Keval Vora

1.1k citations
32 papers · 660 indexed · h-index 13

Impact in

Papers in

Keval Vora

31 papers receiving 643 citations

Peers

Keval Vora
Comparison fields: 5 of 29
  • Hardware and Architecture 213
  • Computer Vision and Pattern Recognition 552
  • Information Systems 263
  • Computer Networks and Communications 252
  • Artificial Intelligence 338
Replace Yangzihao Wang with:
Yangzihao Wang United States
Yuechao Pan United States
Yuduo Wu United States
Youshan Miao China
Zhijia Zhao United States
Sreepathi Pai United States
Rupesh Nasre India
Laxman Dhulipala United States
Farzad Khorasani United States
Ming Wu China
Keval Vora relative to Yangzihao Wang United States Yangzihao Wang's profile →
Citations per field
00.5×3.1×
Yangzihao Wang · 1×
Citations per year

Countries citing papers authored by Keval Vora

Since Specialization
Citations

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

Fields of papers citing papers by Keval Vora

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1
Controlling Memory Footprint of Stateful Streaming Graph Processing
20213
2 20217
3 202126
4
LUMOS: Dependency-Driven Disk-based Graph Processing.
201917
5 20190
6 20193
7 201962
8 201912
9 20182
10 20174
11
Exploiting Asynchrony for Performance and Fault Tolerance in Distributed Graph Processing
20171
12 20174
13 20176
14 20171
15 201787
16
Load the edges you need: a generic I/O optimization for disk-based graph processing
201657
17 201640
18 201620
19 20151
20 20149

About Keval Vora

Keval Vora is a scholar working on Hardware and Architecture, Computer Vision and Pattern Recognition, Computer Networks and Communications, Information Systems and Artificial Intelligence, having authored 32 papers that have together received 660 indexed citations. Recurring topics across this work include Graph Theory and Algorithms (23 papers), Parallel Computing and Optimization Techniques (13 papers), Cloud Computing and Resource Management (12 papers), Advanced Graph Neural Networks (10 papers), Distributed systems and fault tolerance (7 papers), Advanced Data Storage Technologies (5 papers), Caching and Content Delivery (4 papers) and Advanced Database Systems and Queries (3 papers). The work is most often cited by research in Hardware and Architecture (213 citations), Computer Vision and Pattern Recognition (552 citations), Information Systems (263 citations), Computer Networks and Communications (252 citations) and Artificial Intelligence (338 citations). Keval Vora has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Rajiv Gupta, Guoqing Xu, Farzad Khorasani, Laxmi N. Bhuyan, Ziang Hu, Chen Tian, Iulian Neamtiu, Kartik Nayak, Amit Chavan and Xiangyu Zhang. Their work appears in journals such as ACM SIGPLAN Notices, Proceedings of the ACM on Programming Languages, ACM SIGOPS Operating Systems Review, ACM Transactions on Architecture and Code Optimization and USENIX Annual Technical Conference.

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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