Farzad Sabzikar
- Modeling and Simulation top 0.5%
- Applied Mathematics top 5%
- Numerical Analysis top 5%
- Finance top 5%
- Statistical and Nonlinear Physics top 5%
- Co-authors
- Mark M. MeerschaertJinghua ChenMantha S. PhanikumarДонатас СургайлисA. Ian McLeodKrzysztof BurneckiPiotr KokoszkaPeter C.B. Phillips
- Topics
- Complex Systems and Time Series Analysis (12 papers)Financial Risk and Volatility Modeling (11 papers)Fractional Differential Equations Solutions (5 papers)
- Journals
- Journal of Computational PhysicsJournal of EconometricsChaos An Interdisciplinary Journal of Nonlinear Science
- Partner nations
- United StatesSingaporeNew Zealand
In The Last Decade
Farzad Sabzikar
14 papers receiving 493 citations
Hit Papers
Peers
Comparison fields: 5 of 50
- Modeling and Simulation 357
- Applied Mathematics 191
- Numerical Analysis 160
- Finance 102
- Statistical and Nonlinear Physics 93
Countries citing papers authored by Farzad Sabzikar
This map shows the geographic impact of Farzad Sabzikar'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 Farzad Sabzikar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Farzad Sabzikar more than expected).
Fields of papers citing papers by Farzad Sabzikar
This network shows the impact of papers produced by Farzad Sabzikar. 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 Farzad Sabzikar. The network helps show where Farzad Sabzikar may publish in the future.
Co-authorship network of co-authors of Farzad Sabzikar
This figure shows the co-authorship network connecting the top 25 collaborators of Farzad Sabzikar. A scholar is included among the top collaborators of Farzad Sabzikar 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 Farzad Sabzikar. Farzad Sabzikar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 4 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 10 | |
| 9 | 8 | |
| 10 | 14 | |
| 11 | 36 | |
| 12 | Tempered fractional calculusbreakdown → | 280 |
| 13 | 12 | |
| 14 | 67 | |
| 15 | 79 |
About Farzad Sabzikar
Farzad Sabzikar is a scholar working on Finance, Modeling and Simulation and Economics and Econometrics, having authored 15 papers that have together received 518 indexed citations. Recurring topics across this work include Complex Systems and Time Series Analysis (12 papers), Financial Risk and Volatility Modeling (11 papers) and Fractional Differential Equations Solutions (5 papers). The work is most often cited by research in Modeling and Simulation (357 citations), Numerical Analysis (160 citations) and Applied Mathematics (191 citations). Farzad Sabzikar has collaborated with scholars based in United States, Singapore and New Zealand. Frequent co-authors include Mark M. Meerschaert, Jinghua Chen, Mantha S. Phanikumar, Донатас Сургайлис, A. Ian McLeod, Krzysztof Burnecki, Piotr Kokoszka, Peter C.B. Phillips, Qiying Wang and Paul L. Anderson. Their work appears in journals such as Journal of Computational Physics, Journal of Econometrics and Chaos An Interdisciplinary Journal of Nonlinear Science.
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.