Chandan K. Reddy

7.2k citations
155 papers · 3.6k indexed · 3 hit papers · h-index 31
Topics
Topic Modeling (25 papers)Speech and Audio Processing (24 papers)Advanced Adaptive Filtering Techniques (19 papers)

In The Last Decade

Chandan K. Reddy

145 papers receiving 3.4k citations

Hit Papers

Machine Learning for Survival Analysis2014202620182022201920142022100200300

Peers

Chandan K. Reddy
Comparison fields: 5 of 178
  • Artificial Intelligence 1.7k
  • Signal Processing 678
  • Information Systems 529
  • Computer Vision and Pattern Recognition 396
  • Molecular Biology 279
Replace W. Nick Street with:
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Citations per field
00.5×3.9×
W. Nick Street · 1×
Citations per year

Countries citing papers authored by Chandan K. Reddy

Since Specialization
Citations

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

Fields of papers citing papers by Chandan K. Reddy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chandan K. Reddy. 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 Chandan K. Reddy. The network helps show where Chandan K. Reddy may publish in the future.

Co-authorship network of co-authors of Chandan K. Reddy

This figure shows the co-authorship network connecting the top 25 collaborators of Chandan K. Reddy. A scholar is included among the top collaborators of Chandan K. Reddy 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 Chandan K. Reddy. Chandan K. Reddy 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 0
3 3
4 3
5 7
6 15
7 18
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11
Evaluating The Effectiveness Of Human Resource Information System(Hris) Among Information Technology Sector Employees At Bengaluru
1
12 28
13
A Translate-Edit Model for Natural Language Question to SQL Query Generation on Multi-relational Healthcare Data.
1
14
Neural Abstractive Text Summarization with Sequence-to-Sequence Models: A Survey
3
15
How Fast Will You Get a Response? Predicting Interval Time for Reciprocal Link Creation
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16 10
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Providing High Social Presence for Mobile Systems via an Unobtrusive Face Capture System
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19 0
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On data-driven analysis of user-generated content
1

About Chandan K. Reddy

Chandan K. Reddy is a scholar working on Signal Processing, Artificial Intelligence and Computational Mathematics, having authored 155 papers that have together received 3.6k indexed citations. Recurring topics across this work include Topic Modeling (25 papers), Speech and Audio Processing (24 papers) and Advanced Adaptive Filtering Techniques (19 papers). The work is most often cited by research in Signal Processing (678 citations), Artificial Intelligence (1.7k citations) and Health Information Management (235 citations). Chandan K. Reddy has collaborated with scholars based in United States, South Korea and United Kingdom. Frequent co-authors include Ping Wang, Dilpreet Singh, Yan Li, Ross Cutler, Tian Shi, Vineeth Rakesh, Jimeng Sun, Bhanukiran Vinzamuri, Vishak Gopal and Jaegul Choo. Their work appears in journals such as PLoS ONE, Scientific Reports and The Journal of the Acoustical Society of America.

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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