Yahsuan Yang

Bis 2025, Master’s Thesis Researcher – Maize Yield Prediction with Machine Learning, Humboldt-Universität zu Berlin

Fähigkeiten und Kenntnisse

Biodiversity
Data Analysis
Data Collection
Geographic Information Systems (GIS)
Data Management
Google Earth Engine
QGIS
Document Management
LEED Consulting
R
Agricultural Economics
Earth Observation
Literature Reviews
Random Forest
ArcGIS Products
Editing
Machine Learning
Remote Sensing
AutoCAD
Spectral Analysis
Environmental Impact Assessment
Management
Report Writing
Environmental Science
Microsoft Excel
Statistical Data Analysis
Research
Field Data Collection / Validation
Microsoft Office
Statistical Modeling
RStudio
PowerPoint
Sustainability Consulting
Soil
Project Management
Sustainable Agriculture
Soil Management
Sustainable Design
Spatial Analysis
Teamwork
Workshop Presentation
Master's degree
GIS
Image Processing
International experience
Microsoft Word
Economy

Werdegang

Berufserfahrung von Yahsuan Yang

  • 1 Jahr und 3 Monate, Feb. 2024 - Apr. 2025

    Master’s Thesis Researcher – Maize Yield Prediction with Machine Learning

    Humboldt-Universität zu Berlin

    - Integrated multi-source geospatial datasets (CHIRPS, SoilGrids, MODIS) using Google Earth Engine to construct a harmonised sub-national dataset across 11 sub-counties in Kenya - Developed and evaluated multiple ML models (Random Forest, Ridge, LASSO, SVM, GBM) to analyse environmental drivers of maize yield - Key predictors identified: maximum temperature (Tmax in March/May), soil water saturation (SSAT), and NDVI during the growing season — consistent across linear and non-linear models - Applied PCA-bas

  • 7 Monate, Mai 2022 - Nov. 2022

    Student Intern – Remote Sensing & Vegetation Analysis

    Leibniz Centre for Agricultural Landscape Research (ZALF)

    - Processed hyperspectral field imagery in QGIS, including GeoTIFF conversion, georeferencing, and spectral correction across experimental plots with varying nitrogen treatments - Extracted vegetation spectral signatures and calculated reflectance-based indices (CVI, Green–Red ratio) to characterize plant responses under different conditions - Applied unsupervised clustering (SCP plugin) to differentiate vegetation responses across treatment groups - Validated spectral indices against laboratory-measured le

  • 2 Jahre und 11 Monate, Okt. 2014 - Aug. 2017

    Project Assistant

    Segreene Sustainable Design & Consulting

    - Sustainable Design Consulting for USGBC-Certified Green Building Projects: Contributing expertise to over 15 green building projects certified by the U.S. Green Building Council in Asia. - Enforced Green Building Compliance: Collaborated with architects and contractors to ensure strict compliance with USGBC regulations from design to construction. - Water efficiency and biodiversity data collection and analysis - Certification documentation preparation and technical review oversight - Research green build

  • 2 Jahre und 3 Monate, Mai 2015 - Juli 2017

    Instructor

    Taiwan Green Collar Association

    - Facilitated lectures and workshops. - Prepared course modules include Location & Transportation, Sustainable Sites, Water Efficiency, Material & Resources.

  • 7 Monate, Okt. 2013 - Apr. 2014

    Outreach Coordinator

    Ontario Public Interest Research Group (OPIRG) of Peterborough

    - Coordinated different working groups within OPIRG and designed posters, e-newsletters to promote events. - Organized documentary night and open-mic night for public participation in social issues.

Ausbildung von Yahsuan Yang

  • 6 Jahre und 7 Monate, Okt. 2018 - Apr. 2025

    Master of Science - MS

    Humboldt-Universität zu Berlin

    Coursework completed 2021. Thesis conducted 2024–2025 (grade 1.0) on ML-based maize yield prediction in Kenya.

  • 5 Jahre und 1 Monat, Mai 2009 - Mai 2014

    Bachelor of Science - BS

    Trent University

    Minor in Environmental Science. Active in AIESEC, Trent Oxfam, and campus sustainability initiatives.

Sprachen

  • Chinesisch

    C2 (Verhandlungssicher / Muttersprachlich)

  • Englisch

    C2 (Verhandlungssicher / Muttersprachlich)

  • Deutsch

    B1-B2 (Gute Kenntnisse)

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