Brian C. Franczak
- Artificial Intelligence top 10%
- Statistics and Probability top 5%
- Cell Biology
- Molecular Biology
- Pollution
- Co-authors
- Paul D. McNicholasRyan P. BrowneTrevor J. HamiltonNathan A. MagarveyMichael A. SkinniderChris A. DejongCristina TortoraMelike Schalomon
- Topics
- Bayesian Methods and Mixture Models (7 papers)Statistical Methods and Bayesian Inference (5 papers)Advanced Statistical Methods and Models (3 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceThe Science of The Total EnvironmentScientific Reports
- Partner nations
- CanadaUnited StatesItaly
In The Last Decade
Brian C. Franczak
16 papers receiving 274 citations
Peers
Comparison fields: 5 of 81
- Artificial Intelligence 100
- Statistics and Probability 66
- Cell Biology 51
- Molecular Biology 43
- Pollution 36
Countries citing papers authored by Brian C. Franczak
This map shows the geographic impact of Brian C. Franczak'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 Brian C. Franczak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Brian C. Franczak more than expected).
Fields of papers citing papers by Brian C. Franczak
This network shows the impact of papers produced by Brian C. Franczak. 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 Brian C. Franczak. The network helps show where Brian C. Franczak may publish in the future.
Co-authorship network of co-authors of Brian C. Franczak
This figure shows the co-authorship network connecting the top 25 collaborators of Brian C. Franczak. A scholar is included among the top collaborators of Brian C. Franczak based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Brian C. Franczak. Brian C. Franczak is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 39 | |
| 3 | 3 | |
| 4 | 35 | |
| 5 | 4 | |
| 6 | 11 | |
| 7 | 8 | |
| 8 | 10 | |
| 9 | 21 | |
| 10 | 1 | |
| 11 | 38 | |
| 12 | 3 | |
| 13 | 11 | |
| 14 | 8 | |
| 15 | Mixtures of Multiple Scaled Generalized Hyperbolic Distributions | 2 |
| 16 | Model-Based Clustering Using Mixtures of Coalesced Generalized Hyperbolic Distributions | 1 |
| 17 | 87 |
About Brian C. Franczak
Brian C. Franczak is a scholar working on Statistics and Probability, Artificial Intelligence and Virology, having authored 17 papers that have together received 282 indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (7 papers), Statistical Methods and Bayesian Inference (5 papers) and Advanced Statistical Methods and Models (3 papers). The work is most often cited by research in Statistics and Probability (66 citations), Industrial and Manufacturing Engineering (29 citations) and Artificial Intelligence (100 citations). Brian C. Franczak has collaborated with scholars based in Canada, United States and Italy. Frequent co-authors include Paul D. McNicholas, Ryan P. Browne, Trevor J. Hamilton, Nathan A. Magarvey, Michael A. Skinnider, Chris A. Dejong, Cristina Tortora, Melike Schalomon, Rachel Dean and Matthew S. Ross. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, The Science of The Total Environment and Scientific Reports.
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.