Vivekanand Gopalkrishnan
-
- Stock Market Forecasting Methods 5
- Finance top 5%
- Artificial Intelligence top 5%
- Advanced Clustering Algorithms Research 5
- Data Stream Mining Techniques 4
- Signal Processing top 5%
- Data Management and Algorithms 5
- Time Series Analysis and Forecasting 3
-
- Data Mining Algorithms and Applications 9
-
- Rough Sets and Fuzzy Logic 6
-
- Advanced Database Systems and Queries 5
Vivekanand Gopalkrishnan
30 papers receiving 732 citations
Peers
Comparison fields: 5 of 100
- Management Science and Operations Research 297
- Finance 163
- Artificial Intelligence 310
- Signal Processing 103
- Computational Mathematics 4
Countries citing papers authored by Vivekanand Gopalkrishnan
This map shows the geographic impact of Vivekanand Gopalkrishnan'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 Vivekanand Gopalkrishnan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vivekanand Gopalkrishnan more than expected).
Fields of papers citing papers by Vivekanand Gopalkrishnan
This network shows the impact of papers produced by Vivekanand Gopalkrishnan. 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 Vivekanand Gopalkrishnan. The network helps show where Vivekanand Gopalkrishnan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Vivekanand Gopalkrishnan, 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 | 2013 | 81 | |
| 2 | 2013 | 6 | |
| 3 | 2012 | 3 | |
| 4 | 2012 | 15 | |
| 5 | 2012 | 107 | |
| 6 | Confidence Weighted Mean Reversion Strategy for On-Line Portfolio Selection | 2011 | 6 |
| 7 | 2011 | 1 | |
| 8 | Feature Extraction for Outlier Detection in High-Dimensional Spaces | 2010 | 20 |
| 9 | 2010 | 20 | |
| 10 | Epsilon Equitable Partition: On Scheduling Data Loading and View Maintenance in Soft Real-time Data Warehouses. | 2009 | 3 |
| 11 | 2009 | 11 | |
| 12 | 2009 | 7 | |
| 13 | On Scheduling Data Loading and View Maintenance in Soft Real-time Data Warehouses | 2009 | 1 |
| 14 | 2009 | 1 | |
| 15 | 2009 | 22 | |
| 16 | 2008 | 2 | |
| 17 | 2008 | 8 | |
| 18 | 2008 | 1 | |
| 19 | 2008 | 33 | |
| 20 | 2007 | 9 |
About Vivekanand Gopalkrishnan
Vivekanand Gopalkrishnan is a scholar working on Management Science and Operations Research, Signal Processing, Information Systems, Artificial Intelligence and Computer Networks and Communications, having authored 30 papers that have together received 777 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (9 papers), Rough Sets and Fuzzy Logic (6 papers), Stock Market Forecasting Methods (5 papers), Advanced Database Systems and Queries (5 papers), Data Management and Algorithms (5 papers), Advanced Clustering Algorithms Research (5 papers), Data Stream Mining Techniques (4 papers) and Time Series Analysis and Forecasting (3 papers). The work is most often cited by research in Management Science and Operations Research (297 citations), Finance (163 citations), Artificial Intelligence (310 citations), Signal Processing (103 citations) and Computational Mathematics (4 citations). Vivekanand Gopalkrishnan has collaborated with scholars based in Singapore, United States and Netherlands. Frequent co-authors include Steven C. H. Hoi, Bin Li, Kelvin Sim, Peilin Zhao, Gao Cong, Arthur Zimek, Jinyan Li, Guimei Liu, David Steier and Hoang Vu Nguyen. Their work appears in journals such as ACM Transactions on Knowledge Discovery from Data, IEEE Transactions on Knowledge and Data Engineering, Information Sciences, Data Mining and Knowledge Discovery and IEEE Intelligent Systems.
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.