Seung‐Yeal Ha

6.7k total citations
266 papers, 4.4k citations indexed

About

Seung‐Yeal Ha is a scholar working on Computer Networks and Communications, Statistical and Nonlinear Physics and Applied Mathematics. According to data from OpenAlex, Seung‐Yeal Ha has authored 266 papers receiving a total of 4.4k indexed citations (citations by other indexed papers that have themselves been cited), including 178 papers in Computer Networks and Communications, 80 papers in Statistical and Nonlinear Physics and 60 papers in Applied Mathematics. Recurrent topics in Seung‐Yeal Ha's work include Nonlinear Dynamics and Pattern Formation (146 papers), Distributed Control Multi-Agent Systems (56 papers) and Gas Dynamics and Kinetic Theory (52 papers). Seung‐Yeal Ha is often cited by papers focused on Nonlinear Dynamics and Pattern Formation (146 papers), Distributed Control Multi-Agent Systems (56 papers) and Gas Dynamics and Kinetic Theory (52 papers). Seung‐Yeal Ha collaborates with scholars based in South Korea, China and United States. Seung‐Yeal Ha's co-authors include Jian‐Guo Liu, Eitan Tadmor, Sun-Ho Choi, Dongnam Ko, Jeongho Kim, Doheon Kim, Zhuchun Li, Jinyeong Park, Taeyoung Ha and Marshall Slemrod and has published in prestigious journals such as IEEE Transactions on Automatic Control, Automatica and Communications in Mathematical Physics.

In The Last Decade

Seung‐Yeal Ha

244 papers receiving 3.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Seung‐Yeal Ha South Korea 33 3.0k 1.3k 782 727 713 266 4.4k
Björn Sandstede United States 39 2.4k 0.8× 2.4k 1.8× 192 0.2× 282 0.4× 242 0.3× 141 5.2k
Michael J. Ward Canada 33 1.1k 0.4× 785 0.6× 413 0.5× 225 0.3× 207 0.3× 178 3.5k
Théodore Kolokolnikov Canada 26 815 0.3× 528 0.4× 499 0.6× 253 0.3× 143 0.2× 89 2.0k
Masayasu Mimura Japan 30 737 0.2× 280 0.2× 1.4k 1.8× 117 0.2× 429 0.6× 114 3.1k
Peter W. Bates United States 36 993 0.3× 565 0.4× 511 0.7× 195 0.3× 1.4k 2.0× 98 4.7k
Konstantin Mischaikow United States 38 612 0.2× 1.0k 0.8× 570 0.7× 78 0.1× 400 0.6× 138 4.9k
Renato Spigler Italy 21 2.2k 0.7× 1.2k 0.9× 191 0.2× 278 0.4× 260 0.4× 135 3.8k
John Mallet‐Paret United States 36 1.7k 0.6× 1.2k 0.9× 333 0.4× 73 0.1× 999 1.4× 75 4.6k
Robert A. Van Gorder United States 30 405 0.1× 913 0.7× 1.1k 1.5× 117 0.2× 171 0.2× 253 3.6k
Marshall Slemrod United States 33 644 0.2× 951 0.7× 217 0.3× 113 0.2× 1.4k 2.0× 118 5.0k

Countries citing papers authored by Seung‐Yeal Ha

Since Specialization
Citations

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

Fields of papers citing papers by Seung‐Yeal Ha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Seung‐Yeal Ha. 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 Seung‐Yeal Ha. The network helps show where Seung‐Yeal Ha may publish in the future.

Co-authorship network of co-authors of Seung‐Yeal Ha

This figure shows the co-authorship network connecting the top 25 collaborators of Seung‐Yeal Ha. A scholar is included among the top collaborators of Seung‐Yeal Ha 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 Seung‐Yeal Ha. Seung‐Yeal Ha 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.
Ha, Seung‐Yeal, et al.. (2025). Emergence of Well‐Ordering and Clustering for a First‐Order Nonlinear Consensus Model. Studies in Applied Mathematics. 154(1).
2.
Ha, Seung‐Yeal, et al.. (2024). On the comparison between phenomenological and kinetic theories of gas mixtures with applications to flocking. Physica D Nonlinear Phenomena. 469. 134321–134321. 1 indexed citations
3.
Bellomo, Nicola, et al.. (2024). Behavioral swarms: A mathematical theory toward swarm intelligence. Mathematical Models and Methods in Applied Sciences. 34(12). 2305–2349. 4 indexed citations
4.
Ha, Seung‐Yeal, et al.. (2024). On the asymptotic persistency of a bi-cluster flocking in a Cucker-Smale ensemble. Communications on Pure & Applied Analysis. 23(5). 645–673.
5.
Ha, Seung‐Yeal & Dohyun Kim. (2023). Uniform stability and emergent dynamics of particle and kinetic Lohe matrix models. Journal of Differential Equations. 364. 181–243.
6.
Ha, Seung‐Yeal, et al.. (2023). Continuum limit of the lattice Lohe group model and emergent dynamics. Mathematical Methods in the Applied Sciences. 46(8). 9783–9818. 2 indexed citations
7.
Ha, Seung‐Yeal, et al.. (2023). Asymptotic Tracking of a Point Cloud Moving on Riemannian Manifolds. SIAM Journal on Control and Optimization. 61(4). 2379–2406. 7 indexed citations
8.
Gargano, Francesco, Seung‐Yeal Ha, & Vincenzo Sciacca. (2023). On the stability and convergence of a semi-discrete discontinuous Galerkin scheme to the kinetic Cucker–Smale model. Ricerche di Matematica. 73(S1). 157–187.
9.
Dong, Jiu‐Gang, et al.. (2023). Interplay of inertia and adaptive couplings in the emergent dynamics of Kuramoto ensemble. Journal of Differential Equations. 360. 523–571. 1 indexed citations
10.
Dong, Jiu‐Gang, et al.. (2023). Cardinality of Collisions in Asymptotic Phase-Locking for the Kuramoto Model with Inertia. SIAM Journal on Applied Dynamical Systems. 22(2). 1472–1501.
11.
Ha, Seung‐Yeal, et al.. (2021). Emergent behaviors of the continuum thermodynamic Kuramoto model in a large coupling regime. Journal of Differential Equations. 300. 519–564. 3 indexed citations
12.
Ha, Seung‐Yeal, et al.. (2021). On the emerging asymptotic patterns of the Winfree model with frustrations. Nonlinearity. 34(4). 2454–2482. 3 indexed citations
13.
Ha, Seung‐Yeal, et al.. (2021). Emergent behaviors of relativistic flocks on Riemannian manifolds. Physica D Nonlinear Phenomena. 427. 133011–133011. 13 indexed citations
14.
Dong, Jiu‐Gang, Seung‐Yeal Ha, & Doheon Kim. (2020). On the Cucker-Smale ensemble with <inline-formula><tex-math id="M1">\begin{document}$ q $\end{document}</tex-math></inline-formula>-closest neighbors under time-delayed communications. Kinetic and Related Models. 13(4). 653–676. 1 indexed citations
15.
Ha, Seung‐Yeal, et al.. (2020). Nonlinear stability of stationary solutions to the Kuramoto-Sakaguchi equation with frustration. Networks and Heterogeneous Media. 15(3). 427–461. 1 indexed citations
16.
Ha, Seung‐Yeal, et al.. (2018). Particle and Kinetic Models for Swarming Particles on a Sphere and Stability Properties. Journal of Statistical Physics. 174(3). 622–655. 22 indexed citations
17.
Ha, Seung‐Yeal, et al.. (2018). Emergence of aggregation in the swarm sphere model with adaptive coupling laws. Kinetic and Related Models. 12(2). 411–444. 7 indexed citations
18.
Ha, Seung‐Yeal, Eun-Hee Jeong, & Robert M. Strain. (2012). Uniform $L^1$-stability of the relativistic Boltzmann equation near vacuum. Communications on Pure & Applied Analysis. 12(2). 1141–1161. 4 indexed citations
19.
Chae, Myeongju, Seung‐Yeal Ha, & Hyung Ju Hwang. (2006). Time-asymptotic behavior of the Vlasov–Poisson–Boltzmann system near vacuum. Journal of Differential Equations. 230(1). 71–85. 2 indexed citations
20.
Ha, Seung‐Yeal & Tong Yang. (2003). L1 Stability for Systems of Hyperbolic Conservation Laws with a Resonant Moving Source. SIAM Journal on Mathematical Analysis. 34(5). 1226–1251. 4 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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