Portfolio
Nga NGUYEN is a data scientist with 9-year full time experience in sustainability
https://www.linkedin.com/in/npn112/
SKILLS
Project management, research proposal, communication
Python (NumPy, Pandas, MatplotLib, GDAL/OGR etc)
R, SQL, SPARQL, PostGIS, GitHub
QGIS, ArcGIS, ERDAS, ENVI
Google Earth Engine
Google Cloud Platform, Amazon Web Service
Tableau, PowerBI, Plotly, D3.js
Adobe suite: Illustrator, Photoshop
LANGUAGES
Vietnamese (native)
English (bilingual)
French (B2)
Dutch (A2)
Mandarin (A2)
AWARDS
École Polytechnique Excellence Scholarship
Erasmus Mundus Scholarship
Arcadia University Scholarship
Bucknell University Scholarship
INTERESTS
Microcontroller (Arduino, Rasberry Pi) for Internet of things (smart robots, smart agriculture)
Computer numerical control machines (3D printing, laser/wood engraving)
Water sports, horse riding
This section contains codes or writings for assessment purposes
The academic writing sample is a single-authored research project created during the Master in Environmental Sciences, Policy and Management, titled "Prediction of land use pattern in Vietnam in year 2050 under different policy scenarios"
The policy wiring sample is a report for the trust fund PROFOR within the World Bank, with sections that are written by me and reviewed or edited by others: Chapter 3 "Stakeholder- centered PEA approaches" from the publication "The Political Economy of Decision-Making in Forestry : Using Evidence and Analysis for Reform"
Assessment_R.R is a file that illustrates different image manipulation techniques in R, including unsupervised machine learning (CLARA and Kmean) and supervised machine learning (Random forest) with validation using ground truthing and vegetation indices (NDVI and EVI). The codes were written for Mac; for Windows, please follow the instruction to change 2 commands. There are also commented-out sections that were meant for manual manipulations of images (selection of boundary box or vegetated/water/urban/other area), followed by hard-coded values, please feel free to test the manual options as well.
s2_25_sept_2016.img is the input file for the Assessment_R.R file