I am a geologist, a paleontologist, and a network scientist. My research interests are centered around understanding how major geological events, long-term ecological changes, and historical contingencies have shaped the evolutionary history of the Metazoa. To address specific questions on the biosedimentary record, I use a cross-disciplinary approach that combines paleobiological and geological data, with modern spatial statistical and network science tools. I am currently a postdoctoral fellow at the Integrated Science Lab (IceLab), a hub dedicated to cross-disciplinary research located at Umeå University in northern Sweden. IceLab research covers a wide range of scientific questions on the fossil record, social networks, phytoplankton, DNA folding, microbial economics, invasive species, and antibiotic resistance.

Geoscience education at all levels is an integral component of my research program and I use the physical and abstracted fossil records (digital representations) for teaching/learning geosciences in formal and informal learning settings. If you have any questions please don’t hesitate to contact me.

External Links:

Google Scholar || ORCID || ResearchGate || Linkedin || CvLAC || alexis.rojas-briceno@umu.se


Click here to visit selected field localities using Google TIME MACHINE

NEWS!

Date: Wednesday 11 December 2019

Preprint: Low-Latitude Origins of the Four Phanerozoic Evolutionary Faunas. Using a multilayer network representation of the fossil record, we demonstrate that Phanerozoic oceans sequentially harbored four evolutionary faunas. This work resolves the conflict between two central hypotheses in macroevolution: The Three Great Evolutionary Faunas and the Mesozoic Marine Revolution.

Date: Friday 2 August 2019

I attended the GEOCHRONOLOGY: TIMING, TEMPO AND DRIVERS OF BIOTIC EVOLUTION – GORDON RESEARCH CONFERENCE at Waterville Valley, NH, USA. August 4 – 9.

Date: Wednesday 29 May 2019

New Preprint!

Joaquín, C., Bernardo, R., Neuman, M., Rojas, A., Rosvall, M., 2019: Exploring the solution landscape enables more reliable network community detection. arXiv:1905.11230 [physics.soc-ph]