Ashwin Lall

1.2k citations
41 papers · 814 · h-index 16

Impact in

Papers in

    • Advanced Database Systems and Queries 7
    • Network Security and Intrusion Detection 5
    • Constraint Satisfaction and Optimization 4
    • Algorithms and Data Compression 6
    • Internet Traffic Analysis and Secure E-voting 5
    • Data Stream Mining Techniques 4

Ashwin Lall

38 papers receiving 795 citations

Peers

Ashwin Lall
Comparison fields: 5 of 54
  • Signal Processing 345
  • Computer Networks and Communications 478
  • Artificial Intelligence 355
  • Geography, Planning and Development 53
  • Computer Vision and Pattern Recognition 138
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Citations per field
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Citations per year

Countries citing papers authored by Ashwin Lall

Since Specialization
Citations

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

Fields of papers citing papers by Ashwin Lall

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006136
2 201088
3 200668
4 200753
5 201144
6 201242
7 201838
8
Online Generation of Locality Sensitive Hash Signatures
201031
9 201929
10 200927
11 201925
12
Probabilistic counting with randomized storage
200924
13
Streaming Pointwise Mutual Information
200923
14 201021
15 201520
16 201515
17 201413
18 201212
19 201211
20 201010

About Ashwin Lall

Ashwin Lall is a scholar working on Computer Networks and Communications, Artificial Intelligence, Signal Processing, Information Systems and Computer Vision and Pattern Recognition, having authored 41 papers that have together received 814 indexed citations. Recurring topics across this work include Data Management and Algorithms (13 papers), Advanced Database Systems and Queries (7 papers), Algorithms and Data Compression (6 papers), Network Security and Intrusion Detection (5 papers), Internet Traffic Analysis and Secure E-voting (5 papers), Constraint Satisfaction and Optimization (4 papers), Data Stream Mining Techniques (4 papers) and Complex Network Analysis Techniques (4 papers). The work is most often cited by research in Signal Processing (345 citations), Computer Networks and Communications (478 citations), Artificial Intelligence (355 citations), Geography, Planning and Development (53 citations) and Computer Vision and Pattern Recognition (138 citations). Ashwin Lall has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Jun Xu, Mitsunori Ogihara, Atish Das Sarma, Danupon Nanongkai, Benjamin Van Durme, Vyas Sekar, Hui Zhang, Raymond Chi-Wing Wong, Richard J. Lipton and Min Xie. Their work appears in journals such as ACM SIGMETRICS Performance Evaluation Review, Proceedings of the VLDB Endowment, The VLDB Journal, Information Sciences and IEEE Access.

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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