Ankur Teredesai

81 papers receiving 1.6k citations

Peers

Ankur Teredesai
Comparison fields: 5 of 133
  • Health Informatics 136
  • Health Information Management 177
  • Artificial Intelligence 613
  • Information Systems 348
  • Signal Processing 114
Replace Xujuan Zhou with:
Xujuan Zhou Australia
Rayid Ghani United States
Carsten Eickhoff United States
Lin Li China
Mark Hoogendoorn Netherlands
K. I. Mohammed Malaysia
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Citations per year

Countries citing papers authored by Ankur Teredesai

Since Specialization
Citations

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

Fields of papers citing papers by Ankur Teredesai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 84 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018292
2 2018136
3 202179
4 202068
5 201068
6 201168
7 202062
8 201362
9 202048
10 201539
11
Age and gender identification in social media
201438
12 201537
13 201436
14 201536
15 200834
16 202132
17
Extracting Social Networks from Instant Messaging Populations
200428
18 201823
19 200922
20 200821

About Ankur Teredesai

Ankur Teredesai is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Computer Networks and Communications and Signal Processing, having authored 84 papers that have together received 1.6k indexed citations. Recurring topics across this work include Machine Learning in Healthcare (16 papers), Data Management and Algorithms (9 papers), Artificial Intelligence in Healthcare (6 papers), Recommender Systems and Techniques (6 papers), Complex Network Analysis Techniques (6 papers), Spam and Phishing Detection (5 papers), Caching and Content Delivery (5 papers) and Heart Failure Treatment and Management (5 papers). The work is most often cited by research in Health Informatics (136 citations), Health Information Management (177 citations), Artificial Intelligence (613 citations), Information Systems (348 citations) and Signal Processing (114 citations). Ankur Teredesai has collaborated with scholars based in United States, Belgium and France. Frequent co-authors include Muhammad Aurangzeb Ahmad, Carly Eckert, Martine De Cock, Chris Cornelis, Patricia Victor, Christopher Roche, Howard Routman, Steven Overman, Thomas W. Wright and Joseph D. Zuckerman. Their work appears in journals such as Journal of Shoulder and Elbow Surgery, IEEE Pervasive Computing, IEEE Intelligent Systems, Knowledge and Information Systems and Clinical Orthopaedics and Related Research.

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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