Justin Bleich
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 2%
- Explainable Artificial Intelligence (XAI)
- Adversarial Robustness in Machine Learning
- Machine Learning and Data Classification
- Machine Learning in Healthcare
- Anomaly Detection Techniques and Applications
Papers in
-
- Data Analysis with R 4
- Neural Networks and Applications 2
- Machine Learning and Data Classification 2
- Anomaly Detection Techniques and Applications 2
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- Gene expression and cancer classification 2
- Co-authors
- Adam Kapelner (5 shared papers)Alex Goldstein (1 shared paper)Emil Pitkin (1 shared paper)Richard A. Berk (3 shared papers)David Mease (1 shared paper)Matthew Olson (1 shared paper)Abraham J. Wyner (1 shared paper)Shane T. Jensen (2 shared papers)
- Journals
- Criminology & Public Policy (2 papers)The Annals of Applied Statistics (1 paper)Journal of Quantitative Criminology (1 paper)Journal of Statistical Software (1 paper)Journal of Machine Learning Research (1 paper)
- Partner nations
- United States
In The Last Decade
Justin Bleich
10 papers receiving 1.7k citations
Justin Bleich's Hit Papers
Peers
Comparison fields: 5 of 170
- Health Informatics 58
- Artificial Intelligence 544
- Statistics and Probability 106
- Environmental Engineering 110
- Health Information Management 30
Countries citing papers authored by Justin Bleich
This map shows the geographic impact of Justin Bleich'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 Justin Bleich with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Justin Bleich more than expected).
Fields of papers citing papers by Justin Bleich
This network shows the impact of papers produced by Justin Bleich. 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 Justin Bleich. The network helps show where Justin Bleich may publish in the future.
Co-authors
The 9 scholars most cited alongside Justin Bleich, 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 | Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual Conditional Expectation Hit paper breakdown → | 2014 | 1158 |
| 2 | 2016 | 163 | |
| 3 | 2017 | 140 | |
| 4 | 2013 | 105 | |
| 5 | 2014 | 87 | |
| 6 | 2013 | 34 | |
| 7 | bartMachine: A Powerful Tool for Machine Learning. | 2013 | 8 |
| 8 | Variable Selection Inference for Bayesian Additive Regression Trees | 2013 | 3 |
| 9 | 2013 | 3 | |
| 10 | Extensions and applications of ensemble-of-trees methods in machine learning | 2015 | 2 |
About Justin Bleich
Justin Bleich is a scholar working on Artificial Intelligence, Molecular Biology, Sociology and Political Science, Management Science and Operations Research and Statistics and Probability, having authored 10 papers that have together received 1.7k indexed citations. Recurring topics across this work include Data Analysis with R (4 papers), Gene expression and cancer classification (2 papers), Neural Networks and Applications (2 papers), Machine Learning and Data Classification (2 papers), Anomaly Detection Techniques and Applications (2 papers), Statistical Methods and Inference (2 papers), Optimal Experimental Design Methods (2 papers) and Crime Patterns and Interventions (2 papers). The work is most often cited by research in Health Informatics (58 citations), Artificial Intelligence (544 citations), Statistics and Probability (106 citations), Environmental Engineering (110 citations) and Health Information Management (30 citations). Justin Bleich has collaborated with scholars based in United States. Frequent co-authors include Adam Kapelner, Alex Goldstein, Emil Pitkin, Richard A. Berk, David Mease, Matthew Olson, Abraham J. Wyner, Shane T. Jensen and Edward I. George. Their work appears in journals such as Criminology & Public Policy, The Annals of Applied Statistics, Journal of Quantitative Criminology, Journal of Statistical Software and Journal of Machine Learning Research.
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.