Anantha Narayanan

1.5k total citations
52 papers, 808 citations indexed

About

Anantha Narayanan is a scholar working on Industrial and Manufacturing Engineering, Artificial Intelligence and Software. According to data from OpenAlex, Anantha Narayanan has authored 52 papers receiving a total of 808 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Industrial and Manufacturing Engineering, 15 papers in Artificial Intelligence and 10 papers in Software. Recurrent topics in Anantha Narayanan's work include Manufacturing Process and Optimization (11 papers), Model-Driven Software Engineering Techniques (10 papers) and Fault Detection and Control Systems (7 papers). Anantha Narayanan is often cited by papers focused on Manufacturing Process and Optimization (11 papers), Model-Driven Software Engineering Techniques (10 papers) and Fault Detection and Control Systems (7 papers). Anantha Narayanan collaborates with scholars based in United States, New Zealand and France. Anantha Narayanan's co-authors include Sudarsan Rachuri, Lisa Mackay, Tom Stewart, Gábor Karsai, Ram D. Sriram, Sebti Foufou, Paul Witherell, Shaw C. Feng, Xenia Fiorentini and Raphaël Barbau and has published in prestigious journals such as Gastroenterology, Scientific Reports and Medicine & Science in Sports & Exercise.

In The Last Decade

Anantha Narayanan

47 papers receiving 772 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anantha Narayanan United States 13 297 156 150 104 85 52 808
Sašo Karakatič Slovenia 9 222 0.7× 158 1.0× 14 0.1× 118 1.1× 22 0.3× 39 715
Ralph Bruder Germany 12 130 0.4× 37 0.2× 33 0.2× 225 2.2× 8 0.1× 82 1.3k
Bernard C. Jiang Taiwan 22 198 0.7× 98 0.6× 105 0.7× 16 0.2× 11 0.1× 80 1.3k
Sundar Krishnamurty United States 24 494 1.7× 228 1.5× 566 3.8× 230 2.2× 7 0.1× 97 1.4k
Peter Chemweno Belgium 17 154 0.5× 41 0.3× 139 0.9× 32 0.3× 3 0.0× 39 871
Tung‐Hsu Hou Taiwan 12 122 0.4× 49 0.3× 159 1.1× 17 0.2× 21 0.2× 20 547
K. Case United Kingdom 16 291 1.0× 52 0.3× 93 0.6× 35 0.3× 24 0.3× 53 649
Chuan‐Jun Su Taiwan 17 177 0.6× 137 0.9× 91 0.6× 33 0.3× 2 0.0× 43 895
Frédéric Vanderhaegen France 22 70 0.2× 169 1.1× 12 0.1× 75 0.7× 6 0.1× 94 1.2k
Greg A. Jamieson Canada 22 50 0.2× 80 0.5× 29 0.2× 88 0.8× 14 0.2× 97 1.5k

Countries citing papers authored by Anantha Narayanan

Since Specialization
Citations

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

Fields of papers citing papers by Anantha Narayanan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anantha Narayanan

This figure shows the co-authorship network connecting the top 25 collaborators of Anantha Narayanan. A scholar is included among the top collaborators of Anantha Narayanan 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 Anantha Narayanan. Anantha Narayanan 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.
Narayanan, Anantha, Tom Stewart, Scott Duncan, & Gail Pacheco. (2025). Using machine learning to explore the efficacy of administrative variables in prediction of subjective-wellbeing outcomes in New Zealand. Scientific Reports. 15(1). 6831–6831. 1 indexed citations
2.
Narayanan, Anantha, et al.. (2025). Daily time-use compositions of physical behaviours and its association with evaluative and experienced wellbeing: a multilevel compositional analysis. International Journal of Behavioral Nutrition and Physical Activity. 22(1). 73–73.
3.
Hettiarachchi, Pasan, Peter Johansson, Scott Duncan, et al.. (2024). Assessing the Accuracy of Activity Classification Using Thigh-Worn Accelerometry: A Validation Study of ActiPASS in School-Aged Children. Journal of Physical Activity and Health. 21(10). 1092–1099. 1 indexed citations
4.
Balasubramanian, Daniel, et al.. (2024). A Subgraph Operator for Graph Transformation Languages. Technische Universität Berlin – Universitätsbibliothek. 6. 1 indexed citations
5.
Jain, Sanjay & Anantha Narayanan. (2023). Digital Twin–Enabled Machine Learning for Smart Manufacturing. 7(1). 111–128. 4 indexed citations
6.
Yu, Fiona, Anantha Narayanan, Lisa Mackay, et al.. (2020). Describing objectively measured intensive care nurses’ physical work activity behavioural patterns during a 12‐hr shift. Journal of Clinical Nursing. 29(21-22). 4331–4342. 9 indexed citations
7.
Narayanan, Anantha, Tom Stewart, & Lisa Mackay. (2019). A Dual-Accelerometer System for Detecting Human Movement in a Free-living Environment. Medicine & Science in Sports & Exercise. 52(1). 252–258. 35 indexed citations
8.
Ferguson, Max, Yung-Tsun Tina Lee, Anantha Narayanan, & Kincho H. Law. (2019). A Standardized PMML Format for Representing Convolutional Neural Networks with Application to Defect Detection. PubMed. 3(1). 79–97. 4 indexed citations
9.
Jain, Sanjay, Anantha Narayanan, & Yung-Tsun Tina Lee. (2018). Comparison of data analytics approaches using simulation. Winter Simulation Conference. 1084–1095. 3 indexed citations
10.
Stewart, Tom, et al.. (2018). A Dual-Accelerometer System for Classifying Physical Activity in Children and Adults. Medicine & Science in Sports & Exercise. 50(12). 2595–2602. 48 indexed citations
11.
Nannapaneni, Saideep, Sankaran Mahadevan, Abhishek Dubey, et al.. (2017). Automated Uncertainty Quantification Through Information Fusion in Manufacturing Processes. HAL (Le Centre pour la Communication Scientifique Directe). 1(1). 153–178. 4 indexed citations
12.
Brodsky, Alexander, et al.. (2016). Analysis and optimization based on reusable knowledge base of process performance models. The International Journal of Advanced Manufacturing Technology. 88(1-4). 337–357. 15 indexed citations
13.
Nannapaneni, Saideep, Sankaran Mahadevan, David Lechevalier, Anantha Narayanan, & Sudarsan Rachuri. (2015). Automated uncertainty quantification analysis using a system model and data. 1408–1417. 1 indexed citations
14.
Wolff, Sarah J., Anantha Narayanan, David Lechevalier, & K. C. Morris. (2014). An information classification system for life cycle and manufacturing standards. 37. 498–503. 2 indexed citations
15.
Narayanan, Anantha, David Lechevalier, K. C. Morris, & Sudarsan Rachuri. (2013). A Methodology for Handling Standards Terminology for Sustainable Manufacturing. 2 indexed citations
16.
Rachuri, Sudarsan, Ram D. Sriram, Anantha Narayanan, et al.. (2011). Summary of the NIST workshop on sustainable manufacturing: metrics, standards, and infrastructure. 2(2/3). 237–237. 11 indexed citations
17.
Barbau, Raphaël, Sylvère Krima, Xenia Fiorentini, et al.. (2010). OntoSTEP: Enriching Product Model Data Using Ontologies | NIST. IEEE Transactions on Knowledge and Data Engineering. 2 indexed citations
18.
Narayanan, Anantha & Gábor Karsai. (2008). Towards Verifying Model Transformations. Electronic Notes in Theoretical Computer Science. 211. 191–200. 38 indexed citations
19.
20.
Cory, Joseph G., et al.. (1993). Structural aspects of N-hydroxy-N′-aminoguanidine derivatives as inhibitors of L1210 cell growth and ribonucleotide reductase activity. Advances in Enzyme Regulation. 33. 129–140. 5 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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