Supriadi Rustad

1.4k total citations
62 papers, 888 citations indexed

About

Supriadi Rustad is a scholar working on Materials Chemistry, Artificial Intelligence and Civil and Structural Engineering. According to data from OpenAlex, Supriadi Rustad has authored 62 papers receiving a total of 888 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Materials Chemistry, 17 papers in Artificial Intelligence and 15 papers in Civil and Structural Engineering. Recurrent topics in Supriadi Rustad's work include Corrosion Behavior and Inhibition (17 papers), Machine Learning in Materials Science (13 papers) and Concrete Corrosion and Durability (13 papers). Supriadi Rustad is often cited by papers focused on Corrosion Behavior and Inhibition (17 papers), Machine Learning in Materials Science (13 papers) and Concrete Corrosion and Durability (13 papers). Supriadi Rustad collaborates with scholars based in Indonesia, Japan and Malaysia. Supriadi Rustad's co-authors include Muhamad Akrom, Hermawan Kresno Dipojono, De Rosal Ignatius Moses Setiadi, Guruh Fajar Shidik, Abdul Syukur, Pulung Nurtantio Andono, T. Sutojo, Adhitya Gandaryus Saputro, Edi Noersasongko and Heru Agus Santoso and has published in prestigious journals such as SHILAP Revista de lepidopterología, Applied Surface Science and Journal of Physics Condensed Matter.

In The Last Decade

Supriadi Rustad

52 papers receiving 829 citations

Peers

Supriadi Rustad
George B. Adams United States
Huang Lin China
Jiazhen He China
Mario Boley Germany
Thibaut Lavril France
Amalie Trewartha United States
Gunawan Witjaksono Malaysia
Yuki Watanabe Japan
K. Raja India
George B. Adams United States
Supriadi Rustad
Citations per year, relative to Supriadi Rustad Supriadi Rustad (= 1×) peers George B. Adams

Countries citing papers authored by Supriadi Rustad

Since Specialization
Citations

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

Fields of papers citing papers by Supriadi Rustad

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Supriadi Rustad

This figure shows the co-authorship network connecting the top 25 collaborators of Supriadi Rustad. A scholar is included among the top collaborators of Supriadi Rustad 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 Supriadi Rustad. Supriadi Rustad 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.
Rustad, Supriadi, et al.. (2025). SMOTE-ENN Resampling to Optimize Diabetes Prediction in Imbalanced Data. Ingénierie des systèmes d information. 30(5). 1163–1176. 1 indexed citations
2.
Akrom, Muhamad, et al.. (2025). SMILES-driven machine learning for high-throughput investigation of anti-corrosion materials. Chemometrics and Intelligent Laboratory Systems. 263. 105441–105441. 1 indexed citations
3.
Sutojo, T., Supriadi Rustad, De Rosal Ignatius Moses Setiadi, et al.. (2025). Acceptable noise level of quantum circuit for encrypting plaintext. Franklin Open. 12. 100348–100348.
4.
Akrom, Muhamad, Supriadi Rustad, T. Sutojo, et al.. (2024). Quantum machine learning for corrosion resistance in stainless steel. SHILAP Revista de lepidopterología. 3. 100013–100013. 7 indexed citations
5.
Akrom, Muhamad, et al.. (2024). Implementation of quantum machine learning in predicting corrosion inhibition efficiency of expired drugs. Materials Today Communications. 40. 109830–109830. 12 indexed citations
6.
7.
Rustad, Supriadi, et al.. (2024). Phishing Detection Using Random Forest-Based Weighted Bootstrap Sampling and LASSO+ Feature Selection. International Journal of Safety and Security Engineering. 14(6). 1783–1794. 2 indexed citations
8.
Rustad, Supriadi, et al.. (2024). iLDA: A new dimensional reduction method for non-Gaussian and small sample size datasets. Egyptian Informatics Journal. 27. 100533–100533.
9.
10.
Akrom, Muhamad, Supriadi Rustad, Hermawan Kresno Dipojono, & Ryo Maezono. (2024). A comprehensive approach utilizing quantum machine learning in the study of corrosion inhibition on quinoxaline compounds. SHILAP Revista de lepidopterología. 2(2). 100073–100073. 7 indexed citations
11.
Akrom, Muhamad, et al.. (2024). Robust Machine Learning for Predicting Thermal Stability of Metal-Organic Framework. Chemistry Africa. 7(8). 4669–4681. 2 indexed citations
12.
Setiadi, De Rosal Ignatius Moses, Supriadi Rustad, Pulung Nurtantio Andono, & Guruh Fajar Shidik. (2024). Maximizing complex features to minimize the detectability of content-adaptive steganography. Multimedia Tools and Applications. 84(21). 23813–23831. 2 indexed citations
13.
Akrom, Muhamad, Supriadi Rustad, & Hermawan Kresno Dipojono. (2024). Prediction of Anti-Corrosion performance of new triazole derivatives via Machine learning. Computational and Theoretical Chemistry. 1236. 114599–114599. 19 indexed citations
14.
Rustad, Supriadi, Guruh Fajar Shidik, Edi Noersasongko, et al.. (2024). Systematic Literature Review on Named Entity Recognition: Approach, Method, and Application. Statistics Optimization & Information Computing. 12(4). 907–942. 3 indexed citations
15.
Akrom, Muhamad, et al.. (2023). Investigation of Best QSPR-Based Machine Learning Model to Predict Corrosion Inhibition Performance of Pyridine-Quinoline Compounds. Journal of Physics Conference Series. 2673(1). 12014–12014. 27 indexed citations
16.
Akrom, Muhamad, Supriadi Rustad, & Hermawan Kresno Dipojono. (2023). Machine learning investigation to predict corrosion inhibition capacity of new amino acid compounds as corrosion inhibitors. Results in Chemistry. 6. 101126–101126. 41 indexed citations
17.
Sutojo, T., Supriadi Rustad, Muhamad Akrom, et al.. (2023). A machine learning approach for corrosion small datasets. npj Materials Degradation. 7(1). 81 indexed citations
18.
Akrom, Muhamad, et al.. (2023). A combination of machine learning model and density functional theory method to predict corrosion inhibition performance of new diazine derivative compounds. Materials Today Communications. 35. 106402–106402. 38 indexed citations
19.
Akrom, Muhamad, Supriadi Rustad, Adhitya Gandaryus Saputro, & Hermawan Kresno Dipojono. (2023). Data-driven investigation to model the corrosion inhibition efficiency of Pyrimidine-Pyrazole hybrid corrosion inhibitors. Computational and Theoretical Chemistry. 1229. 114307–114307. 42 indexed citations
20.
Subagjo, Mohammad Kemal Agusta, Adhitya Gandaryus Saputro, et al.. (2019). Density functional study of methyl butanoate adsorption and its C–O bonds cleavage on MoS 2 -based catalyst with various loads of Ni promoters. Journal of Physics Condensed Matter. 31(36). 365001–365001. 7 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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