Ilia Vovsha
- Artificial Intelligence top 2%
- Information Systems top 2%
- Sociology and Political Science top 10%
- Statistical and Nonlinear Physics top 5%
- Management Science and Operations Research top 10%
- Co-authors
- Owen RambowRebecca J. PassonneauApoorv AgarwalBoyi XieRaphael PelossofCynthia RudinMichael JonesJulia Hirschberg
- Topics
- Preterm Birth and Chorioamnionitis (2 papers)Pregnancy and preeclampsia studies (1 paper)Advanced Text Analysis Techniques (1 paper)
- Journals
- Columbia Academic Commons (Columbia University)National Conference on Artificial Intelligence
- Partner nations
- United States
In The Last Decade
Ilia Vovsha
6 papers receiving 864 citations
Hit Papers
Peers
Comparison fields: 5 of 81
- Artificial Intelligence 810
- Information Systems 287
- Sociology and Political Science 150
- Statistical and Nonlinear Physics 122
- Management Science and Operations Research 60
Countries citing papers authored by Ilia Vovsha
This map shows the geographic impact of Ilia Vovsha'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 Ilia Vovsha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ilia Vovsha more than expected).
Fields of papers citing papers by Ilia Vovsha
This network shows the impact of papers produced by Ilia Vovsha. 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 Ilia Vovsha. The network helps show where Ilia Vovsha may publish in the future.
Co-authorship network of co-authors of Ilia Vovsha
This figure shows the co-authorship network connecting the top 25 collaborators of Ilia Vovsha. A scholar is included among the top collaborators of Ilia Vovsha 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 Ilia Vovsha. Ilia Vovsha is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Using Kernel Methods and Model Selection for Prediction of Preterm Birth. | 2 |
| 2 | Predicting Preterm Birth Is Not Elusive: Machine Learning Paves the Way to Individual Wellness | 16 |
| 3 | 1 | |
| 4 | Sentiment Analysis of Twitter Databreakdown → | 892 |
| 5 | 38 | |
| 6 | 26 |
About Ilia Vovsha
Ilia Vovsha is a scholar working on Obstetrics and Gynecology, Language and Linguistics and Artificial Intelligence, having authored 6 papers that have together received 975 indexed citations. Recurring topics across this work include Preterm Birth and Chorioamnionitis (2 papers), Pregnancy and preeclampsia studies (1 paper) and Advanced Text Analysis Techniques (1 paper). The work is most often cited by research in Artificial Intelligence (810 citations), Information Systems (287 citations) and Statistical and Nonlinear Physics (122 citations). Ilia Vovsha has collaborated with scholars based in United States. Frequent co-authors include Owen Rambow, Rebecca J. Passonneau, Apoorv Agarwal, Boyi Xie, Raphael Pelossof, Cynthia Rudin, Michael Jones, Julia Hirschberg, Štefan Beňuš and Agustı́n Gravano. Their work appears in journals such as Columbia Academic Commons (Columbia University) and National Conference on Artificial Intelligence.
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.