Akash Das Sarma
- Signal Processing top 5%
- Computer Networks and Communications top 5%
- Artificial Intelligence top 10%
- Management Science and Operations Research top 5%
- Information Systems top 10%
- Co-authors
- Jennifer WidomAlon HalevyOmar BenjellounAditya ParameswaranYeye HeSurajit ChaudhuriAyush JainRobert Ikeda
- Topics
- Mobile Crowdsensing and Crowdsourcing (5 papers)Advanced Database Systems and Queries (4 papers)Big Data and Business Intelligence (3 papers)
- Journals
- SHILAP Revista de lepidopterologíaProceedings of the VLDB EndowmentKing Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology)
- Partner nations
- United StatesIsraelCanada
In The Last Decade
Akash Das Sarma
12 papers receiving 367 citations
Peers
Comparison fields: 5 of 43
- Signal Processing 215
- Computer Networks and Communications 187
- Artificial Intelligence 159
- Management Science and Operations Research 108
- Information Systems 89
Countries citing papers authored by Akash Das Sarma
This map shows the geographic impact of Akash Das Sarma'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 Akash Das Sarma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Akash Das Sarma more than expected).
Fields of papers citing papers by Akash Das Sarma
This network shows the impact of papers produced by Akash Das Sarma. 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 Akash Das Sarma. The network helps show where Akash Das Sarma may publish in the future.
Co-authorship network of co-authors of Akash Das Sarma
This figure shows the co-authorship network connecting the top 25 collaborators of Akash Das Sarma. A scholar is included among the top collaborators of Akash Das Sarma 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 Akash Das Sarma. Akash Das Sarma is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | Aggregating crowdsourced image segmentations | 1 |
| 3 | 1 | |
| 4 | 44 | |
| 5 | Optimizing Open-Ended Crowdsourcing: The Next Frontier in Crowdsourced Data Management. | 8 |
| 6 | 21 | |
| 7 | 12 | |
| 8 | 4 | |
| 9 | 59 | |
| 10 | 15 | |
| 11 | 5 | |
| 12 | 221 |
About Akash Das Sarma
Akash Das Sarma is a scholar working on Computer Science Applications, Management Information Systems and Information Systems and Management, having authored 12 papers that have together received 393 indexed citations. Recurring topics across this work include Mobile Crowdsensing and Crowdsourcing (5 papers), Advanced Database Systems and Queries (4 papers) and Big Data and Business Intelligence (3 papers). The work is most often cited by research in Signal Processing (215 citations), Computer Science Applications (75 citations) and Management Science and Operations Research (108 citations). Akash Das Sarma has collaborated with scholars based in United States, Israel and Canada. Frequent co-authors include Jennifer Widom, Alon Halevy, Omar Benjelloun, Aditya Parameswaran, Yeye He, Surajit Chaudhuri, Ayush Jain, Robert Ikeda, Arnab Nandi and Robert Fischer. Their work appears in journals such as SHILAP Revista de lepidopterología, Proceedings of the VLDB Endowment and King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology).
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.