Andres C Rodriguez

Andres C Rodriguez

PhD Student at ETH Zurich

EcoVision Lab - Photogrammetry and Remote Sensing at ETH Zurich

Biography

I am a PhD student at ETH Zurich working at the intersection of Remote Sensing, Computer Vision and Machine Learning. I joined the EcoVision Lab in 2017 after finishing my master studies in Statistics at ETH Zurich.

Born and raised in Colombia, I developed a broader perception of global challenges like poverty, human rights and deforestation; which is why I actively direct my research towards solving them.

My current research interests are Machine Learning for Optical and Radar satellite imagery in large-scale applications, Fine-grained classification and Semi-supervised learning.

See my CV.

Contact: andres.rodriguez(at)geod.baug.ethz.ch

Interests
  • Machine Learning
  • Remote Sensing
  • Data Efficency
  • Sensor Fusion
  • Fine Grained Classification
Education
  • PhD in Photogrammetry and Remote Sensing, 2022 (expected)

    ETH Zurich

  • Master in Science in Statistics, 2015

    ETH Zurich

  • BSc in Industrial Engineering, 2012

    Pontificia Universidad Javeriana

Experience

 
 
 
 
 
Research Assistant - PhD Student
Oct 2017 – Present Zurich, Switzerland

Responsibilities include:

  • Teaching Assistant Image Processing, Machine Learning and Multivariate Statistics
  • Organizer of the first Machine Learning Workshop for Environmental and Geosciences MLEG2019
  • BS and MS Thesis supervisor in deforestation detection in tropical regions, cocoa mapping and avalance mapping.
 
 
 
 
 
Research Assistant
ETH Zurich - Chair of Risk and Insurance Economics
Apr 2016 – Sep 2017 Zurich, Switzerland

Responsibilities include:

  • Data processing with STATA and R
  • Statistical Analysis: Models for panel data using Logistic Regression, Hurdle models and Box-Cox Regression.
 
 
 
 
 
Research Assistant
Pontificia Universidad Javeriana - Faculty of Engineering
Apr 2016 – Sep 2017 Zurich, Switzerland

Responsibilities include:

  • Joint Research Project with University of Washington, WA and Northeastern University, MA
  • Data collection with WBV equipment in Mining Heavy Equipment.
  • Data processing with Labview, SAS and R.
  • Statistical Analysis: Logistic Regression, Mixed Models and Box-Cox Regression on Epidemiological.
  • See related academic output in the publications section.

Publications

(2021). Mapping Oil Palm Density at Country Scale: an Active Learning Approach / in review.

Cite

(2018). Fast cosmic web simulations with generative adversarial networks. Computational Astrophysics and Cosmology.

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