Sanjeev Arora

7.0k citations
23 papers · 2.8k indexed · 2 hit papers · h-index 15
Topics
Hepatitis C virus research (9 papers)Complexity and Algorithms in Graphs (6 papers)Liver Disease Diagnosis and Treatment (3 papers)

In The Last Decade

Sanjeev Arora

21 papers receiving 2.6k citations

Hit Papers

Computational Complexity: A Modern Approach2009202620142020200920092505007501000

Peers

Sanjeev Arora
Comparison fields: 5 of 141
  • Artificial Intelligence 1.3k
  • Computational Theory and Mathematics 1.1k
  • Computer Networks and Communications 369
  • Hepatology 221
  • Electrical and Electronic Engineering 207
Replace Philip M. Long with:
Philip M. Long United States
Michael J. Todd United States
Ran Raz Israel
Stephen S.‐T. Yau China
Alex Pothen United States
Tamás Terlaky Netherlands
Kenneth P. Bogart United States
Ümit V. Çatalyürek United States
Vincent Y. F. Tan Singapore
Zhongzhi Zhang China
Sanjeev Arora relative to Philip M. Long United States Philip M. Long's profile →
Citations per field
00.5×3.4×
Philip M. Long · 1×
Citations per year

Countries citing papers authored by Sanjeev Arora

Since Specialization
Citations

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

Fields of papers citing papers by Sanjeev Arora

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sanjeev Arora

This figure shows the co-authorship network connecting the top 25 collaborators of Sanjeev Arora. A scholar is included among the top collaborators of Sanjeev Arora 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 Sanjeev Arora. Sanjeev Arora 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
#WorkIndexed citations
1 0
2 14
3 5
4 25
5 64
6
Computational Complexity: A Modern Approachbreakdown →
1028
7 14
8
Computational Complexity: ADVANCED TOPICS
336
9
Computational Complexitybreakdown →
760
10
57
11 40
12 25
13 55
14 110
15 17
16 106
17
Proof verification and the hardness of approximation problems.
14
18 66
19 12
20 35

About Sanjeev Arora

Sanjeev Arora is a scholar working on Hepatology, Computational Theory and Mathematics and Rheumatology, having authored 23 papers that have together received 2.8k indexed citations. Recurring topics across this work include Hepatitis C virus research (9 papers), Complexity and Algorithms in Graphs (6 papers) and Liver Disease Diagnosis and Treatment (3 papers). The work is most often cited by research in Computational Theory and Mathematics (1.1k citations), Computational Mathematics (24 citations) and Artificial Intelligence (1.3k citations). Sanjeev Arora has collaborated with scholars based in United States, United Kingdom and India. Frequent co-authors include Boaz Barak, Ravi Kannan, David Steurer, David Johnston, Mazen M. Jamal, Patrick G. Quinn, Anurag Soni, Robert Rosenberg, Donald E. Wheeler and John R. Saltzman. Their work appears in journals such as Gastroenterology, American Journal of Clinical Nutrition and Hepatology.

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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