Unmesh Kurup

687 citations
25 papers · 337 indexed · h-index 7

Unmesh Kurup

21 papers receiving 324 citations

Peers

Unmesh Kurup
Comparison fields: 5 of 70
  • Automotive Engineering 94
  • Computer Vision and Pattern Recognition 97
  • Artificial Intelligence 118
  • Safety, Risk, Reliability and Quality 27
  • Computer Networks and Communications 53
Replace Arijit Chowdhury with:
Arijit Chowdhury India
Sumbal Malik United Arab Emirates
Vipin Kumar Kukkala United States
Arnav Vaibhav Malawade United States
Rafia Inam Sweden
Seop Hyeong Park South Korea
Manisha Chahal India
Sebastian Zug Germany
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Citations per year

Countries citing papers authored by Unmesh Kurup

Since Specialization
Citations

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

Fields of papers citing papers by Unmesh Kurup

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 22 scholars most cited alongside Unmesh Kurup, 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 Unmesh Kurup Line = papers co-authored together Unmesh Kurup links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20240
2 20230
3 20210
4 202184
5 2019143
6 20198
7 20152
8 20154
9 201225
10 201217
11 20116
12 20101
13 20102
14
Multirepresentational architectures for human-level intelligence : papers from the AAAI Fall Symposium
20091
15 20092
16
Design and use of a bimodal cognitive architecture for diagrammatic reasoning and cognitive modeling
20083
17
A Bimodal Cognitive Architecture: Explorations in Architectural Explanation of Spatial Reasoning.
20071
18
Modeling Memories of Large-scale Space Using a Bimodal Cognitive Architecture
20074
19
Multi-modal Cognitive Architectures: A Partial Solution to the Frame Problem
20065
20
A Diagrammatic Reasoning Architecture: Design, Implementation and Experiments
20055

About Unmesh Kurup

Unmesh Kurup is a scholar working on Artificial Intelligence, Family Practice and Computer Networks and Communications, having authored 25 papers that have together received 337 indexed citations. Recurring topics across this work include AI-based Problem Solving and Planning (9 papers), Constraint Satisfaction and Optimization (8 papers), Logic, Reasoning, and Knowledge (3 papers), Data Stream Mining Techniques (3 papers), Semantic Web and Ontologies (3 papers), Patient Satisfaction in Healthcare (2 papers), Time Series Analysis and Forecasting (2 papers) and Cognitive Science and Mapping (2 papers). The work is most often cited by research in Automotive Engineering (94 citations), Computer Vision and Pattern Recognition (97 citations) and Artificial Intelligence (118 citations). Unmesh Kurup has collaborated with scholars based in United States, India and Netherlands. Frequent co-authors include Mohak Shah, Junyao Guo, Samarth Tripathi, Christian Lebière, B. Chandrasekaran, Anthony Stentz, Nicholas L. Cassimatis, Bonny Banerjee, Florian Jentsch and Scott Ososky. Their work appears in journals such as IEEE Transactions on Intelligent Transportation Systems, Cognitive Systems Research, Topics in Cognitive Science, Biologically Inspired Cognitive Architectures and Proceedings of the AAAI Conference on Artificial Intelligence.

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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