William B. Haskell
Impact in
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- Risk and Portfolio Optimization
Papers in
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- Risk and Portfolio Optimization 25
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- Reinforcement Learning in Robotics 11
- Stochastic Gradient Optimization Techniques 7
- Co-authors
- Rahul Jain (9 shared papers)Milind Tambe (5 shared papers)Guodong Yu (2 shared papers)M. Poremba (1 shared paper)P. L. Yu (5 shared papers)Alejandro Toriello (1 shared paper)Matthew Brown (1 shared paper)Vincent Y. F. Tan (3 shared papers)
- Journals
- IEEE Transactions on Automatic Control (3 papers)Annals of Operations Research (3 papers)Operations Research (3 papers)SIAM Journal on Optimization (2 papers)IISE Transactions (2 papers)
- Partner nations
- United StatesSingaporeChina
In The Last Decade
William B. Haskell
48 papers receiving 482 citations
Peers
Comparison fields: 5 of 78
- Management Science and Operations Research 202
- General Decision Sciences 13
- Industrial and Manufacturing Engineering 64
- Statistics and Probability 48
- Organizational Behavior and Human Resource Management 47
Countries citing papers authored by William B. Haskell
This map shows the geographic impact of William B. Haskell'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 William B. Haskell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William B. Haskell more than expected).
Fields of papers citing papers by William B. Haskell
This network shows the impact of papers produced by William B. Haskell. 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 William B. Haskell. The network helps show where William B. Haskell may publish in the future.
Co-authors
The 25 scholars most cited alongside William B. Haskell, 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 49 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 47 | |
| 2 | 2014 | 45 | |
| 3 | 2014 | 41 | |
| 4 | 2014 | 38 | |
| 5 | 2015 | 36 | |
| 6 | 2016 | 29 | |
| 7 | 2016 | 27 | |
| 8 | 2017 | 26 | |
| 9 | 2018 | 21 | |
| 10 | 2019 | 19 | |
| 11 | 2013 | 19 | |
| 12 | 2014 | 14 | |
| 13 | 2023 | 14 | |
| 14 | 2018 | 12 | |
| 15 | 2017 | 11 | |
| 16 | 2019 | 11 | |
| 17 | 2021 | 10 | |
| 18 | 2015 | 10 | |
| 19 | 2017 | 8 | |
| 20 | 2013 | 7 |
About William B. Haskell
William B. Haskell is a scholar working on Management Science and Operations Research, Artificial Intelligence, Economics and Econometrics, Management Information Systems and Computational Mechanics, having authored 49 papers that have together received 512 indexed citations. Recurring topics across this work include Risk and Portfolio Optimization (25 papers), Reinforcement Learning in Robotics (11 papers), Sparse and Compressive Sensing Techniques (7 papers), Stochastic Gradient Optimization Techniques (7 papers), Supply Chain and Inventory Management (7 papers), Economic theories and models (6 papers), Decision-Making and Behavioral Economics (4 papers) and Markov Chains and Monte Carlo Methods (3 papers). The work is most often cited by research in Management Science and Operations Research (202 citations), General Decision Sciences (13 citations), Industrial and Manufacturing Engineering (64 citations), Statistics and Probability (48 citations) and Organizational Behavior and Human Resource Management (47 citations). William B. Haskell has collaborated with scholars based in United States, Singapore and China. Frequent co-authors include Rahul Jain, Milind Tambe, Guodong Yu, M. Poremba, P. L. Yu, Alejandro Toriello, Matthew Brown, Vincent Y. F. Tan, Dileep Kalathil and Maged Dessouky. Their work appears in journals such as IEEE Transactions on Automatic Control, Annals of Operations Research, Operations Research, SIAM Journal on Optimization and IISE Transactions.
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.