Naresh Iyer

523 citations
31 papers · 284 · h-index 11

Impact in

Papers in

Naresh Iyer

27 papers receiving 266 citations

Peers

Naresh Iyer
Comparison fields: 5 of 70
  • Medical Laboratory Technology 6
  • Management Science and Operations Research 34
  • Artificial Intelligence 81
  • Statistics, Probability and Uncertainty 18
  • Control and Systems Engineering 58
Replace Hongsheng Su with:
Hongsheng Su China
João A. Duro United Kingdom
Sung-Shick Kim South Korea
María Consiglio United States
Bo Zheng China
Dang-Hai Pham Vietnam
Mohamadreza Ahmadi United States
Michał Kozielski Poland
Naresh Iyer relative to Hongsheng Su China Hongsheng Su's profile →
Citations per field
00.5×1.5×2.1×
Hongsheng Su · 1×
Citations per year

Countries citing papers authored by Naresh Iyer

Since Specialization
Citations

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

Fields of papers citing papers by Naresh Iyer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Naresh Iyer, 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 Naresh Iyer Line = papers co-authored together Naresh Iyer links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200048
2
An architecture for exploring large design spaces
199832
3 200624
4 200018
5 200318
6 199714
7 201813
8 200712
9 200612
10 199811
11 200811
12 20078
13 20208
14 20088
15 20086
16 20205
17 20075
18 20164
19 20074
20 20084

About Naresh Iyer

Naresh Iyer is a scholar working on Artificial Intelligence, Control and Systems Engineering, Ocean Engineering, Mechanical Engineering and Management Science and Operations Research, having authored 31 papers that have together received 284 indexed citations. Recurring topics across this work include Fault Detection and Control Systems (8 papers), Reservoir Engineering and Simulation Methods (5 papers), Hydraulic Fracturing and Reservoir Analysis (5 papers), Anomaly Detection Techniques and Applications (5 papers), Adversarial Robustness in Machine Learning (4 papers), Oil and Gas Production Techniques (3 papers), Advanced Statistical Process Monitoring (2 papers) and Advanced Control Systems Optimization (2 papers). The work is most often cited by research in Medical Laboratory Technology (6 citations), Management Science and Operations Research (34 citations), Artificial Intelligence (81 citations), Statistics, Probability and Uncertainty (18 citations) and Control and Systems Engineering (58 citations). Naresh Iyer has collaborated with scholars based in United States, Norway and Israel. Frequent co-authors include Abraham Kandel, M. Schneider, Piero P. Bonissone, Hai Qiu, Kai Goebel, John R. Josephson, Dinesh K. Shetty, Rajamani Lakshminarayanan, Weizhong Yan and Neil Eklund. Their work appears in journals such as Wear, IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans, Fuzzy Sets and Systems, Proceedings of the AAAI Conference on Artificial Intelligence and SPE Improved Oil Recovery Conference.

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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