Khashayar Pakdaman
- Statistical and Nonlinear Physics top 0.5%
- Cognitive Neuroscience top 2%
- Computer Networks and Communications top 2%
- Molecular Biology
- Modeling and Simulation top 1%
- Co-authors
- Seiji TanabeShunsuke SatoGilles WainribPierre‐Yves BoëlleTakashi TatenoBenoı̂t PerthameDelphine SalortTaishin Nomura
- Topics
- Neural dynamics and brain function (51 papers)stochastic dynamics and bifurcation (48 papers)Nonlinear Dynamics and Pattern Formation (35 papers)
In The Last Decade
Khashayar Pakdaman
85 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 111
- Statistical and Nonlinear Physics 1.2k
- Cognitive Neuroscience 907
- Computer Networks and Communications 707
- Molecular Biology 230
- Modeling and Simulation 204
Countries citing papers authored by Khashayar Pakdaman
This map shows the geographic impact of Khashayar Pakdaman'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 Khashayar Pakdaman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Khashayar Pakdaman more than expected).
Fields of papers citing papers by Khashayar Pakdaman
This network shows the impact of papers produced by Khashayar Pakdaman. 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 Khashayar Pakdaman. The network helps show where Khashayar Pakdaman may publish in the future.
Co-authorship network of co-authors of Khashayar Pakdaman
This figure shows the co-authorship network connecting the top 25 collaborators of Khashayar Pakdaman. A scholar is included among the top collaborators of Khashayar Pakdaman 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 Khashayar Pakdaman. Khashayar Pakdaman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 54 | |
| 2 | 23 | |
| 3 | 12 | |
| 4 | 79 | |
| 5 | 13 | |
| 6 | 14 | |
| 7 | Tonic-to-Bursting Bifurcations in Neuronal Recordings and HH-type Computer Simulations. | 1 |
| 8 | 10 | |
| 9 | 62 | |
| 10 | 18 | |
| 11 | Leaky Integrate-and-Fire 神経モデルのアンサンブルのダイナミクスとパルス入力に対する応答 | 0 |
| 12 | 11 | |
| 13 | 36 | |
| 14 | 9 | |
| 15 | Dynamical stability of human locomotion | 1 |
| 16 | 18 | |
| 17 | 5 | |
| 18 | 22 | |
| 19 | Modeling Excitatory Networks (数理生物学における最近の話題--神経コ-ディングを中心に ) -- (神経コ-ディングの非線形力学系モデルによる解析) | 1 |
| 20 | 4 |
About Khashayar Pakdaman
Khashayar Pakdaman is a scholar working on Statistical and Nonlinear Physics, Cognitive Neuroscience and Computer Networks and Communications, having authored 87 papers that have together received 1.8k indexed citations. Recurring topics across this work include Neural dynamics and brain function (51 papers), stochastic dynamics and bifurcation (48 papers) and Nonlinear Dynamics and Pattern Formation (35 papers). The work is most often cited by research in Statistical and Nonlinear Physics (1.2k citations), Cognitive Neuroscience (907 citations) and Modeling and Simulation (204 citations). Khashayar Pakdaman has collaborated with scholars based in France, Japan and Uruguay. Frequent co-authors include Seiji Tanabe, Shunsuke Sato, Shunsuke Sato, Gilles Wainrib, Pierre‐Yves Boëlle, Takashi Tateno, Benoı̂t Perthame, Delphine Salort, Taishin Nomura and Antoine Flahault. Their work appears in journals such as Nature Medicine, PLoS ONE and Emerging infectious diseases.
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.