Arun Agarwal

2.3k citations
132 papers · 1.4k indexed · 1 hit paper · h-index 15

Impact in

Papers in

Arun Agarwal

120 papers receiving 1.3k citations

Hit Papers

Recurrent neural network and a hybrid model for prediction of stock returns 2014 · 337 citations
3372014202620182022100200300

Peers

Arun Agarwal
Comparison fields: 5 of 130
  • Management Science and Operations Research 314
  • Computer Networks and Communications 259
  • Finance 89
  • Signal Processing 92
  • Computer Vision and Pattern Recognition 160
Replace Soumya Sen with:
Soumya Sen India
Yuanzhu Chen Canada
Adebayo Felix Adekoya Ghana
Ajit Singh India
Nonita Sharma India
Ning Chen China
Ayodele A. Adebiyi Nigeria
Yining Wang United States
Hamidou Tembiné United States
Arun Agarwal relative to Soumya Sen India Soumya Sen's profile →
Citations per field
00.5×2.5×
Soumya Sen · 1×
Citations per year

Countries citing papers authored by Arun Agarwal

Since Specialization
Citations

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

Fields of papers citing papers by Arun Agarwal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20242
3 20241
4 20244
5 20231
6 20230
7 20212
8 20192
9 20191
10 20192
11 201651
12 20161
13 20162
14 201512
15 20155
16 201513
17 201546
18 20152
19 200666
20
OFF-LINE SHORTHAND RECOGNITION SYSTEM
19902

About Arun Agarwal

Arun Agarwal is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications, Media Technology, Electrical and Electronic Engineering and Signal Processing, having authored 132 papers that have together received 1.4k indexed citations. Recurring topics across this work include Distributed and Parallel Computing Systems (15 papers), Advanced Wireless Communication Techniques (13 papers), Handwritten Text Recognition Techniques (12 papers), Advanced MIMO Systems Optimization (11 papers), Advanced Data Storage Technologies (11 papers), Cloud Computing and Resource Management (10 papers), Advanced Welding Techniques Analysis (9 papers) and Image Retrieval and Classification Techniques (8 papers). The work is most often cited by research in Management Science and Operations Research (314 citations), Computer Networks and Communications (259 citations), Finance (89 citations), Signal Processing (92 citations) and Computer Vision and Pattern Recognition (160 citations). Arun Agarwal has collaborated with scholars based in India, United States and Ireland. Frequent co-authors include Akhter Mohiuddin Rather, V. N. Sastry, Kabita Agarwal, Gourav Misra, Rajkumar Buyya, Raghavendra Kune, Ashwini Chhatre, Nicolas Perrin, Vivek Kumar and Sarat Kumar Patra. Their work appears in journals such as Propellants Explosives Pyrotechnics, Sadhana, Future Generation Computer Systems, Pattern Recognition and Software Practice and Experience.

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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