Dipankar Ray

681 total citations
10 papers, 297 citations indexed

About

Dipankar Ray is a scholar working on Artificial Intelligence, Mechanical Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Dipankar Ray has authored 10 papers receiving a total of 297 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 3 papers in Mechanical Engineering and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Dipankar Ray's work include Geochemistry and Geologic Mapping (3 papers), Mineral Processing and Grinding (3 papers) and Advanced Image Fusion Techniques (2 papers). Dipankar Ray is often cited by papers focused on Geochemistry and Geologic Mapping (3 papers), Mineral Processing and Grinding (3 papers) and Advanced Image Fusion Techniques (2 papers). Dipankar Ray collaborates with scholars based in India, Switzerland and Germany. Dipankar Ray's co-authors include David M. Chickering, Denis Charles, Léon Bottou, Jonas Peters, Patrice Simard, Elon Portugaly, Joaquin Quiñonero-Candela, Bijay Sarkar, D. Dutta Majumder and Amit Das and has published in prestigious journals such as Journal of Machine Learning Research, Neural Computing and Applications and Journal of the Geological Society of India.

In The Last Decade

Dipankar Ray

10 papers receiving 272 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Dipankar Ray India	4	176	115	83	53	29	10	297
Shimon Schocken Israel	6	166 0.9×	40 0.3×	28 0.3×	14 0.3×	18 0.6×	28	303
Chenxin Ma China	6	189 1.1×	48 0.4×	19 0.2×	9 0.2×	87 3.0×	11	315
Małgorzata Przybyła‐Kasperek Poland	11	146 0.8×	94 0.8×	58 0.7×	11 0.2×	12 0.4×	58	279
J. J. Martin United States	5	194 1.1×	43 0.4×	38 0.5×	29 0.5×	18 0.6×	6	303
Jiří Vomlel Czechia	10	242 1.4×	53 0.5×	37 0.4×	19 0.4×	27 0.9×	30	335
Relu Patrascu Canada	8	180 1.0×	88 0.8×	30 0.4×	8 0.2×	73 2.5×	10	273
Hossein Esfandiari United States	10	85 0.5×	67 0.6×	13 0.2×	4 0.1×	121 4.2×	42	261
Roan Thi Ngan Vietnam	6	122 0.7×	255 2.2×	40 0.5×	80 1.5×	25 0.9×	9	346
Jianchao Tang China	9	107 0.6×	268 2.3×	27 0.3×	8 0.2×	34 1.2×	18	440
David Harmanec United States	11	278 1.6×	208 1.8×	19 0.2×	60 1.1×	27 0.9×	19	405

Countries citing papers authored by Dipankar Ray

Since Specialization

Citations

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

Fields of papers citing papers by Dipankar Ray

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dipankar Ray

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

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

1.

Ray, Dipankar, et al.. (2022). Mineral deposit grade assessment using a hybrid model of kriging and generalized regression neural network. Neural Computing and Applications. 34(13). 10611–10627. 3 indexed citations

2.

Ray, Dipankar, et al.. (2021). Geostatistical Modelling of a High-grade Iron Ore Deposit. Journal of the Geological Society of India. 97(9). 1005–1012. 1 indexed citations

3.

Agrawal, Anil K., et al.. (2019). Expert system to select tunnel boring machine (TBM). IOP Conference Series Materials Science and Engineering. 691(1). 12012–12012. 2 indexed citations

4.

Ray, Dipankar, et al.. (2018). Recurrent neural network approach to mineral deposit modelling. 11 indexed citations

5.

Ray, Dipankar, et al.. (2017). Comparative performance analysis of machine learning classifiers on ovarian cancer dataset. 213–218. 3 indexed citations

6.

Bottou, Léon, Jonas Peters, Joaquin Quiñonero-Candela, et al.. (2013). Counterfactual reasoning and learning systems: the example of computational advertising. Journal of Machine Learning Research. 14(1). 3207–3260. 208 indexed citations

7.

Bottou, Léon, Jonas Peters, Joaquin Quiñonero-Candela, et al.. (2012). Counterfactual Reasoning and Learning Systems. Journal of Machine Learning Research. 57 indexed citations

8.

Ray, Dipankar, D. Dutta Majumder, & Amit Das. (2012). Noise reduction and image enhancement of MRI using adaptive multiscale data condensation. 52. 107–113. 9 indexed citations

9.

Ray, Dipankar, et al.. (2011). Approaches of Multimodal Medical Images Registration and Fusion: Efficacy on Diagnostic and Therapeutic Planning. IETE Journal of Research. 57(6). 498–498. 2 indexed citations

10.

Ray, Dipankar. (1987). Abu Dhabi Offshore Khuff Gas Completions Using Exotic Metallurgy. Middle East Oil Show. 1 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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