Sameer Wagh

1.3k citations
16 papers · 697 · h-index 12

Impact in

    • Privacy-Preserving Technologies in Data
    • Cryptography and Data Security
    • Adversarial Robustness in Machine Learning
    • Stochastic Gradient Optimization Techniques
    • Internet Traffic Analysis and Secure E-voting

Papers in

    • Cryptography and Data Security 11
    • Privacy-Preserving Technologies in Data 10
    • Internet Traffic Analysis and Secure E-voting 5
    • Stochastic Gradient Optimization Techniques 3
    • Adversarial Robustness in Machine Learning 2
    • Network Security and Intrusion Detection 2

Sameer Wagh

15 papers receiving 678 citations

Peers

Sameer Wagh
Comparison fields: 5 of 39
  • Artificial Intelligence 619
  • Health Informatics 7
  • Information Systems 117
  • Computational Theory and Mathematics 61
  • Computer Science Applications 19
Replace Mayank Rathee with:
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Shuichi Katsumata Japan
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Sameer Wagh relative to Mayank Rathee United States Mayank Rathee's profile →
Citations per field
00.5×5×10×17×
Mayank Rathee · 1×
Citations per year

Countries citing papers authored by Sameer Wagh

Since Specialization
Citations

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

Fields of papers citing papers by Sameer Wagh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Sameer Wagh, 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 Sameer Wagh Line = papers co-authored together Sameer Wagh links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 2019260
2 2021135
3 202359
4 202240
5 202040
6 201728
7 202123
8 200823
9 202119
10 201918
11 201815
12 202214
13 201110
14 201910
15
New Directions in Efficient Privacy-Preserving Machine Learning
20203
16 20240

About Sameer Wagh

Sameer Wagh is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Computer Vision and Pattern Recognition and Computational Theory and Mathematics, having authored 16 papers that have together received 697 indexed citations. Recurring topics across this work include Cryptography and Data Security (11 papers), Privacy-Preserving Technologies in Data (10 papers), Internet Traffic Analysis and Secure E-voting (5 papers), Stochastic Gradient Optimization Techniques (3 papers), Adversarial Robustness in Machine Learning (2 papers), Complexity and Algorithms in Graphs (2 papers), Network Security and Intrusion Detection (2 papers) and Chaos-based Image/Signal Encryption (1 paper). The work is most often cited by research in Artificial Intelligence (619 citations), Health Informatics (7 citations), Information Systems (117 citations), Computational Theory and Mathematics (61 citations) and Computer Science Applications (19 citations). Sameer Wagh has collaborated with scholars based in United States, Belgium and India. Frequent co-authors include Divya Gupta, Nishanth Chandran, Prateek Mittal, Shruti Tople, Tal Rabin, Eyal Kushilevitz, Raluca Ada Popa, Mayank Rathee, Dragos Rotaru and Liwei Song. Their work appears in journals such as Communications of the ACM, Lecture notes in computer science, Indian Journal of Medical Sciences, DOAJ (DOAJ: Directory of Open Access Journals) and Proceedings on Privacy Enhancing Technologies.

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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