David Hallac
Impact in
- Signal Processing top 5%
- Time Series Analysis and Forecasting
- Artificial Intelligence top 10%
- Anomaly Detection Techniques and Applications
- Advanced Graph Neural Networks
- Bayesian Modeling and Causal Inference
- Data Stream Mining Techniques
Papers in
- Surgery 2
- Surgical Sutures and Adhesives 1
- Co-authors
- Jure Leskovec (5 shared papers)Stephen Boyd (4 shared papers)Gregory Simonian (2 shared papers)Herbert Dardik (2 shared papers)Rosalyn E. Stahl (1 shared paper)Claire Donnat (1 shared paper)Marinka Žitnik (1 shared paper)Ibrahim Ibrahim (1 shared paper)
- Journals
- The American Journal of Surgery (1 paper)PubMed (3 papers)arXiv (Cornell University) (1 paper)Vascular Surgery (1 paper)
- Partner nations
- United States
In The Last Decade
David Hallac
7 papers receiving 376 citations
Peers
Comparison fields: 5 of 88
- Signal Processing 132
- Artificial Intelligence 191
- Statistical and Nonlinear Physics 46
- Hematology 34
- Computational Mathematics 2
Countries citing papers authored by David Hallac
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
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-authors
The 8 scholars most cited alongside David Hallac, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 174 | |
| 2 | 2017 | 107 | |
| 3 | 2018 | 52 | |
| 4 | 1992 | 40 | |
| 5 | Spectral Graph Wavelets for Structural Role Similarity in Networks | 2018 | 10 |
| 6 | 1997 | 5 | |
| 7 | Learning the Network Structure of Heterogeneous Data via Pairwise Exponential Markov Random Fields. | 2017 | 2 |
About David Hallac
David Hallac is a scholar working on Artificial Intelligence, Surgery, Computer Vision and Pattern Recognition, Signal Processing and Economics and Econometrics, having authored 7 papers that have together received 390 indexed citations. Recurring topics across this work include Time Series Analysis and Forecasting (2 papers), Complex Systems and Time Series Analysis (2 papers), Statistical Methods and Inference (1 paper), Wound Healing and Treatments (1 paper), Data Visualization and Analytics (1 paper), Hemostasis and retained surgical items (1 paper), Bioinformatics and Genomic Networks (1 paper) and Surgical Sutures and Adhesives (1 paper). The work is most often cited by research in Signal Processing (132 citations), Artificial Intelligence (191 citations), Statistical and Nonlinear Physics (46 citations), Hematology (34 citations) and Computational Mathematics (2 citations). David Hallac has collaborated with scholars based in United States. Frequent co-authors include Jure Leskovec, Stephen Boyd, Gregory Simonian, Herbert Dardik, Rosalyn E. Stahl, Claire Donnat, Marinka Žitnik and Ibrahim Ibrahim. Their work appears in journals such as The American Journal of Surgery, PubMed, arXiv (Cornell University) and Vascular Surgery.
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.