Mauricio Tec
Impact in
- Transportation top 10%
- Urban Transport and Accessibility
- Modeling and Simulation top 10%
- COVID-19 epidemiological studies
Papers in
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- Statistical Methods and Bayesian Inference 3
- Advanced Causal Inference Techniques 2
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- Health Systems, Economic Evaluations, Quality of Life 2
- Co-authors
- James G. Scott (4 shared papers)Natalia Zuniga-Garcia (1 shared paper)Randy B. Machemehl (1 shared paper)Abigail R.A. Aiken (1 shared paper)Catherine Aiken (1 shared paper)Rebecca Gomperts (1 shared paper)Jennifer E. Starling (1 shared paper)Lauren Ancel Meyers (2 shared papers)
- Journals
- Transportation Research Part C Emerging Technologies (1 paper)American Journal of Epidemiology (1 paper)Nature Communications (1 paper)Pharmaceutical Statistics (1 paper)Journal of the American Statistical Association (1 paper)
- Partner nations
- United StatesSouth KoreaSouth Sudan
In The Last Decade
Mauricio Tec
10 papers receiving 177 citations
Peers
Comparison fields: 5 of 69
- Transportation 50
- Modeling and Simulation 29
- Reproductive Medicine 31
- Obstetrics and Gynecology 28
- Automotive Engineering 41
Countries citing papers authored by Mauricio Tec
This map shows the geographic impact of Mauricio Tec'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 Mauricio Tec with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mauricio Tec more than expected).
Fields of papers citing papers by Mauricio Tec
This network shows the impact of papers produced by Mauricio Tec. 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 Mauricio Tec. The network helps show where Mauricio Tec may publish in the future.
Co-authors
The 25 scholars most cited alongside Mauricio Tec, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 60 | |
| 2 | 2022 | 55 | |
| 3 | 2022 | 33 | |
| 4 | 2021 | 13 | |
| 5 | 2022 | 6 | |
| 6 | 2025 | 5 | |
| 7 | 2023 | 5 | |
| 8 | 2024 | 3 | |
| 9 | Random clique covers for graphs with local density and global sparsity | 2018 | 1 |
| 10 | 2022 | 1 | |
| 11 | 2023 | 0 | |
| 12 | 2024 | 0 |
About Mauricio Tec
Mauricio Tec is a scholar working on Statistics and Probability, Economics and Econometrics, Artificial Intelligence, Modeling and Simulation and Molecular Biology, having authored 12 papers that have together received 182 indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (3 papers), Advanced Causal Inference Techniques (2 papers), Health Systems, Economic Evaluations, Quality of Life (2 papers), COVID-19 epidemiological studies (2 papers), Gaze Tracking and Assistive Technology (1 paper), Cell Image Analysis Techniques (1 paper), COVID-19 Digital Contact Tracing (1 paper) and Advanced Graph Neural Networks (1 paper). The work is most often cited by research in Transportation (50 citations), Modeling and Simulation (29 citations), Reproductive Medicine (31 citations), Obstetrics and Gynecology (28 citations) and Automotive Engineering (41 citations). Mauricio Tec has collaborated with scholars based in United States, South Korea and South Sudan. Frequent co-authors include James G. Scott, Natalia Zuniga-Garcia, Randy B. Machemehl, Abigail R.A. Aiken, Catherine Aiken, Rebecca Gomperts, Jennifer E. Starling, Lauren Ancel Meyers, Spencer J. Fox and Xutong Wang. Their work appears in journals such as Transportation Research Part C Emerging Technologies, American Journal of Epidemiology, Nature Communications, Pharmaceutical Statistics and Journal of the American Statistical Association.
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.