Sahil Verma

1.5k citations
5 papers · 636 indexed · 1 hit paper · h-index 5
Topics
Software Engineering Research (2 papers)Adversarial Robustness in Machine Learning (2 papers)Software Testing and Debugging Techniques (2 papers)
Journals
ACM Computing SurveysFormal Methods in System DesignProceedings of the AAAI Conference on Artificial Intelligence
Partner nations
IndiaUnited StatesCanada

In The Last Decade

Sahil Verma

5 papers receiving 612 citations

Hit Papers

Fairness definitions explained20182026202020232018100200300400500

Peers

Sahil Verma
Comparison fields: 5 of 99
  • Safety Research 366
  • Artificial Intelligence 364
  • Sociology and Political Science 88
  • Health Informatics 80
  • Information Systems 72
Replace Pranay Lohia with:
Pranay Lohia India
Kalapriya Kannan India
Parker Barnes United States
Jacquelyn Martino United States
S. Nagar United States
Alon Jacovi Israel
Marija Slavkovik Norway
Mahima Pushkarna United States
Natalia Criado United Kingdom
Manish Raghavan United States
Sahil Verma relative to Pranay Lohia India Pranay Lohia's profile →
Citations per field
00.5×1.5×2.2×
Pranay Lohia · 1×
Citations per year

Countries citing papers authored by Sahil Verma

Since Specialization
Citations

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

Fields of papers citing papers by Sahil Verma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sahil Verma

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

All Works

5 of 5 papers shown
#WorkIndexed citations
1 45
2 8
3 4
4
Fairness definitions explainedbreakdown →
567
5 12

About Sahil Verma

Sahil Verma is a scholar working on Software, Information Systems and Management and Information Systems, having authored 5 papers that have together received 636 indexed citations. Recurring topics across this work include Software Engineering Research (2 papers), Adversarial Robustness in Machine Learning (2 papers) and Software Testing and Debugging Techniques (2 papers). The work is most often cited by research in Health Informatics (80 citations), Safety Research (366 citations) and Artificial Intelligence (364 citations). Sahil Verma has collaborated with scholars based in India, United States and Canada. Frequent co-authors include Julia Rubin, John P. Dickerson, Keegan Hines, Subhajit Roy and Chirag Shah. Their work appears in journals such as ACM Computing Surveys, Formal Methods in System Design and Proceedings of the AAAI Conference on Artificial Intelligence.

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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