Panos Toulis
- Statistics and Probability top 5%
- Artificial Intelligence top 10%
- Management Science and Operations Research
- Education
- Statistical and Nonlinear Physics
- Co-authors
- Edoardo M. AiroldiDavid C. ParkesGuillaume BasseAvi FellerAzeem M. ShaikhNikolaos MavridisWajahat KazmiChiraz BenAbdelkader
- Topics
- Advanced Causal Inference Techniques (5 papers)Stochastic Gradient Optimization Techniques (5 papers)Statistical Methods and Inference (5 papers)
- Partner nations
- United StatesGreeceUnited Arab Emirates
In The Last Decade
Panos Toulis
14 papers receiving 231 citations
Peers
Comparison fields: 5 of 81
- Statistics and Probability 105
- Artificial Intelligence 92
- Management Science and Operations Research 23
- Education 21
- Statistical and Nonlinear Physics 20
Countries citing papers authored by Panos Toulis
This map shows the geographic impact of Panos Toulis'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 Panos Toulis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Panos Toulis more than expected).
Fields of papers citing papers by Panos Toulis
This network shows the impact of papers produced by Panos Toulis. 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 Panos Toulis. The network helps show where Panos Toulis may publish in the future.
Co-authorship network of co-authors of Panos Toulis
This figure shows the co-authorship network connecting the top 25 collaborators of Panos Toulis. A scholar is included among the top collaborators of Panos Toulis 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 Panos Toulis. Panos Toulis 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 | 10 | |
| 4 | Minimax Crossover Designs | 4 |
| 5 | Convergence diagnostics for stochastic gradient descent with constant learning rate. | 13 |
| 6 | 30 | |
| 7 | 55 | |
| 8 | Statistical inference of long-term causal effects in multiagent systems under the Neyman-Rubin model. | 0 |
| 9 | Stability and optimality in stochastic gradient descent. | 2 |
| 10 | 26 | |
| 11 | 24 | |
| 12 | Implicit stochastic gradient descent for principled estimation with large datasets | 3 |
| 13 | Estimation of Causal Peer Influence Effects | 46 |
| 14 | 12 | |
| 15 | 5 | |
| 16 | 7 |
About Panos Toulis
Panos Toulis is a scholar working on Statistics and Probability, Transplantation and Artificial Intelligence, having authored 16 papers that have together received 241 indexed citations. Recurring topics across this work include Advanced Causal Inference Techniques (5 papers), Stochastic Gradient Optimization Techniques (5 papers) and Statistical Methods and Inference (5 papers). The work is most often cited by research in Statistics and Probability (105 citations), Transplantation (10 citations) and Artificial Intelligence (92 citations). Panos Toulis has collaborated with scholars based in United States, Greece and United Arab Emirates. Frequent co-authors include Edoardo M. Airoldi, David C. Parkes, Guillaume Basse, Avi Feller, Azeem M. Shaikh, Nikolaos Mavridis, Wajahat Kazmi, Chiraz BenAbdelkader, Pericles A. Mitkas and Dionysios Kehagias. Their work appears in journals such as Journal of the American Statistical Association, Econometrica and Biometrika.
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.