Deeksha Sinha
Impact in
- Modeling and Simulation top 2%
- COVID-19 epidemiological studies
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- Forecasting Techniques and Applications
- Optimal Experimental Design Methods
Papers in
-
- Recommender Systems and Techniques 3
- Co-authors
- Vivek F. Farias (5 shared papers)Ciamac C. Moallemi (1 shared paper)Theja Tulabandhula (3 shared papers)Abhay Karandikar (1 shared paper)Veeraruna Kavitha (1 shared paper)Jagabondhu Hazra (1 shared paper)Tanuja Ganu (1 shared paper)Shivkumar Kalyanaraman A (1 shared paper)
- Journals
- Management Science (2 papers)IEEE Journal on Selected Areas in Communications (1 paper)European Journal of Operational Research (1 paper)Journal of Policy Modeling (1 paper)Manufacturing & Service Operations Management (1 paper)
- Partner nations
- United StatesIndiaBrunei
In The Last Decade
Deeksha Sinha
10 papers receiving 262 citations
Deeksha Sinha's Hit Papers
Peers
Comparison fields: 5 of 54
- Modeling and Simulation 110
- Management Science and Operations Research 37
- Statistics and Probability 21
- Epidemiology 44
- Management Information Systems 15
Countries citing papers authored by Deeksha Sinha
This map shows the geographic impact of Deeksha Sinha'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 Deeksha Sinha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deeksha Sinha more than expected).
Fields of papers citing papers by Deeksha Sinha
This network shows the impact of papers produced by Deeksha Sinha. 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 Deeksha Sinha. The network helps show where Deeksha Sinha may publish in the future.
Co-authors
The 17 scholars most cited alongside Deeksha Sinha, 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 | Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States Hit paper breakdown → | 2022 | 188 |
| 2 | 2020 | 27 | |
| 3 | 2013 | 21 | |
| 4 | 2014 | 9 | |
| 5 | 2021 | 8 | |
| 6 | 2023 | 7 | |
| 7 | 2021 | 6 | |
| 8 | 2021 | 2 | |
| 9 | 2020 | 1 | |
| 10 | 2025 | 1 | |
| 11 | 2020 | 0 |
About Deeksha Sinha
Deeksha Sinha is a scholar working on Information Systems, Management Science and Operations Research, Modeling and Simulation, Marketing and Statistical and Nonlinear Physics, having authored 11 papers that have together received 270 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (3 papers), Microfinance and Financial Inclusion (1 paper), Supply Chain and Inventory Management (1 paper), Mathematical and Theoretical Epidemiology and Ecology Models (1 paper), Consumer Market Behavior and Pricing (1 paper), Advanced MIMO Systems Optimization (1 paper), Statistical Methods in Clinical Trials (1 paper) and Advanced Causal Inference Techniques (1 paper). The work is most often cited by research in Modeling and Simulation (110 citations), Management Science and Operations Research (37 citations), Statistics and Probability (21 citations), Epidemiology (44 citations) and Management Information Systems (15 citations). Deeksha Sinha has collaborated with scholars based in United States, India and Brunei. Frequent co-authors include Vivek F. Farias, Ciamac C. Moallemi, Theja Tulabandhula, Abhay Karandikar, Veeraruna Kavitha, Jagabondhu Hazra, Tanuja Ganu, Shivkumar Kalyanaraman A, Liyanage C. De Silva and Vijay Arya. Their work appears in journals such as Management Science, IEEE Journal on Selected Areas in Communications, European Journal of Operational Research, Journal of Policy Modeling and Manufacturing & Service Operations Management.
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.