Chris Hans
Impact in
- Statistics and Probability top 1%
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
- Advanced Statistical Methods and Models
- Artificial Intelligence top 5%
- Bayesian Methods and Mixture Models
- Bayesian Modeling and Causal Inference
Papers in
-
- Bayesian Methods and Mixture Models 3
- Bayesian Modeling and Causal Inference 2
- Machine Learning and Algorithms 1
-
- Statistical Methods and Inference 5
- Statistical Methods and Bayesian Inference 3
- Markov Chains and Monte Carlo Methods 1
- Co-authors
- Adrian Dobra (3 shared papers)Mike West (3 shared papers)Beatrix Jones (2 shared papers)Joseph R. Nevins (1 shared paper)Guang Yao (1 shared paper)Chris Carter (1 shared paper)Carlos M. Carvalho (1 shared paper)David B. Dunson (1 shared paper)
- Journals
- Journal of the American Statistical Association (2 papers)Statistical Science (1 paper)Biometrics (1 paper)Journal of Computational and Graphical Statistics (1 paper)Journal of Multivariate Analysis (1 paper)
- Partner nations
- United StatesNew ZealandAustralia
In The Last Decade
Chris Hans
8 papers receiving 703 citations
Peers
Comparison fields: 5 of 113
- Statistics and Probability 303
- Artificial Intelligence 311
- Computational Mathematics 4
- Molecular Biology 234
- Management Science and Operations Research 36
Countries citing papers authored by Chris Hans
This map shows the geographic impact of Chris Hans'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 Chris Hans with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chris Hans more than expected).
Fields of papers citing papers by Chris Hans
This network shows the impact of papers produced by Chris Hans. 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 Chris Hans. The network helps show where Chris Hans may publish in the future.
Co-authors
The 13 scholars most cited alongside Chris Hans, 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 | 2004 | 280 | |
| 2 | 2005 | 145 | |
| 3 | 2007 | 143 | |
| 4 | 2011 | 111 | |
| 5 | 2009 | 55 | |
| 6 | 2005 | 12 | |
| 7 | 2012 | 2 | |
| 8 | 2011 | 1 |
About Chris Hans
Chris Hans is a scholar working on Artificial Intelligence, Statistics and Probability, Molecular Biology, Control and Systems Engineering and Infectious Diseases, having authored 8 papers that have together received 749 indexed citations. Recurring topics across this work include Statistical Methods and Inference (5 papers), Statistical Methods and Bayesian Inference (3 papers), Bayesian Methods and Mixture Models (3 papers), Bayesian Modeling and Causal Inference (2 papers), Machine Learning and Algorithms (1 paper), Gene expression and cancer classification (1 paper), Gene Regulatory Network Analysis (1 paper) and Markov Chains and Monte Carlo Methods (1 paper). The work is most often cited by research in Statistics and Probability (303 citations), Artificial Intelligence (311 citations), Computational Mathematics (4 citations), Molecular Biology (234 citations) and Management Science and Operations Research (36 citations). Chris Hans has collaborated with scholars based in United States, New Zealand and Australia. Frequent co-authors include Adrian Dobra, Mike West, Beatrix Jones, Joseph R. Nevins, Guang Yao, Chris Carter, Carlos M. Carvalho, David B. Dunson, Juhee Lee and Greg M. Allenby. Their work appears in journals such as Journal of the American Statistical Association, Statistical Science, Biometrics, Journal of Computational and Graphical Statistics and Journal of Multivariate Analysis.
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.