Ankush Chakrabarty

1.7k citations
101 papers · 1.2k indexed · h-index 20

Impact in

Papers in

Ankush Chakrabarty

93 papers receiving 1.2k citations

Peers

Ankush Chakrabarty
Comparison fields: 5 of 104
  • Control and Systems Engineering 611
  • Endocrinology, Diabetes and Metabolism 148
  • Statistical and Nonlinear Physics 82
  • Building and Construction 79
  • Artificial Intelligence 175
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Xia Yu China
Carlos H. Llanos Brazil
Antonio Della Cioppa Italy
Nasser Sadati Iran
Maryam Zekri Iran
Khalid A. Alattas Saudi Arabia
Rui Huang China
Damiano Varagnolo Norway
Xin Chen China
Yiming Wan China
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Citations per field
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Citations per year

Countries citing papers authored by Ankush Chakrabarty

Since Specialization
Citations

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

Fields of papers citing papers by Ankush Chakrabarty

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20240
4 20243
5 20231
6 20237
7 20233
8 202211
9 202221
10 20226
11 20228
12 202124
13 20211
14 202124
15 201918
16 201917
17 201811
18 201767
19 201729
20 201624

About Ankush Chakrabarty

Ankush Chakrabarty is a scholar working on Control and Systems Engineering, Statistical and Nonlinear Physics, Building and Construction, Artificial Intelligence and Computational Theory and Mathematics, having authored 101 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Control Systems Optimization (26 papers), Fault Detection and Control Systems (22 papers), Control Systems and Identification (16 papers), Building Energy and Comfort Optimization (13 papers), Model Reduction and Neural Networks (12 papers), Stability and Control of Uncertain Systems (12 papers), Diabetes Management and Research (8 papers) and Pancreatic function and diabetes (8 papers). The work is most often cited by research in Control and Systems Engineering (611 citations), Endocrinology, Diabetes and Metabolism (148 citations), Statistical and Nonlinear Physics (82 citations), Building and Construction (79 citations) and Artificial Intelligence (175 citations). Ankush Chakrabarty has collaborated with scholars based in United States, Japan and Switzerland. Frequent co-authors include Stanisław H. Żak, Gregery T. Buzzard, Francis J. Doyle, Ann E. Rundell, Christopher R. Laughman, Eyal Dassau, M. Corless, Fanglai Zhu, Stefano Di Cairano and Claus Danielson. Their work appears in journals such as Energy and Buildings, IEEE Transactions on Control Systems Technology, Automatica, Journal of Process Control and IEEE Transactions on Automatic Control.

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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