V.V. Phansalkar

589 citations
11 papers · 376 · h-index 6

Impact in

Papers in

V.V. Phansalkar

8 papers receiving 355 citations

Peers

V.V. Phansalkar
Comparison fields: 5 of 60
  • Computer Networks and Communications 204
  • Management Science and Operations Research 64
  • Artificial Intelligence 135
  • Control and Systems Engineering 46
  • Electrical and Electronic Engineering 110
Replace Mohammad Naghshvar with:
Mohammad Naghshvar United States
Robert L. Popp United States
Yuqing Zhai China
Zhiguang Xu United States
Leonidas Pitsoulis Greece
Thomas Locher Switzerland
Ilai Bistritz United States
Jan Lemeire Belgium
V.V. Phansalkar relative to Mohammad Naghshvar United States Mohammad Naghshvar's profile →
Citations per field
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Mohammad Naghshvar · 1×
Citations per year

Countries citing papers authored by V.V. Phansalkar

Since Specialization
Citations

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

Fields of papers citing papers by V.V. Phansalkar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 2 scholars most cited alongside V.V. Phansalkar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with V.V. Phansalkar Line = papers co-authored together V.V. Phansalkar links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1 1994201
2 1994105
3 199523
4 199519
5 199517
6 19945
7 19945
8 19911
9 20030
10 20050
11 19960

About V.V. Phansalkar

V.V. Phansalkar is a scholar working on Computer Networks and Communications, Control and Systems Engineering, Artificial Intelligence, Management Science and Operations Research and Electrical and Electronic Engineering, having authored 11 papers that have together received 376 indexed citations. Recurring topics across this work include Optimization and Search Problems (7 papers), Reinforcement Learning in Robotics (4 papers), Iterative Learning Control Systems (4 papers), Game Theory and Applications (2 papers), Distributed Control Multi-Agent Systems (2 papers), Auction Theory and Applications (2 papers), Rings, Modules, and Algebras (1 paper) and Ferroelectric and Negative Capacitance Devices (1 paper). The work is most often cited by research in Computer Networks and Communications (204 citations), Management Science and Operations Research (64 citations), Artificial Intelligence (135 citations), Control and Systems Engineering (46 citations) and Electrical and Electronic Engineering (110 citations). V.V. Phansalkar has collaborated with scholars based in India. Frequent co-authors include P. S. Sastry and M.A.L. Thathachar. Their work appears in journals such as International Journal of Systems Science, Neural Computation, Sadhana, Proceedings - Mathematical Sciences and NOT FOUND REPOSITORY (Indian Institute of Science Bangalore).

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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