Vikas Khullar

1.3k total citations
88 papers, 661 citations indexed

About

Vikas Khullar is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Computer Networks and Communications. According to data from OpenAlex, Vikas Khullar has authored 88 papers receiving a total of 661 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Artificial Intelligence, 17 papers in Cognitive Neuroscience and 13 papers in Computer Networks and Communications. Recurrent topics in Vikas Khullar's work include Smart Agriculture and AI (10 papers), Privacy-Preserving Technologies in Data (10 papers) and Autism Spectrum Disorder Research (10 papers). Vikas Khullar is often cited by papers focused on Smart Agriculture and AI (10 papers), Privacy-Preserving Technologies in Data (10 papers) and Autism Spectrum Disorder Research (10 papers). Vikas Khullar collaborates with scholars based in India, Spain and Saudi Arabia. Vikas Khullar's 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 and has published in prestigious journals such as Scientific Reports, IEEE Access and Sensors.

In The Last Decade

Vikas Khullar

76 papers receiving 632 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Vikas Khullar India 14 191 179 82 74 72 88 661
R Surendran India 16 120 0.6× 155 0.9× 39 0.5× 46 0.6× 137 1.9× 219 888
Huizilopoztli Luna-García Mexico 12 108 0.6× 110 0.6× 45 0.5× 44 0.6× 18 0.3× 64 592
Ricardo Araújo Brazil 14 117 0.6× 149 0.8× 18 0.2× 50 0.7× 42 0.6× 51 843
Venkata Krishna Kishore Kolli India 14 188 1.0× 220 1.2× 23 0.3× 64 0.9× 51 0.7× 71 815
Amiya Kumar Tripathy India 12 220 1.2× 157 0.9× 43 0.5× 49 0.7× 49 0.7× 83 614
Natheer Khasawneh Jordan 13 90 0.5× 170 0.9× 376 4.6× 33 0.4× 29 0.4× 30 809
Hai Vu Vietnam 16 158 0.8× 135 0.8× 61 0.7× 127 1.7× 60 0.8× 101 811
Hari Kishan Kondaveeti India 11 109 0.6× 70 0.4× 48 0.6× 43 0.6× 61 0.8× 53 567
Amitabha Chakrabarty Bangladesh 16 118 0.6× 203 1.1× 28 0.3× 42 0.6× 99 1.4× 85 760
Abeer Ali Alnuaim Saudi Arabia 13 90 0.5× 132 0.7× 28 0.3× 43 0.6× 40 0.6× 30 571

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-authorship network of co-authors of Vikas Khullar

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

All Works

20 of 20 papers shown
1.
Gupta, Chetna & Vikas Khullar. (2025). Modality independent federated multimodal classification system detached EEG, audio and text data for IID and non-IID conditions. Biomedical Signal Processing and Control. 108. 107938–107938.
2.
Panda, Surya Narayan, et al.. (2025). Federated Learning: An Approach for Managing Data Privacy and Security in Collaborative Learning. Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering). 18(10).
3.
Sharma, Ishu & Vikas Khullar. (2024). Blockchain-enabled federated learning-based privacy preservation framework for secure IoT in precision agriculture. Journal of Industrial Information Integration. 44. 100765–100765. 2 indexed citations
4.
Khullar, Vikas, Mohit Angurala, Abhineet Anand, Jagdish Chandra Patni, & Harjit Singh. (2024). Intelligent fruit quality classification system using transfer learning. Journal of Autonomous Intelligence. 7(4). 1 indexed citations
5.
Panda, Surya Narayan, et al.. (2024). Deep learning based next word prediction aided assistive gaming technology for people with limited vocabulary. Entertainment Computing. 50. 100661–100661. 2 indexed citations
6.
Khullar, Vikas, et al.. (2024). Identification of Sounds Using Deep Learning with MFCC Features Extraction. 60–64. 1 indexed citations
7.
Khullar, Vikas, et al.. (2024). Federated Learning on Internet of Things: Extensive and Systematic Review. Computers, materials & continua/Computers, materials & continua (Print). 79(2). 1795–1834. 12 indexed citations
8.
Sharma, Ashutosh, et al.. (2024). Gas Detection and Classification Using Multimodal Data Based on Federated Learning. Sensors. 24(18). 5904–5904. 6 indexed citations
9.
Khullar, Vikas & Harjit Singh. (2023). f-FNC: Privacy concerned efficient federated approach for fake news classification. Information Sciences. 639. 119017–119017. 15 indexed citations
10.
11.
Chhabra, Rishu, Saravjeet Singh, & Vikas Khullar. (2023). Privacy enabled driver behavior analysis in heterogeneous IoV using federated learning. Engineering Applications of Artificial Intelligence. 120. 105881–105881. 38 indexed citations
12.
Khullar, Vikas, et al.. (2023). Federated Transfer Learning for Rice-Leaf Disease Classification across Multiclient Cross-Silo Datasets. Agronomy. 13(10). 2483–2483. 29 indexed citations
13.
Khullar, Vikas, et al.. (2023). Lightweight Federated Learning for Rice Leaf Disease Classification Using Non Independent and Identically Distributed Images. Sustainability. 15(16). 12149–12149. 47 indexed citations
14.
15.
Khullar, Vikas, et al.. (2023). Pre-Trained Deep Neural Network-Based Features Selection Supported Machine Learning for Rice Leaf Disease Classification. Agriculture. 13(5). 936–936. 50 indexed citations
16.
Khullar, Vikas, et al.. (2023). Privacy preserved collaborative transfer learning model with heterogeneous distributed data for brain tumor classification. International Journal of Imaging Systems and Technology. 34(2). 10 indexed citations
17.
Kansal, Isha, et al.. (2023). IoT-Fog-enabled robotics-based robust classification of hazy and normal season agricultural images for weed detection. Paladyn Journal of Behavioral Robotics. 14(1). 12 indexed citations
18.
Khullar, Vikas, Harjit Singh, Divya Anand, et al.. (2022). IoT Fog-Enabled Multi-Node Centralized Ecosystem for Real Time Screening and Monitoring of Health Information. Applied Sciences. 12(19). 9845–9845. 21 indexed citations
19.
Khullar, Vikas, et al.. (2019). Perinatal Hypoxia Diagnostic System by using Scalable Machine Learning Algorithms. International Journal of Innovative Technology and Exploring Engineering. 8(12). 1954–1959. 4 indexed citations
20.
Singh, Harmeet, Ashish Kr. Luhach, Harjit Singh, & Vikas Khullar. (2017). Performance Investigations of HBO Based Sink Mobility Aware Heterogeneous Protocol of WSN. 7(2). 90–92. 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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