Maykol Rodríguez Prieto
- Kontakt
-
Wissenschaftlicher Mitarbeiter
E-mail: maykol.rodriguez.prieto@wirtschaft.uni-giessen.de
Telefon: 0641 / 99-22644
Addresse: Licher Str. 64, 35394 Gießen
- Akademischer und beruflicher Werdegang
- Akademischer und beruflicher Werdegang
-
Academic career
- Since 2022- Ph.D. in Economics Justus-Liebig-Universität Gießen. Germany.
- 2019- MA Economics, Rosario University, Colombia.
- 2013 -BA Mathematics, Javeriana University, Colombia.
Academic-professional activities
- 2021 Environmental economics and natural resources Assistant Professor, Los Andes University, Bogotá.
- 2020-2022 Data analyst and policy maker, Secretaría Distrital de Desarrollo Económico.
- 2017-2020 Biomathematics Professor, Rosario University, Bogota.
- 2017-2020 Programming Professor (R and Python), Rosario University, Bogota.
- 2018-2019 Young Researcher, forest conservation and implications for sustainability in the peri‐urban bogota (Colombia), Rosario University, Bogota.
- 2017 Differential Equations and Numerical Methods Professor, Piloto University, Bogota.
- 2017 Linear Algebra and Linear Programming Professor, Rosario University, Bogota.
- 2016-2017 Economics Mathematics Assistant Professor, Universidad del Rosario.
Topics research
- Conflict economics and armed conflicts.
- Network theory.
- Economic modelling.
- Political violence.
Publications
- Cardenas-Sánchez, D., Sampayo, AM, Rodríguez-Prieto, M. et al. Un marco comparativo para analizar la convergencia en las conversaciones electorales de Twitter. Informe científico 12, 19062 (2022).
- Marco, J.; Valderrama, D.; Rueda, M., Rodriguez-Prieto, M. (2021): Improving Utilization of the Queen Conch (Aliger gigas) Resource in the Colombian Caribbean: A Bioeconomic Model of Rotational Harvesting. Marine Resource Economics.
- 2021 Rodriguez-Prieto, M.; Bodini, A; Escobedo, F; Clerici, N. (2021): Analyzing socio-ecological interactions through qualitative modeling: Forest conservation and implications for sustainability in the peri‐urban bogota (Colombia). Ecological Modelling 439 (2021) 109344.