David Hallac

1.3k total citations
6 papers, 348 citations indexed

About

David Hallac is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, David Hallac has authored 6 papers receiving a total of 348 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 2 papers in Computer Vision and Pattern Recognition and 2 papers in Signal Processing. Recurrent topics in David Hallac's work include Time Series Analysis and Forecasting (2 papers), Complex Systems and Time Series Analysis (2 papers) and Hemostasis and retained surgical items (1 paper). David Hallac is often cited by papers focused on Time Series Analysis and Forecasting (2 papers), Complex Systems and Time Series Analysis (2 papers) and Hemostasis and retained surgical items (1 paper). David Hallac collaborates with scholars based in United States. David Hallac's co-authors include Jure Leskovec, Stephen Boyd, Herbert Dardik, Gregory Simonian, Marinka Žitnik and Claire Donnat and has published in prestigious journals such as The American Journal of Surgery, arXiv (Cornell University) and PubMed.

In The Last Decade

David Hallac

6 papers receiving 337 citations

Peers

David Hallac
Xuan He China
Ivelin Stoianov Netherlands
Huan Song United States
Meike Nauta Netherlands
Matthew Olson United States
David Hallac
Citations per year, relative to David Hallac David Hallac (= 1×) peers Daniele Zambon

Countries citing papers authored by David Hallac

Since Specialization
Citations

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

Fields of papers citing papers by David Hallac

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Hallac

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

All Works

6 of 6 papers shown
1.
Donnat, Claire, Marinka Žitnik, David Hallac, & Jure Leskovec. (2018). Spectral Graph Wavelets for Structural Role Similarity in Networks. arXiv (Cornell University). 9 indexed citations
2.
Hallac, David, et al.. (2018). Toeplitz Inverse Covariance-based Clustering of Multivariate Time Series Data. 5254–5258. 47 indexed citations
3.
Hallac, David, et al.. (2017). Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data. PubMed. 2017. 215–223. 159 indexed citations
4.
Hallac, David, et al.. (2017). Learning the Network Structure of Heterogeneous Data via Pairwise Exponential Markov Random Fields.. PubMed. 54. 1302–1310. 2 indexed citations
5.
Hallac, David, et al.. (2017). Network Inference via the Time-Varying Graphical Lasso. PubMed. 2017. 205–213. 93 indexed citations
6.
Simonian, Gregory, et al.. (1992). Comparative efficacy of topical hemostatic agents in a rat kidney model. The American Journal of Surgery. 163(2). 234–238. 38 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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