Vikas Khullar

1.3k citations
88 papers · 661 · h-index 14

Impact in

Papers in

Vikas Khullar

76 papers receiving 632 citations

Peers

Vikas Khullar
Comparison fields: 5 of 114
  • Analytical Chemistry 74
  • Artificial Intelligence 179
  • Plant Science 191
  • Cognitive Neuroscience 82
  • Health Information Management 16
Replace Venkata Krishna Kishore Kolli with:
Venkata Krishna Kishore Kolli India
Amitabha Chakrabarty Bangladesh
R Surendran India
Huizilopoztli Luna-García Mexico
Hari Kishan Kondaveeti India
Abeer Ali Alnuaim Saudi Arabia
Asad Masood Khattak United Arab Emirates
Sultan Alfarhood Saudi Arabia
Mejdl Safran Saudi Arabia
Ricardo Araújo Brazil
Vikas Khullar relative to Venkata Krishna Kishore Kolli India Venkata Krishna Kishore Kolli's profile →
Citations per field
00.5×3.6×
Venkata Krishna Kishore Kolli · 1×
Citations per year

Countries citing papers authored by Vikas Khullar

Since Specialization
Citations

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

Fields of papers citing papers by Vikas Khullar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 88 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201755
2 202350
3 202347
4 202338
5 202432
6 202329
7 202126
8 202221
9 202121
10 201920
11 202218
12 202315
13 202414
14 202113
15 202113
16 202412
17 202312
18 202212
19 202111
20 202311

About Vikas Khullar

Vikas Khullar is a scholar working on Artificial Intelligence, Cognitive Neuroscience, Computer Networks and Communications, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering, having authored 88 papers that have together received 661 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (10 papers), Smart Agriculture and AI (10 papers), Autism Spectrum Disorder Research (10 papers), EEG and Brain-Computer Interfaces (7 papers), IoT and Edge/Fog Computing (6 papers), Spectroscopy and Chemometric Analyses (6 papers), Energy Efficient Wireless Sensor Networks (5 papers) and Water Quality Monitoring Technologies (5 papers). The work is most often cited by research in Analytical Chemistry (74 citations), Artificial Intelligence (179 citations), Plant Science (191 citations), Cognitive Neuroscience (82 citations) and Health Information Management (16 citations). Vikas Khullar has collaborated with scholars based in India, Spain and Saudi Arabia. Frequent co-authors include Harjit Singh, Nitin Goyal, Aman Singh, Manju Bala, Ambuj Kumar Agarwal, Saravjeet Singh, Rishu Chhabra, Raj Gaurang Tiwari, Isha Kansal and Marwan Ali Albahar. Their work appears in journals such as Scientific Reports, Sustainability, Asian Journal of Psychiatry, Multimedia Tools and Applications and Information Sciences.

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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