Justin Sirignano
- Statistical and Nonlinear Physics top 0.5%
- Computational Mechanics top 2%
- Artificial Intelligence top 5%
- Statistics, Probability and Uncertainty top 1%
- Finance top 5%
- Co-authors
- Konstantinos SpiliopoulosKay GieseckeApaar SadhwaniGerry TsoukalasJonathan F. MacArtZiheng WangRichard B. SowersGeorge Papanicolaou
- Topics
- Stochastic processes and financial applications (9 papers)Credit Risk and Financial Regulations (7 papers)Insurance and Financial Risk Management (3 papers)
- Cited by
- Statistical and Nonlinear PhysicsStatistics, Probability and UncertaintyComputational Mechanics
- Partner nations
- United StatesUnited KingdomItaly
In The Last Decade
Justin Sirignano
16 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 72
- Statistical and Nonlinear Physics 989
- Computational Mechanics 445
- Artificial Intelligence 251
- Statistics, Probability and Uncertainty 192
- Finance 186
Countries citing papers authored by Justin Sirignano
This map shows the geographic impact of Justin Sirignano'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 Justin Sirignano with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Justin Sirignano more than expected).
Fields of papers citing papers by Justin Sirignano
This network shows the impact of papers produced by Justin Sirignano. 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 Justin Sirignano. The network helps show where Justin Sirignano may publish in the future.
Co-authorship network of co-authors of Justin Sirignano
This figure shows the co-authorship network connecting the top 25 collaborators of Justin Sirignano. A scholar is included among the top collaborators of Justin Sirignano 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 Justin Sirignano. Justin Sirignano is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 13 | |
| 4 | 50 | |
| 5 | 19 | |
| 6 | 30 | |
| 7 | DGM: A deep learning algorithm for solving partial differential equationsbreakdown → | 1250 |
| 8 | 1 | |
| 9 | 31 | |
| 10 | 4 | |
| 11 | 23 | |
| 12 | 4 | |
| 13 | 4 | |
| 14 | 3 | |
| 15 | 1 | |
| 16 | 3 |
About Justin Sirignano
Justin Sirignano is a scholar working on Finance, Management Science and Operations Research and Statistical and Nonlinear Physics, having authored 16 papers that have together received 1.4k indexed citations. Recurring topics across this work include Stochastic processes and financial applications (9 papers), Credit Risk and Financial Regulations (7 papers) and Insurance and Financial Risk Management (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (989 citations), Statistics, Probability and Uncertainty (192 citations) and Computational Mechanics (445 citations). Justin Sirignano has collaborated with scholars based in United States, United Kingdom and Italy. Frequent co-authors include Konstantinos Spiliopoulos, Kay Giesecke, Apaar Sadhwani, Gerry Tsoukalas, Jonathan F. MacArt, Ziheng Wang, Richard B. Sowers, George Papanicolaou, Narendra Singh and Giulio Gori. Their work appears in journals such as Management Science, Journal of Computational Physics and Operations Research.
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.