V. Jeyakumar

5.4k total citations
167 papers, 3.9k citations indexed

About

V. Jeyakumar is a scholar working on Computational Theory and Mathematics, Numerical Analysis and Control and Systems Engineering. According to data from OpenAlex, V. Jeyakumar has authored 167 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 129 papers in Computational Theory and Mathematics, 117 papers in Numerical Analysis and 59 papers in Control and Systems Engineering. Recurrent topics in V. Jeyakumar's work include Optimization and Variational Analysis (124 papers), Advanced Optimization Algorithms Research (117 papers) and Risk and Portfolio Optimization (48 papers). V. Jeyakumar is often cited by papers focused on Optimization and Variational Analysis (124 papers), Advanced Optimization Algorithms Research (117 papers) and Risk and Portfolio Optimization (48 papers). V. Jeyakumar collaborates with scholars based in Australia, Vietnam and South Korea. V. Jeyakumar's co-authors include Guoyin Li, Dinh The Luc, Xiaoqi Yang, N. Dinh, B. Mond, G. M. Lee, Miguel Á. Goberna, A. M. Rubinov, B. M. Glover and Zhiyou Wu and has published in prestigious journals such as SHILAP Revista de lepidopterología, European Journal of Operational Research and Journal of Mathematical Analysis and Applications.

In The Last Decade

V. Jeyakumar

161 papers receiving 3.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
V. Jeyakumar Australia 37 3.2k 2.4k 1.1k 950 455 167 3.9k
Marco A. López Spain 24 1.7k 0.5× 1.5k 0.6× 664 0.6× 484 0.5× 236 0.5× 139 2.2k
Miguel Á. Goberna Spain 22 1.5k 0.5× 1.2k 0.5× 570 0.5× 484 0.5× 229 0.5× 120 1.9k
Boris S. Mordukhovich United States 41 6.6k 2.0× 4.3k 1.8× 1.5k 1.4× 437 0.5× 1.2k 2.7× 264 7.5k
Johannes Jahn Germany 23 2.1k 0.7× 1.7k 0.7× 444 0.4× 262 0.3× 167 0.4× 57 2.5k
Constantin Zălinescu Romania 20 2.3k 0.7× 1.5k 0.6× 236 0.2× 354 0.4× 572 1.3× 82 2.8k
Guoyin Li Australia 31 1.5k 0.5× 1.3k 0.5× 406 0.4× 674 0.7× 69 0.2× 123 2.8k
Asen L. Dontchev United States 30 2.6k 0.8× 2.1k 0.9× 801 0.8× 134 0.1× 616 1.4× 96 3.8k
W. Oettli Germany 21 3.4k 1.1× 2.3k 0.9× 477 0.5× 130 0.1× 538 1.2× 63 4.0k
Nan‐jing Huang China 34 4.2k 1.3× 1.5k 0.6× 371 0.4× 201 0.2× 805 1.8× 363 4.9k
Jochem Zowe Germany 22 1.7k 0.5× 1.1k 0.5× 490 0.5× 132 0.1× 239 0.5× 45 2.6k

Countries citing papers authored by V. Jeyakumar

Since Specialization
Citations

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

Fields of papers citing papers by V. Jeyakumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of V. Jeyakumar

This figure shows the co-authorship network connecting the top 25 collaborators of V. Jeyakumar. A scholar is included among the top collaborators of V. Jeyakumar 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 V. Jeyakumar. V. Jeyakumar 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.
Jeyakumar, V., et al.. (2024). A distributional Farkas’ lemma and moment optimization problems with no-gap dual semi-definite programs. Optimization Letters. 18(5). 1095–1110.
2.
Jeyakumar, V. & H. Mohebi. (2018). Characterizing best approximation from a convex set without convex representation. Journal of Approximation Theory. 239. 113–127. 6 indexed citations
3.
Jeyakumar, V., et al.. (2017). Constraint qualifications for convex optimization without convexity of constraints : New connections and applications to best approximation. European Journal of Operational Research. 265(1). 19–25. 12 indexed citations
4.
Chương, Thái Doãn & V. Jeyakumar. (2016). A generalized Farkas lemma with a numerical certificate and linear semi-infinite programs with SDP duals. Linear Algebra and its Applications. 515. 38–52. 13 indexed citations
5.
Chương, Thái Doãn & V. Jeyakumar. (2015). Robust global error bounds for uncertain linear inequality systems with applications. Linear Algebra and its Applications. 493. 183–205. 13 indexed citations
6.
Jeyakumar, V., et al.. (2012). Lagrange multiplier characterizations of robust best approximations under constraint data uncertainty. Journal of Mathematical Analysis and Applications. 393(1). 285–297. 22 indexed citations
7.
8.
Cysique, Lucette A., et al.. (2010). A screening algorithm for HIV‐associated neurocognitive disorders. HIV Medicine. 11(10). 642–649. 44 indexed citations
9.
Jeyakumar, V., et al.. (2009). A note on sufficient global optimality conditions for fixed charge quadratic programs. Applied Mathematics Letters. 22(7). 1016–1020. 2 indexed citations
10.
Jeyakumar, V., et al.. (2007). Kuhn–Tucker sufficiency for global minimum of multi-extremal mathematical programming problems. Journal of Mathematical Analysis and Applications. 335(2). 779–788. 12 indexed citations
11.
Jeyakumar, V. & Aleksandr Moiseevich Rubinov. (2005). Continuous optimization : current trends and modern applications. CERN Document Server (European Organization for Nuclear Research). 26 indexed citations
12.
Jeyakumar, V. & H. Mohebi. (2005). Limiting ε-subgradient characterizations of constrained best approximation. Journal of Approximation Theory. 135(2). 145–159. 20 indexed citations
13.
Burachik, Regina S. & V. Jeyakumar. (2004). A simple closure condition for the normal cone intersection formula. Proceedings of the American Mathematical Society. 133(6). 1741–1748. 31 indexed citations
14.
Jeyakumar, V., Dinh The Luc, & Siegfried Schaible. (1998). Characterizations of generalized monotone nonsmooth continuous maps using approximate Jacobians.. 5(1). 119–132. 28 indexed citations
15.
Jeyakumar, V., A. M. Rubinov, B. M. Glover, & Yo Ishizuka. (1996). Inequality Systems and Global Optimization. Journal of Mathematical Analysis and Applications. 202(3). 900–919. 47 indexed citations
16.
Rubinov, A. M., B. M. Glover, & V. Jeyakumar. (1995). A general approach to dual characterizations of solvability of inequality systems with applications.. 2. 309–344. 23 indexed citations
17.
Jeyakumar, V., et al.. (1994). On Global Optimality Conditions for D.C. Programming Problems. 1994. 227–228. 7 indexed citations
18.
Jeyakumar, V., et al.. (1993). A Solvability Theorem for a Class of Quasiconvex Mappings with Applications to Optimization. Journal of Mathematical Analysis and Applications. 179(2). 537–546. 65 indexed citations
19.
Jeyakumar, V. & B. Mond. (1992). On generalised convex mathematical programming. The Journal of the Australian Mathematical Society Series B Applied Mathematics. 34(1). 43–53. 176 indexed citations
20.
Jeyakumar, V.. (1988). Equivalence of saddle-points and optima, and duality for a class of non-smooth non-convex problems. Journal of Mathematical Analysis and Applications. 130(2). 334–343. 43 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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