Wencheng Lau-medrano
Estudiante De Doctorado at University of Montpellier
Tourbes, Occitania, France
Summary
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Senior🎓
Top SchoolWencheng Lau-medrano is a marine biologist and PhD candidate at the University of Montpellier with 11 years of experience applying machine learning and predictive modeling to fisheries and aquatic ecosystems. He has led field biomass estimation campaigns—including Antarctic krill surveys—and developed automated tools and Shiny visualizations to translate large satellite and ecological datasets into actionable fisheries reports. His work spans pelagic, demersal and highly migratory stocks, combining hands-on sampling, ecosystem modeling (OSMOSE calibration) and spatial-temporal standardization methods (VAST). Currently his doctoral research focuses on using AI to improve stock sizing and dynamics for Indian Ocean tuna, bridging academic research with policy-relevant outreach. Colleagues value his ability to convert complex models into practical monitoring tools and to foster collaborations across NGOs, researchers and managers. An uncommon strength is his track record of moving between intensive field programs and advanced computational workflows, ensuring models stay grounded in real-world data.
12 years of coding experience
Bachillerato, Marine Biology and Biological Oceanography, Bachillerato, Marine Biology and Biological Oceanography at Universidad Nacional Mayor de San MarcosMaestría, Ciencias del mar, Maestría, Ciencias del mar at Universidad Peruana Cayetano Heredia
English, French
Stackoverflow
703reputation
26kreached
29answers
10questions
Github Skills (64)
r-package10
windows10
ide10
image-filters10
powertoys10
command-palette10
r9
rstudio9
overleaf9
pdf9
tex9
latex9
noaa-data9
spatial8
raster8
Programming languages (8)
Github contributions (5)
LuisLauM/imagine
Sep 2016 - Oct 2022
Imaging Engine, Tools for Application of Image Filters to Data Matrices
Contributions:52 commits, 9 PRs, 69 pushes in 6 years 2 months
image-filtersimaging
LuisLauM/grec
Jun 2017 - Feb 2020
Classification of spatial patterns from environmental data through GRadient RECognition
Contributions:51 commits, 8 PRs, 65 pushes in 2 years 7 months
classification
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