Julia Stoyanovich
- Artificial Intelligence top 2%
- Information Systems top 2%
- Safety Research top 1%
- Management Science and Operations Research top 2%
- Computer Networks and Communications top 5%
- Co-authors
- Ke YangBill HoweH. V. JagadishSusan B. DavidsonVal TannenSebastian SchelterAbolfazl AsudehMeike Zehlike
- Topics
- Ethics and Social Impacts of AI (28 papers)Data Management and Algorithms (18 papers)Explainable Artificial Intelligence (XAI) (18 papers)
- Journals
- SHILAP Revista de lepidopterologíaBioinformaticsCommunications of the ACM
- Partner nations
- United StatesIsraelNetherlands
In The Last Decade
Julia Stoyanovich
83 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 110
- Artificial Intelligence 741
- Information Systems 382
- Safety Research 364
- Management Science and Operations Research 266
- Computer Networks and Communications 239
Countries citing papers authored by Julia Stoyanovich
This map shows the geographic impact of Julia Stoyanovich'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 Julia Stoyanovich with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Julia Stoyanovich more than expected).
Fields of papers citing papers by Julia Stoyanovich
This network shows the impact of papers produced by Julia Stoyanovich. 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 Julia Stoyanovich. The network helps show where Julia Stoyanovich may publish in the future.
Co-authorship network of co-authors of Julia Stoyanovich
This figure shows the co-authorship network connecting the top 25 collaborators of Julia Stoyanovich. A scholar is included among the top collaborators of Julia Stoyanovich 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 Julia Stoyanovich. Julia Stoyanovich is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 4 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 16 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 0 | |
| 9 | 0 | |
| 10 | 22 | |
| 11 | Lightweight Inspection of Data Preprocessing in Native Machine Learning Pipelines. | 12 |
| 12 | Nutritional Labels for Data and Models | 27 |
| 13 | 3 | |
| 14 | 89 | |
| 15 | 1 | |
| 16 | Enabling privacy in provenance-aware workflow systems | 19 |
| 17 | 1 | |
| 18 | EntityAuthority: Semantically Enriched Graph-Based Authority Propagation | 6 |
| 19 | 3 | |
| 20 | 7 |
About Julia Stoyanovich
Julia Stoyanovich is a scholar working on Safety Research, Health Informatics and Artificial Intelligence, having authored 94 papers that have together received 1.4k indexed citations. Recurring topics across this work include Ethics and Social Impacts of AI (28 papers), Data Management and Algorithms (18 papers) and Explainable Artificial Intelligence (XAI) (18 papers). The work is most often cited by research in Health Informatics (67 citations), Safety Research (364 citations) and Information Systems and Management (198 citations). Julia Stoyanovich has collaborated with scholars based in United States, Israel and Netherlands. Frequent co-authors include Ke Yang, Bill Howe, H. V. Jagadish, Susan B. Davidson, H. V. Jagadish, Val Tannen, Sebastian Schelter, Abolfazl Asudeh, Meike Zehlike and Marina Drosou. Their work appears in journals such as SHILAP Revista de lepidopterología, Bioinformatics and Communications of the ACM.
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.