Mohammad Isa Irawan

147 total papers · 538 total citations
89 papers, 352 citations indexed

About

Mohammad Isa Irawan is a scholar working on Artificial Intelligence, Information Systems and Molecular Biology. According to data from OpenAlex, Mohammad Isa Irawan has authored 89 papers receiving a total of 352 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Artificial Intelligence, 25 papers in Information Systems and 18 papers in Molecular Biology. Recurrent topics in Mohammad Isa Irawan's work include Data Mining and Machine Learning Applications (12 papers), Edcuational Technology Systems (10 papers) and Machine Learning in Bioinformatics (8 papers). Mohammad Isa Irawan is often cited by papers focused on Data Mining and Machine Learning Applications (12 papers), Edcuational Technology Systems (10 papers) and Machine Learning in Bioinformatics (8 papers). Mohammad Isa Irawan collaborates with scholars based in Indonesia, Malaysia and Czechia. Mohammad Isa Irawan's co-authors include Imam Mukhlash, Dieky Adzkiya, Nurul Jadid, Syaharuddin Syaharuddin, Eko Budi Djatmiko, Santoso Santoso, Adi Soeprijanto, Raden Venantius Hari Ginardi, Mohammad Iqbal and Kristanti Indah Purwani and has published in prestigious journals such as SHILAP Revista de lepidopterología, Artificial Intelligence in Medicine and Symmetry.

In The Last Decade

Mohammad Isa Irawan

76 papers receiving 318 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Mohammad Isa Irawan	102	102	48	42	40	89	352
Bahtiar Saleh Abbas	149 1.5×	89 0.9×	16 0.3×	34 0.8×	47 1.2×	63	398
Shastri L. Nimmagadda	91 0.9×	103 1.0×	16 0.3×	23 0.5×	19 0.5×	59	375
Salvatore F. Pileggi	69 0.7×	91 0.9×	16 0.3×	36 0.9×	19 0.5×	50	348
Agung Trisetyarso	167 1.6×	99 1.0×	15 0.3×	30 0.7×	17 0.4×	85	401
Eu-Gene Siew	104 1.0×	142 1.4×	36 0.8×	19 0.5×	109 2.7×	30	370
Deepika Goyal	69 0.7×	43 0.4×	51 1.1×	17 0.4×	31 0.8×	37	324
Gero Strobel	40 0.4×	66 0.6×	28 0.6×	34 0.8×	23 0.6×	35	357
Tatiana Gavrilova	89 0.9×	167 1.6×	20 0.4×	34 0.8×	14 0.3×	49	387
Mona A. Mohamed	57 0.6×	49 0.5×	15 0.3×	34 0.8×	26 0.7×	38	316
Roberta Cuel	104 1.0×	172 1.7×	31 0.6×	37 0.9×	31 0.8×	27	328

Countries citing papers authored by Mohammad Isa Irawan

Since Specialization

Citations

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

Fields of papers citing papers by Mohammad Isa Irawan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mohammad Isa Irawan. 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 Mohammad Isa Irawan. The network helps show where Mohammad Isa Irawan may publish in the future.

Co-authorship network of co-authors of Mohammad Isa Irawan

This figure shows the co-authorship network connecting the top 25 collaborators of Mohammad Isa Irawan. A scholar is included among the top collaborators of Mohammad Isa Irawan 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 Mohammad Isa Irawan. Mohammad Isa Irawan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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