Adam Galper

415 total citations
5 papers, 91 citations indexed

About

Adam Galper is a scholar working on Artificial Intelligence, Information Systems and Management and Computer Networks and Communications. According to data from OpenAlex, Adam Galper has authored 5 papers receiving a total of 91 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 2 papers in Information Systems and Management and 1 paper in Computer Networks and Communications. Recurrent topics in Adam Galper's work include Bayesian Modeling and Causal Inference (3 papers), AI-based Problem Solving and Planning (3 papers) and Machine Learning in Healthcare (2 papers). Adam Galper is often cited by papers focused on Bayesian Modeling and Causal Inference (3 papers), AI-based Problem Solving and Planning (3 papers) and Machine Learning in Healthcare (2 papers). Adam Galper collaborates with scholars based in United States. Adam Galper's co-authors include Paul Dagum, Eric Horvitz, Elizabeth Seiver, Douglas L. Brutlag and Adam Seiver and has published in prestigious journals such as International Journal of Human-Computer Studies, International Journal of Forecasting and Computer applications in the biosciences.

In The Last Decade

Adam Galper

5 papers receiving 81 citations

Peers

Adam Galper
Faraz Hussain United States
Adam Galper
Citations per year, relative to Adam Galper Adam Galper (= 1×) peers Faraz Hussain

Countries citing papers authored by Adam Galper

Since Specialization
Citations

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

Fields of papers citing papers by Adam Galper

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Adam Galper

This figure shows the co-authorship network connecting the top 25 collaborators of Adam Galper. A scholar is included among the top collaborators of Adam Galper 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 Adam Galper. Adam Galper is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

5 of 5 papers shown
1.
Dagum, Paul & Adam Galper. (1995). Time series prediction using belief network models. International Journal of Human-Computer Studies. 42(6). 617–632. 24 indexed citations
2.
Dagum, Paul, Adam Galper, Eric Horvitz, & Elizabeth Seiver. (1995). Uncertain reasoning and forecasting. International Journal of Forecasting. 11(1). 73–87. 39 indexed citations
3.
Dagum, Paul, Adam Galper, & Adam Seiver. (1994). Automating ARDS Management: A Dynamical Systems Approach. 1 indexed citations
4.
Galper, Adam, et al.. (1993). Knowledge-based simulation of DNA metabolism: Prediction of action and envisionment of pathways. 365–395. 7 indexed citations
5.
Brutlag, Douglas L., et al.. (1991). Knowledge-based simulation of DNA metabolism: prediction of enzyme action. Computer applications in the biosciences. 7(1). 9–19. 20 indexed citations

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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