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Hi! Hallo! Oi!

I am a doctoral researcher at the Institute for Modelling Hydraulic and Environmental Systems (University of Stuttgart) and passionate about programmatic approaches. My interests are on river connectivity and associated hydro-morphodynamics, which I approach with fuzzy-based and data-driven methods, database management, web development/scraping, and geospatial Python. My latest projects involved hypothesis testing of bedload drivers, a novel fuzzy interpretation of riverbed clogging, developing a web app and database in Django for hydro-environmental analyses, and leveraging the power of GoogLeNet for mapping river landscape elements.

Python  Django  Pandas  Selenium  Pytorch  HTML  MySQL  Anaconda  Bash  Latex  Pycharm 

Beatriz Negreiros's Projects

alembic icon alembic

⚗️ A Jekyll boilerplate theme designed to be a starting point for any Jekyll website

flopy icon flopy

A Python package to create, run, and post-process MODFLOW-based models.

fuzzycorr icon fuzzycorr

A Python package for correlating simulated with observed datasets via fuzzy map comparison.

github-stats icon github-stats

Automatically generate summary GitHub statistics images for your profile using Actions, no server required

minimal icon minimal

Minimal is a Jekyll theme for GitHub Pages

riodetrend icon riodetrend

Structured python codes to detrend DEMs of fluvial systems.

riodetrend-1 icon riodetrend-1

Remove trend of a digital elevation model (DEM) of rivers

routines_hydro icon routines_hydro

Useful routines for handling input and output data from HYDRO_AS-2D and HYDRO_FT-2D

sediment-analyst icon sediment-analyst

A python package for performing sedimentological analyses, including user interface (app).

skspatial icon skspatial

Simple Functions for spatial interpolation using machine learning

thesis-tex-template icon thesis-tex-template

This repository contains tex templates for writing a master thesis in the usual format of the University of Stuttgart.

web-scraping-wos icon web-scraping-wos

A program to scrape papers from Web of Science, get useful information (title, author, citations, abstract, journal) and store it in tables (.csv).

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