Ankit

487 citations
19 papers · 319 · 1 hit paper · h-index 6

Impact in

    • Sentiment Analysis and Opinion Mining
    • Advanced Text Analysis Techniques
    • Text and Document Classification Technologies
    • Topic Modeling
    • Spam and Phishing Detection

Papers in

Ankit

16 papers receiving 304 citations

Ankit's Hit Papers

Application of Machine Learning and Deep Learning in Finite Element Analysis: A Comprehensive Review 2024 · 67 citations
670+1Years since publication204060

Peers

Ankit
Comparison fields: 5 of 79
  • Artificial Intelligence 170
  • Information Systems 69
  • Electronic, Optical and Magnetic Materials 36
  • Management Science and Operations Research 18
  • Building and Construction 14
Replace Dongyang Yan with:
Dongyang Yan China
Yuqiu Qian China
Anuradha India
Irina Trubitsyna Italy
M. C. Rajalakshmi India
Shiqi Zhao China
Ge Fan China
Talha Younas Pakistan
Carlos García-Rubio Spain
Haochen Zhang China
Ankit relative to Dongyang Yan China Dongyang Yan's profile →
Citations per field
00.5×2×2.6×
Dongyang Yan · 1×
Citations per year

Countries citing papers authored by Ankit

Since Specialization
Citations

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

Fields of papers citing papers by Ankit

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 13 scholars most cited alongside Ankit, 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 Ankit Line = papers co-authored together Ankit links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 2018183
2
Application of Machine Learning and Deep Learning in Finite Element Analysis: A Comprehensive Review
Hit paper breakdown →
202467
3 202414
4 20239
5 20248
6 20247
7 20246
8 20205
9 20205
10 20223
11 20253
12 20223
13
Advance Electronic Load Controller for Micro Hydro Power Plant
20142
14 20212
15 20251
16 20251
17 20260
18 20220
19 20240

About Ankit

Ankit is a scholar working on Electronic, Optical and Magnetic Materials, Aerospace Engineering, Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems, having authored 19 papers that have together received 319 indexed citations. Recurring topics across this work include Metamaterials and Metasurfaces Applications (8 papers), Advanced Antenna and Metasurface Technologies (7 papers), Antenna Design and Analysis (5 papers), Spam and Phishing Detection (2 papers), AI in cancer detection (2 papers), Sentiment Analysis and Opinion Mining (2 papers), Autonomous Vehicle Technology and Safety (1 paper) and Digital Imaging for Blood Diseases (1 paper). The work is most often cited by research in Artificial Intelligence (170 citations), Information Systems (69 citations), Electronic, Optical and Magnetic Materials (36 citations), Management Science and Operations Research (18 citations) and Building and Construction (14 citations). Ankit has collaborated with scholars based in India, Israel and South Korea. Frequent co-authors include Sachin Singh Gautam, Debanga Raj Neog, Ravindra Kumar Sinha, Kamal Kishor, Yasha Hasija, Pooja Jain, K. Aditya Shastry, Rahul Shekhar, Dibyendu Narayan Ghosh and Sandeep Sandeep. Their work appears in journals such as Journal of Optics, Applied Physics A, Applied Optics, Journal of Applied Physics and Journal of Electronic Materials.

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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