Chang, Serina & Johan Ugander. (2022). To Recommend or Not? A Model-Based Comparison of Item-Matching Processes. Proceedings of the International AAAI Conference on Web and Social Media. 16. 55–66. 1 indexed citations

9.

Wilson, Mandy, Serina Chang, Bryan Lewis, et al.. (2022). Data-Driven Real-Time Strategic Placement of Mobile Vaccine Distribution Sites. Proceedings of the AAAI Conference on Artificial Intelligence. 36(11). 12573–12579. 4 indexed citations

10.

Chang, Serina, Mandy Wilson, Bryan Lewis, et al.. (2021). Supporting COVID-19 Policy Response with Large-scale Mobility-based Modeling. 2632–2642. 19 indexed citations

11.

Chang, Serina, Greg Huber, Lucy M. Li, et al.. (2021). Epidemic dynamics in inhomogeneous populations and the role of superspreaders. Physical Review Research. 3(3). 7 indexed citations

12.

Chang, Serina, Emma Pierson, Pang Wei Koh, et al.. (2020). Mobility network models of COVID-19 explain inequities and inform reopening. Nature. 589(7840). 82–87. 958 indexed citations breakdown →

13.

Chang, Serina & Kathy McKeown. (2019). Automatically Inferring Gender Associations from Language. 5745–5751. 4 indexed citations

14.

Chang, Serina, et al.. (2018). Detecting Gang-Involved Escalation on Social Media Using Context. 46–56. 11 indexed citations

15.

Chang, Serina, et al.. (2017). Crowd-Sourced Iterative Annotation for Narrative Summarization Corpora. 46–51. 13 indexed citations

16.

Sujansky, Walter, et al.. (2009). The Development of a Highly Constrained Health Level 7 Implementation Guide to Facilitate Electronic Laboratory Reporting to Ambulatory Electronic Health Record Systems. Journal of the American Medical Informatics Association. 16(3). 285–290. 14 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