Jieming Mao
Impact in
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- Auction Theory and Applications
- Advanced Bandit Algorithms Research
- Marketing top 10%
- Consumer Market Behavior and Pricing
Papers in
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- Auction Theory and Applications 16
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- Privacy-Preserving Technologies in Data 5
- Cryptography and Data Security 4
- Co-authors
- Song Zuo (11 shared papers)Vahab Mirrokni (10 shared papers)Yuan Deng (9 shared papers)S. C. Chan (9 shared papers)K.L. Ho (8 shared papers)Santiago Balseiro (5 shared papers)Mark Braverman (3 shared papers)S. Matthew Weinberg (2 shared papers)
- Journals
- IEEE Signal Processing Letters (3 papers)Theoretical Computer Science (1 paper)IEEE Transactions on Information Theory (1 paper)IEEE Transactions on Signal Processing (1 paper)ACM Transactions on Algorithms (1 paper)
- Partner nations
- United StatesHong KongChina
In The Last Decade
Jieming Mao
32 papers receiving 219 citations
Peers
Comparison fields: 5 of 34
- Management Science and Operations Research 108
- Marketing 78
- Signal Processing 53
- Computer Science Applications 21
- Computer Vision and Pattern Recognition 42
Countries citing papers authored by Jieming Mao
This map shows the geographic impact of Jieming Mao'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 Jieming Mao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jieming Mao more than expected).
Fields of papers citing papers by Jieming Mao
This network shows the impact of papers produced by Jieming Mao. 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 Jieming Mao. The network helps show where Jieming Mao may publish in the future.
Co-authors
The 25 scholars most cited alongside Jieming Mao, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 32 | |
| 2 | 2021 | 24 | |
| 3 | 2000 | 18 | |
| 4 | 2000 | 16 | |
| 5 | Contextual Pricing for Lipschitz Buyers | 2018 | 14 |
| 6 | 2016 | 14 | |
| 7 | 2014 | 11 | |
| 8 | 2021 | 9 | |
| 9 | 2000 | 9 | |
| 10 | 2022 | 9 | |
| 11 | 2018 | 8 | |
| 12 | 2021 | 7 | |
| 13 | 2017 | 6 | |
| 14 | 2019 | 6 | |
| 15 | 2019 | 6 | |
| 16 | 2016 | 4 | |
| 17 | 2023 | 4 | |
| 18 | Incentivizing Exploration with Unbiased Histories | 2018 | 3 |
| 19 | 2015 | 3 | |
| 20 | 2018 | 3 |
About Jieming Mao
Jieming Mao is a scholar working on Management Science and Operations Research, Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition and Marketing, having authored 37 papers that have together received 225 indexed citations. Recurring topics across this work include Auction Theory and Applications (16 papers), Consumer Market Behavior and Pricing (8 papers), Digital Filter Design and Implementation (8 papers), Image and Signal Denoising Methods (8 papers), Optimization and Search Problems (6 papers), Complexity and Algorithms in Graphs (6 papers), Privacy-Preserving Technologies in Data (5 papers) and Cryptography and Data Security (4 papers). The work is most often cited by research in Management Science and Operations Research (108 citations), Marketing (78 citations), Signal Processing (53 citations), Computer Science Applications (21 citations) and Computer Vision and Pattern Recognition (42 citations). Jieming Mao has collaborated with scholars based in United States, Hong Kong and China. Frequent co-authors include Song Zuo, Vahab Mirrokni, Yuan Deng, S. C. Chan, K.L. Ho, Santiago Balseiro, Mark Braverman, S. Matthew Weinberg, Xi Chen and Matthew Joseph. Their work appears in journals such as IEEE Signal Processing Letters, Theoretical Computer Science, IEEE Transactions on Information Theory, IEEE Transactions on Signal Processing and ACM Transactions on Algorithms.
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.