Surojit Chatterjee
Impact in
- Signal Processing top 2%
- Data Management and Algorithms
- Time Series Analysis and Forecasting
- Artificial Intelligence top 5%
- Advanced Clustering Algorithms Research
- Anomaly Detection Techniques and Applications
Papers in
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- Advanced Clustering Algorithms Research 4
- Natural Language Processing Techniques 1
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- Image Retrieval and Classification Techniques 2
- Advanced Data Compression Techniques 1
- Co-authors
- Gholamhosein Sheikholeslami (4 shared papers)Aidong Zhang (3 shared papers)Anirban Pal (1 shared paper)Dantong Yu (2 shared papers)Ricardo Vinuesa (1 shared paper)Aidong Zhang (1 shared paper)Daniel Silva (1 shared paper)Marc Najork (1 shared paper)
- Journals
- The VLDB Journal (1 paper)Anesthesia Essays and Researches (1 paper)Very Large Data Bases (1 paper)
- Partner nations
- United StatesSwedenIndia
In The Last Decade
Surojit Chatterjee
8 papers receiving 616 citations
Peers
Comparison fields: 5 of 85
- Signal Processing 293
- Artificial Intelligence 454
- Information Systems 174
- Computer Vision and Pattern Recognition 158
- Statistical and Nonlinear Physics 70
Countries citing papers authored by Surojit Chatterjee
This map shows the geographic impact of Surojit Chatterjee'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 Surojit Chatterjee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Surojit Chatterjee more than expected).
Fields of papers citing papers by Surojit Chatterjee
This network shows the impact of papers produced by Surojit Chatterjee. 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 Surojit Chatterjee. The network helps show where Surojit Chatterjee may publish in the future.
Co-authors
The 13 scholars most cited alongside Surojit Chatterjee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | WaveCluster: A Multi-Resolution Clustering Approach for Very Large Spatial Databases | 1998 | 465 |
| 2 | 2000 | 172 | |
| 3 | 2011 | 36 | |
| 4 | 2002 | 4 | |
| 5 | Efficiently Detecting Arbitrary Shaped Clusters in Very Large Datasets with High Dimensions | 1998 | 4 |
| 6 | 2022 | 2 | |
| 7 | 2003 | 1 | |
| 8 | 2019 | 1 |
About Surojit Chatterjee
Surojit Chatterjee is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Surgery and Pediatrics, Perinatology and Child Health, having authored 8 papers that have together received 685 indexed citations. Recurring topics across this work include Advanced Clustering Algorithms Research (4 papers), Data Management and Algorithms (2 papers), Image Retrieval and Classification Techniques (2 papers), Natural Language Processing Techniques (1 paper), Time Series Analysis and Forecasting (1 paper), Advanced Data Compression Techniques (1 paper), Neonatal and fetal brain pathology (1 paper) and Data Mining Algorithms and Applications (1 paper). The work is most often cited by research in Signal Processing (293 citations), Artificial Intelligence (454 citations), Information Systems (174 citations), Computer Vision and Pattern Recognition (158 citations) and Statistical and Nonlinear Physics (70 citations). Surojit Chatterjee has collaborated with scholars based in United States, Sweden and India. Frequent co-authors include Gholamhosein Sheikholeslami, Aidong Zhang, Anirban Pal, Dantong Yu, Ricardo Vinuesa, Aidong Zhang, Daniel Silva, Marc Najork, Yuan Wang and Amr Ahmed. Their work appears in journals such as The VLDB Journal, Anesthesia Essays and Researches and Very Large Data Bases.
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.