David Heckerman
Impact in
- Virology top 0.1%
- HIV Research and Treatment
- Artificial Intelligence top 0.05%
- Bayesian Modeling and Causal Inference
- AI-based Problem Solving and Planning
- Text and Document Classification Technologies
Papers in
-
- Bayesian Modeling and Causal Inference 87
- AI-based Problem Solving and Planning 26
- Machine Learning and Algorithms 16
- Bayesian Methods and Mixture Models 15
-
- vaccines and immunoinformatics approaches 35
- Co-authors
- Dan Geiger (21 shared papers)David M. Chickering (6 shared papers)Eric Horvitz (25 shared papers)Susan Dumais (2 shared papers)Mehran Sahami (2 shared papers)Carl Kadie (44 shared papers)Jennifer Listgarten (21 shared papers)John Platt (1 shared paper)
- Journals
- Journal of Virology (20 papers)PLoS ONE (13 papers)Machine Learning (6 papers)Bioinformatics (6 papers)PLoS Computational Biology (6 papers)
- Partner nations
- United StatesUnited KingdomSouth Africa
In The Last Decade
David Heckerman
245 papers receiving 21.6k citations
David Heckerman's Hit Papers
Peers
Comparison fields: 5 of 219
- Virology 2.5k
- Artificial Intelligence 11.3k
- Signal Processing 2.0k
- Management Science and Operations Research 2.1k
- Information Systems 3.6k
Countries citing papers authored by David Heckerman
This map shows the geographic impact of David Heckerman'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 David Heckerman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Heckerman more than expected).
Fields of papers citing papers by David Heckerman
This network shows the impact of papers produced by David Heckerman. 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 David Heckerman. The network helps show where David Heckerman may publish in the future.
Co-authors
The 25 scholars most cited alongside David Heckerman, 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 252 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Learning Bayesian Networks: The Combination of Knowledge and Statistical Data Hit paper breakdown → | 1995 | 2424 |
| 2 | Learning Bayesian networks: The combination of knowledge and statistical data Hit paper breakdown → | 1995 | 1667 |
| 3 | Efficient Control of Population Structure in Model Organism Association Mapping Hit paper breakdown → | 2008 | 1325 |
| 4 | Inductive learning algorithms and representations for text categorization Hit paper breakdown → | 1998 | 1173 |
| 5 | A Bayesian Approach to Filtering Junk E-Mail Hit paper breakdown → | 1998 | 910 |
| 6 | A Tutorial on Learning with Bayesian Networks Hit paper breakdown → | 2008 | 851 |
| 7 | FaST linear mixed models for genome-wide association studies Hit paper breakdown → | 2011 | 847 |
| 8 | A Tutorial on Learning with Bayesian Networks Hit paper breakdown → | 1998 | 527 |
| 9 | Bayesian Networks for Data Mining Hit paper breakdown → | 1997 | 509 |
| 10 | 2010 | 326 | |
| 11 | 1994 | 294 | |
| 12 | 1996 | 292 | |
| 13 | 1995 | 290 | |
| 14 | 1992 | 287 | |
| 15 | 1995 | 277 | |
| 16 | 2011 | 274 | |
| 17 | 1986 | 246 | |
| 18 | Proceedings of the 3rd International Conference on Knowledge Discovery and Data Mining | 1997 | 239 |
| 19 | Probabilistic Similarity Networks | 1991 | 236 |
| 20 | Probabilistic diagnosis using a reformulation of the INTERNIST-1/QMR knowledge base. I. The probabilistic model and inference algorithms. | 1991 | 235 |
About David Heckerman
David Heckerman is a scholar working on Artificial Intelligence, Molecular Biology, Virology, Immunology and Management Science and Operations Research, having authored 252 papers that have together received 23.3k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (87 papers), HIV Research and Treatment (60 papers), vaccines and immunoinformatics approaches (35 papers), AI-based Problem Solving and Planning (26 papers), T-cell and B-cell Immunology (23 papers), Immune Cell Function and Interaction (20 papers), Machine Learning and Algorithms (16 papers) and Bayesian Methods and Mixture Models (15 papers). The work is most often cited by research in Virology (2.5k citations), Artificial Intelligence (11.3k citations), Signal Processing (2.0k citations), Management Science and Operations Research (2.1k citations) and Information Systems (3.6k citations). David Heckerman has collaborated with scholars based in United States, United Kingdom and South Africa. Frequent co-authors include Dan Geiger, David M. Chickering, Eric Horvitz, Susan Dumais, Mehran Sahami, Carl Kadie, Jennifer Listgarten, John Platt, Christopher Meek and Christoph Lippert. Their work appears in journals such as Journal of Virology, PLoS ONE, Machine Learning, Bioinformatics and PLoS Computational Biology.
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.