Mark Fleischer

About

Mark Fleischer is a scholar working on Artificial Intelligence, Computer Networks and Communications and Computational Theory and Mathematics. According to data from OpenAlex, Mark Fleischer has authored 5 papers receiving a total of 24 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Artificial Intelligence, 1 paper in Computer Networks and Communications and 1 paper in Computational Theory and Mathematics. Recurrent topics in Mark Fleischer’s work include Metaheuristic Optimization Algorithms Research (2 papers), Markov Chains and Monte Carlo Methods (1 paper) and Machine Learning and Data Classification (1 paper). Mark Fleischer is often cited by papers focused on Metaheuristic Optimization Algorithms Research (2 papers), Markov Chains and Monte Carlo Methods (1 paper) and Machine Learning and Data Classification (1 paper). Mark Fleischer collaborates with scholars based in United States. Mark Fleischer's co-authors include Sheldon H. Jacobson, Kelly A. Sullivan, Ashok Kumar and Alan W. Johnson and has published in prestigious journals such as INFORMS journal on computing, Journal of Heuristics and Journal of Medical Marketing Device Diagnostic and Pharmaceutical Marketing.

In The Last Decade

Co-authorship network of co-authors of Mark Fleischer i

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Fields of papers citing papers by Mark Fleischer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Mark Fleischer

Since Specialization

Citations

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

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