Emily So

1.1k total citations
41 papers, 730 citations indexed

About

Emily So is a scholar working on Civil and Structural Engineering, Global and Planetary Change and Sociology and Political Science. According to data from OpenAlex, Emily So has authored 41 papers receiving a total of 730 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Civil and Structural Engineering, 10 papers in Global and Planetary Change and 8 papers in Sociology and Political Science. Recurrent topics in Emily So's work include Seismic Performance and Analysis (7 papers), Remote-Sensing Image Classification (7 papers) and Disaster Management and Resilience (7 papers). Emily So is often cited by papers focused on Seismic Performance and Analysis (7 papers), Remote-Sensing Image Classification (7 papers) and Disaster Management and Resilience (7 papers). Emily So collaborates with scholars based in United Kingdom, Germany and United States. Emily So's co-authors include Robin Spence, Stephen Platt, Yue Zhu, J. E. Alarcon, Christian Geiß, Ying Jin, Ruth Spence, Fabio Taucer, Yutaka Ohta and Pete Smith and has published in prestigious journals such as PLoS ONE, Natural Hazards and International Journal of Applied Earth Observation and Geoinformation.

In The Last Decade

Emily So

39 papers receiving 707 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Emily So United Kingdom 17 272 165 156 125 120 41 730
Masakatsu Miyajima Japan 17 595 2.2× 149 0.9× 79 0.5× 93 0.7× 179 1.5× 105 1.0k
Charles Huyck United States 15 225 0.8× 145 0.9× 206 1.3× 179 1.4× 62 0.5× 46 805
David Lallemant Singapore 15 565 2.1× 227 1.4× 231 1.5× 115 0.9× 120 1.0× 51 954
Joachim Post Germany 15 117 0.4× 166 1.0× 291 1.9× 195 1.6× 189 1.6× 46 845
Kambod Amini Hosseini Iran 18 378 1.4× 319 1.9× 149 1.0× 77 0.6× 140 1.2× 50 884
Guiwu Su China 13 66 0.2× 162 1.0× 128 0.8× 70 0.6× 79 0.7× 30 434
Ufuk Hancılar Türkiye 12 397 1.5× 113 0.7× 78 0.5× 64 0.5× 177 1.5× 26 581
Marjorie Greene United States 12 120 0.4× 361 2.2× 128 0.8× 60 0.5× 38 0.3× 17 683
Hideomi Gokon Japan 15 214 0.8× 63 0.4× 118 0.8× 214 1.7× 258 2.1× 56 772
Babak Mansouri Iran 11 158 0.6× 81 0.5× 43 0.3× 62 0.5× 51 0.4× 31 332

Countries citing papers authored by Emily So

Since Specialization
Citations

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

Fields of papers citing papers by Emily So

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Emily So

This figure shows the co-authorship network connecting the top 25 collaborators of Emily So. A scholar is included among the top collaborators of Emily So 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 So. Emily So 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.
Zhu, Yue, Christian Geiß, Emily So, et al.. (2024). Urban expansion simulation with an explainable ensemble deep learning framework. Heliyon. 10(7). e28318–e28318. 3 indexed citations
2.
Geiß, Christian, Emily So, Elisabeth Schöepfer, et al.. (2024). Anticipating a risky future: long short-term memory (LSTM) models for spatiotemporal extrapolation of population data in areas prone to earthquakes and tsunamis in Lima, Peru. Natural hazards and earth system sciences. 24(3). 1051–1064. 2 indexed citations
3.
Milillo, Pietro, Giorgia Giardina, Michael Schmitt, et al.. (2024). The EEFIT Remote Sensing Reconnaissance Mission for the February 2023 Turkey Earthquakes. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 17. 19160–19173. 6 indexed citations
4.
Zhu, Yue, Christian Geiß, & Emily So. (2024). Simulating urban expansion with interpretable cycle recurrent neural networks. GIScience & Remote Sensing. 61(1). 3 indexed citations
5.
Geiß, Christian, et al.. (2023). LSTM models for spatiotemporal extrapolation of population data. elib (German Aerospace Center). 66. 1–4. 1 indexed citations
6.
Baker, Hannah, et al.. (2022). COVID-19 and science advice on the ‘Grand Stage’: the metadata and linguistic choices in a scientific advisory groups’ meeting minutes. Humanities and Social Sciences Communications. 9(1). 465–465. 1 indexed citations
7.
Baker, Hannah, et al.. (2022). Information sharing practices during the COVID-19 pandemic: A case study about face masks. PLoS ONE. 17(5). e0268043–e0268043. 3 indexed citations
8.
So, Emily. (2022). Data and its role in reducing the risk of disasters in the built environment. Natural Hazards. 119(2). 1127–1130.
9.
Geiß, Christian, Patrick Aravena Pelizari, Elisabeth Schöepfer, et al.. (2022). Benefits of global earth observation missions for disaggregation of exposure data and earthquake loss modeling: evidence from Santiago de Chile. Natural Hazards. 119(2). 779–804. 11 indexed citations
10.
So, Emily, et al.. (2020). The Zagreb Earthquake of 22 March 2020. 1 indexed citations
11.
Su, Guiwu, Wenhua Qi, David Milledge, et al.. (2019). Creating an earthquake scenario in China: A case study in Weinan City, Shaanxi province. International Journal of Disaster Risk Reduction. 42. 101305–101305. 11 indexed citations
12.
Zhu, Yue, Christian Geiß, & Emily So. (2019). Using deep neural networks for predictive modelling of informal settlements in the context of flood risk. Journal of Physics Conference Series. 1343(1). 12032–12032. 3 indexed citations
13.
Kiremidjian, Anne S., et al.. (2017). Bayesian Updating of Earthquake Vulnerability Functions with Application to Mortality Rates. Earthquake Spectra. 33(3). 1173–1189. 25 indexed citations
14.
Platt, Stephen & Emily So. (2016). Speed or deliberation: a comparison of post‐disaster recovery in Japan, Turkey, and Chile. Disasters. 41(4). 696–727. 50 indexed citations
15.
So, Emily, et al.. (2016). Enhanced change detection index for disaster response, recovery assessment and monitoring of accessibility and open spaces (camp sites). International Journal of Applied Earth Observation and Geoinformation. 57. 49–60. 34 indexed citations
16.
Platt, Stephen, et al.. (2015). Thinking Fast Thinking Slow: bridging the gap between research and practice in disaster recovery. 5 indexed citations
17.
Spence, Ruth, et al.. (2011). Human casualties in earthquakes : progress in modelling and mitigation. Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)). 33 indexed citations
18.
Rossetto, Tiziana, J. E. Alarcon, Emily So, et al.. (2010). Field observations from the Aquila, Italy earthquake of April 6, 2009. Bulletin of Earthquake Engineering. 9(1). 11–37. 44 indexed citations
19.
Rossetto, Tiziana, et al.. (2009). The L’Aquila (Italy) Earthquake of 6th April 2009: A Preliminary Report by EEFIT. UCL Discovery (University College London). 14 indexed citations
20.
Furukawa, Aiko, Robin Spence, Yutaka Ohta, & Emily So. (2009). Analytical study on vulnerability functions for casualty estimation in the collapse of adobe buildings induced by earthquake. Bulletin of Earthquake Engineering. 8(2). 451–479. 33 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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