Hongjun Si

709 total citations
25 papers, 447 citations indexed

About

Hongjun Si is a scholar working on Geophysics, Civil and Structural Engineering and Artificial Intelligence. According to data from OpenAlex, Hongjun Si has authored 25 papers receiving a total of 447 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Geophysics, 18 papers in Civil and Structural Engineering and 4 papers in Artificial Intelligence. Recurrent topics in Hongjun Si's work include Seismic Performance and Analysis (17 papers), earthquake and tectonic studies (14 papers) and Seismic Waves and Analysis (13 papers). Hongjun Si is often cited by papers focused on Seismic Performance and Analysis (17 papers), earthquake and tectonic studies (14 papers) and Seismic Waves and Analysis (13 papers). Hongjun Si collaborates with scholars based in Japan, China and United States. Hongjun Si's co-authors include Saburoh MIDORIKAWA, Taku Ozawa, Hiroyuki Fujiwara, Dun Wang, Can Zhang, Tadahiro Kishida, Kazuki Koketsu, H. Miyake, Qiang Yao and Yasuhiro Matsumoto and has published in prestigious journals such as Geophysical Research Letters, Bulletin of the Seismological Society of America and Soil Dynamics and Earthquake Engineering.

In The Last Decade

Hongjun Si

21 papers receiving 404 citations

Peers

Hongjun Si

GEOPH

CSE

MMPL

Nelson Pulido Japan

Shigeki Senna Japan

M. Yanger Walling India

Kimiyuki Asano Japan

Masayoshi Ichiyanagi Japan

Valerie J. Sahakian United States

Ezio D’Alema Italy

Katsuhiro Kamae Japan

Michiko Shigefuji Japan

Chiara Ladina Italy

Nelson Pulido Japan

Hongjun Si

470 ×1.3

GEOPH

305 ×1.2

CSE

50 ×0.6

34 ×0.7

MMPL

17 ×1.1

Citations per year, relative to Hongjun Si Hongjun Si (= 1×) peers Nelson Pulido

Countries citing papers authored by Hongjun Si

Since Specialization

Citations

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

Fields of papers citing papers by Hongjun Si

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hongjun Si

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

All Works

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20 of 20 papers shown

Ren, Yefei, et al.. (2025). Supershear rupture process of the 2025 Myanmar earthquake as derived from joint inversion of near-field and teleseismic waveforms. Earthquake Engineering and Engineering Vibration. 24(4). 917–925.

Zhang, Haizhong, et al.. (2025). Probabilistic assessment of response spectra for multiple damping levels in seismic hazard analysis. Soil Dynamics and Earthquake Engineering. 196. 109460–109460.

Zhang, Haizhong, et al.. (2025). A unified probabilistic assessment of multiple ground-motion intensity measures in seismic hazard analysis based on Fourier amplitude spectra. Bulletin of Earthquake Engineering. 23(10). 3837–3859.

Miyake, H., et al.. (2025). High-Probability Ground Motion Simulation in Maduo County for the Maduo MS7.4 Earthquake in 2021: A Possible Supershear Earthquake. Journal of Earth Science. 36(2). 781–800.

Fujiwara, Hiroyuki, Katsumi Ebisawa, Takao Kagawa, et al.. (2024). DEVELOPMENT OF GROUND MOTION CHARACTERIZATION MODEL AT THE IKATA SITE BASED ON GUIDELINES FOR SSHAC LEVEL 3. Journal of Japan Association for Earthquake Engineering. 24(2). 2_1–2_29. 1 indexed citations

Gregor, Nick, Kofi Addo, Norman Abrahamson, et al.. (2022). Comparisons of the NGA‐Subduction ground motion models. Earthquake Spectra. 38(4). 2580–2610. 14 indexed citations

Si, Hongjun, Saburoh MIDORIKAWA, & Tadahiro Kishida. (2022). Development of NGA‐Sub ground‐motion prediction equation of 5%‐damped pseudo‐spectral acceleration based on database of subduction earthquakes in Japan. Earthquake Spectra. 38(4). 2682–2706. 18 indexed citations

Wang, Dun, et al.. (2022). Rapid Estimation of Seismic Intensities Using a New Algorithm That Incorporates Array Technologies and Ground-Motion Prediction Equations (GMPEs). Bulletin of the Seismological Society of America. 112(3). 1647–1661. 17 indexed citations

Fujiwara, Hiroyuki, Katsumi Ebisawa, Takao Kagawa, et al.. (2022). Development of Ground Motion Characterization Model at the Ikata Site Based on Guidelines for SSHAC Level 3. Journal of Japan Association for Earthquake Engineering. 22(2). 2_61–2_87. 2 indexed citations

10.

Kishida, Tadahiro, Robert B. Darragh, Yousef Bozorgnia, Chun‐Hsiang Kuo, & Hongjun Si. (2018). Homogeneous Estimation of Moment Magnitude for Small‐to‐Moderate Magnitude Earthquakes Located near the Border between Japan and Taiwan. Seismological Research Letters. 89(3). 1093–1100. 3 indexed citations

11.

Si, Hongjun, Kazuki Koketsu, & H. Miyake. (2017). High Attenuation Rate for Shallow, Small Earthquakes in Japan. Pure and Applied Geophysics. 174(9). 3557–3567. 2 indexed citations

12.

Si, Hongjun, et al.. (2016). Attenuation Characteristics of Strong Motions during the 2016 Kumamoto Earthquake. Japan Geoscience Union. 1 indexed citations

13.

Si, Hongjun, et al.. (2016). Long‐Period Ground‐Motion Prediction Equations for Moment Magnitude Estimation of Large Earthquakes in Japan. Bulletin of the Seismological Society of America. 106(1). 54–72. 8 indexed citations

14.

Si, Hongjun, Kazuki Koketsu, & H. Miyake. (2016). Attenuation Characteristics of Strong Ground Motion from Megathrust Earthquakes in Subduction Zone. Journal of Japan Association for Earthquake Engineering. 16(1). 1_96–1_105. 4 indexed citations

15.

Si, Hongjun, et al.. (2016). Long‐Period Site Response in Northeastern Japan from Ground‐Motion Prediction Equations. Bulletin of the Seismological Society of America. 106(6). 2521–2531. 1 indexed citations

16.

Kurahashi, Susumu, et al.. (2015). Relationships between building damage and characteristics of strong ground motions during the M6.5 Zhaotong Earthquake-2. Japan Geoscience Union. 1 indexed citations

17.

Matsumoto, Yasuhiro, et al.. (2013). Comparative Study on Scaling Relations of Source Parameters for Great Earthquakes in Inland Crusts and on Subducting Plate-Boundaries. Zisin (Journal of the Seismological Society of Japan 2nd ser ). 66(3). 31–45. 18 indexed citations

18.

Miyake, H., Yusuke Yokota, Hongjun Si, & Kazuki Koketsu. (2011). Earthquake Scenarios Generating Extreme Ground Motions: Application to the 2011 Tohoku Earthquake. AGUFM. 2011. 1 indexed citations

19.

Si, Hongjun, et al.. (2008). Coseismic Faults and Crust Deformation Accompanied the 2008 Wenchuan Earthquake, China by Field Investigation and InSAR Interferogram. AGUFM. 2008. 1 indexed citations

20.

Si, Hongjun & Saburoh MIDORIKAWA. (1999). NEW ATTENUATION RELATIONSHIPS FOR PEAK GROUND ACCELERATION AND VELOCITY CONSIDERING EFFECTS OF FAULT TYPE AND SITE CONDITION. Journal of Structural and Construction Engineering (Transactions of AIJ). 64(523). 63–70. 243 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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