Biography
Doctor-PhD. in Geology from the University of Salamanca, highest qualification: Cum laude. Researcher in External Geodynamics. Master in Management and Environmental Sciences. Geology Engineer, Specialist in Applied Geomatics (Geographic Information Systems, Remote Sensing and Numerical Modeling).
Developer of methodologies for the reduction of natural and anthropic risks. Trainer in universities, institutes and ministries in Advanced Applied Geomatics. Speaker at symposiums and workshops nationwide and international. Corrector and advisor of 56 master's theses in management and reduction of Risks. Undergraduate professor in Hydrogeological Risks and Hydrogeochemistry. Director and Undersecretary of Risk Analysis-Secretariat of Risk Management Ecuador
Research Interest
Researcher in Geology, Geomorphology, Applies Geomatics, Geoinformatics (GIS), External Geodinamics, Risk management (Earthquakes, floods, mass movements, tornadoes, hurricanes, volcanic fires, forest fires, dispersion of pollution vectors, social risk, explosions, structural fires, deformations of topographic relief, geological risks in general, among other hazards.
Editor
Work Details
PhD. in Geology, External Geodynamics and Applied Geomatics
University of Salamanca
Department of Geology
Spain
Contribution by Topic Area
PUBLISH YOUR RESEARCH
We publish a wide range of article types in biology, medicine and engineering with no editorial biases.
SubmitSee Manuscript Guidelines and APC
Explore the IgMin Subjects
Which articles are now trending?
Research Articles
- Solar Energy Resource Potentials of the City of Arkadag
- Physical Activity and Lifestyle of Female Students of the Faculty of Health Sciences University of Applied Sciences in Tarnów (Poland)
- Modeling of an Electric-fired Brick Oven, Directly Heated
- Correlation between Different Factors of Non-point Source Pollution in Yangtze River Basin
- Prevalence of Non-specific Low Back Pain Among Chinese Healthcare Workers (Surgeons and Surgical Nurses): A Multi-Center Survey Study
- Enhancing Material Property Predictions through Optimized KNN Imputation and Deep Neural Network Modeling