Dana Mackenzie

1.1k citations
52 papers · 554 indexed · 1 hit paper · h-index 9

Impact in

Papers in

Dana Mackenzie

41 papers receiving 504 citations

Hit Papers

The Book of Why: The New Science of Cause and Effect 2018 · 316 citations
3162018202620202023100200300

Peers

Dana Mackenzie
Comparison fields: 5 of 152
  • Statistics and Probability 43
  • Theoretical Computer Science 5
  • Health Informatics 6
  • Artificial Intelligence 141
  • Management Science and Operations Research 29
Replace Cornelis Kraaikamp with:
Cornelis Kraaikamp Netherlands
Michael P. Cohen United States
Daniel Reichman United States
Thomas Bayes
Michael Cox United Kingdom
Nurul Huda Abd Rahman Malaysia
Daniel G. Brooks United States
Hans Rudi Fischer United States
Murray Hochberg United States
Roland Schinzinger United States
Dana Mackenzie relative to Cornelis Kraaikamp Netherlands Cornelis Kraaikamp's profile →
Citations per field
00.5×
Cornelis Kraaikamp · 1×
Citations per year

Countries citing papers authored by Dana Mackenzie

Since Specialization
Citations

This map shows the geographic impact of Dana Mackenzie'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 Dana Mackenzie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dana Mackenzie more than expected).

Fields of papers citing papers by Dana Mackenzie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dana Mackenzie. 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 Dana Mackenzie. The network helps show where Dana Mackenzie may publish in the future.

Co-authors

The 3 scholars most cited alongside Dana Mackenzie, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Dana Mackenzie Line = papers co-authored together Dana Mackenzie links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20241
2 20151
3 20134
4 20120
5 20110
6
Take it to the limit
20051
7 20039
8 20034
9 20023
10 20021
11 19993
12 19981
13
Equality and the Charter: Ten Years of Feminist Advocacy Before the Supreme Court of Canada
19983
14 19971
15 19971
16 19973
17 19972
18 199515
19 19952
20 19840

About Dana Mackenzie

Dana Mackenzie is a scholar working on Theoretical Computer Science, Architecture, Applied Mathematics, Computational Theory and Mathematics and Geometry and Topology, having authored 52 papers that have together received 554 indexed citations. Recurring topics across this work include History and Theory of Mathematics (4 papers), Big Data and Business Intelligence (2 papers), Modular Robots and Swarm Intelligence (2 papers), Point processes and geometric inequalities (2 papers), Mathematics and Applications (2 papers), Advanced Numerical Analysis Techniques (2 papers), Ophthalmology and Visual Impairment Studies (2 papers) and Geometric Analysis and Curvature Flows (2 papers). The work is most often cited by research in Statistics and Probability (43 citations), Theoretical Computer Science (5 citations), Health Informatics (6 citations), Artificial Intelligence (141 citations) and Management Science and Operations Research (29 citations). Dana Mackenzie has collaborated with scholars based in Brazil, United States and Canada. Frequent co-authors include Judea Pearl, Herman Gluck and Frank Morgan. Their work appears in journals such as Science, Engineering, Duke Mathematical Journal, Scientific American and American Scientist.

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.

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