William La Cava

51 papers and 1.6k indexed citations i.

About

William La Cava is a scholar working on Artificial Intelligence, Molecular Biology and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, William La Cava has authored 51 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Artificial Intelligence, 9 papers in Molecular Biology and 8 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in William La Cava’s work include Evolutionary Algorithms and Applications (20 papers), Metaheuristic Optimization Algorithms Research (13 papers) and Machine Learning and Data Classification (10 papers). William La Cava is often cited by papers focused on Evolutionary Algorithms and Applications (20 papers), Metaheuristic Optimization Algorithms Research (13 papers) and Machine Learning and Data Classification (10 papers). William La Cava collaborates with scholars based in United States, Portugal and Italy. William La Cava's co-authors include Jason H. Moore, Randal S. Olson, Ryan J. Urbanowicz, Melissa Meeker, Patryk Orzechowski, Lee Spector, Kourosh Danai, Yi Guo, Jonathan Keller and Thomas Helmuth and has published in prestigious journals such as Circulation, Bioinformatics and Journal of the American College of Cardiology.

In The Last Decade

Co-authorship network of co-authors of William La Cava i

Fields of papers citing papers by William La Cava

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by William La Cava. 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 William La Cava. The network helps show where William La Cava may publish in the future.

Countries citing papers authored by William La Cava

Since Specialization
Citations

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

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2025