Vikas Garg

94 papers receiving 770 citations

Peers

Vikas Garg
Comparison fields: 5 of 129
  • Artificial Intelligence 168
  • Computer Vision and Pattern Recognition 102
  • Management Information Systems 44
  • Organizational Behavior and Human Resource Management 46
  • Management Science and Operations Research 56
Replace May El Barachi with:
May El Barachi United Arab Emirates
Evangelos Pournaras United Kingdom
Yao Liu China
V. Suresh India
Xin An China
Praphula Kumar Jain India
Jie Cao China
Linda Plotnick United States
Dhavalkumar Thakker United Kingdom
Vikas Garg relative to May El Barachi United Arab Emirates May El Barachi's profile →
Citations per field
00.5×4.2×
May El Barachi · 1×
Citations per year

Countries citing papers authored by Vikas Garg

Since Specialization
Citations

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

Fields of papers citing papers by Vikas Garg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 124 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Generative models for graph-based protein design
2019102
2 201844
3 201242
4 201237
5 202136
6 201535
7
Link label prediction in signed social networks
201334
8 201830
9 202128
10 201922
11 202022
12
Multiresolution Matrix Factorization
201420
13 200518
14 202115
15 202014
16 202413
17
Adaptivity to Local Smoothness and Dimension in Kernel Regression
201312
18 201012
19 202011
20 202211

About Vikas Garg

Vikas Garg is a scholar working on Artificial Intelligence, Information Systems, Management Science and Operations Research, Computer Networks and Communications and Economics and Econometrics, having authored 124 papers that have together received 812 indexed citations. Recurring topics across this work include Blockchain Technology Applications and Security (11 papers), FinTech, Crowdfunding, Digital Finance (6 papers), Advanced Clustering Algorithms Research (5 papers), AI and HR Technologies (5 papers), IoT and Edge/Fog Computing (4 papers), Business and Economic Development (4 papers), Railway Systems and Energy Efficiency (4 papers) and Complex Network Analysis Techniques (4 papers). The work is most often cited by research in Artificial Intelligence (168 citations), Computer Vision and Pattern Recognition (102 citations), Management Information Systems (44 citations), Organizational Behavior and Human Resource Management (46 citations) and Management Science and Operations Research (56 citations). Vikas Garg has collaborated with scholars based in India, United States and United Arab Emirates. Frequent co-authors include Tommi Jaakkola, Gurinder Singh, John Ingraham, Regina Barzilay, Anubhuti Gupta, T. S. Jayram, M. Narasimha Murty, Abhishek Singhal, Y. Narahari and Roberto Cipolla. Their work appears in journals such as Journal of Sustainable Finance & Investment, IEEE Transactions on Knowledge and Data Engineering, HardwareX, Environment Development and Sustainability and Current Opinion in Structural Biology.

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.

Explore authors with similar magnitude of impact