Microsoft (India)

4.4k citations
291 papers ·

Impact in

    • Topic Modeling
    • Anomaly Detection Techniques and Applications
    • Natural Language Processing Techniques
    • Sentiment Analysis and Opinion Mining
    • Advanced Text Analysis Techniques
    • Time Series Analysis and Forecasting

Papers in

Microsoft (India)

244 papers receiving 4.3k citations

Peers

Microsoft (India)
Comparison fields: 5 of 169
  • Artificial Intelligence 2.5k
  • Signal Processing 719
  • Software 178
  • Computer Science Applications 244
  • Information Systems 944
Replace ABB (India) with:
ABB (India) India
Indian Institute of Information Technology Sri City India
Vaagdevi College of Engineering India
JK Lakshmipat University India
Thiagarajar College of Engineering India
Ansal University India
Karnataka State Women's University India
Rama Devi Women's University India
Scientific Analysis Group India
Marwadi Education Foundation India
Microsoft (India) relative to ABB (India) India ABB (India)'s profile →
Citations per field
00.5×6.4×
ABB (India) · 1×
Citations per year

Countries citing scholars working at Microsoft (India)

Since Specialization
Citations

This map shows the geographic impact of research produced by authors working at Microsoft (India). 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 papers produced at Microsoft (India) with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Microsoft (India) more than expected).

Fields of papers published by authors at Microsoft (India)

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers affiliated with Microsoft (India) at the time of their publication. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers affiliated with Microsoft (India) at the time of their publication.

About Microsoft (India)

In recent decades, authors affiliated with Microsoft (India) have published 291 papers, which have received a total of 4.4k indexed citations . Scholars at this organization have produced 144 papers in Artificial Intelligence, 36 papers in Signal Processing, 72 papers in Information Systems, 12 papers in Software and 58 papers in Computer Vision and Pattern Recognition on the topics of Topic Modeling (60 papers), Natural Language Processing Techniques (42 papers), Cloud Computing and Resource Management (16 papers), Multimodal Machine Learning Applications (16 papers), Complex Network Analysis Techniques (14 papers), Advanced Malware Detection Techniques (12 papers), Software Testing and Debugging Techniques (11 papers) and Advanced Image and Video Retrieval Techniques (11 papers). Their work is cited by papers focused on Artificial Intelligence (2.5k citations), Signal Processing (719 citations), Software (178 citations), Computer Science Applications (244 citations) and Information Systems (944 citations). Authors at Microsoft (India) collaborate with scholars in India, United States and United Kingdom and have published in prestigious journals including Proceedings of the VLDB Endowment, Proceedings of the ACM on Programming Languages, Multimedia Tools and Applications, Machine Learning and SIAM Journal on Optimization. Some of Microsoft (India)'s most productive authors include Manish Gupta, Jiawei Han, Jing Gao, Charų C. Aggarwal, Puneet Agrawal, Ankush Chatterjee, Manoj Kumar Chinnakotla, Anoop Kunchukuttan, Venkata N. Padmanabhan and Prashanth Mohan.

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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