Andres Felipe Posada Moreno
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En esta página

  • Clases
    • Learning-based Control Seminar
    • Artificial Intelligence and Data Analytics for Engineers
    • Seminarios de la Academia Internacional RWTH
    • Diseño Mecatrónico
  • Charlas
    • Invertible Neural Networks in Production
  • Tesis Supervisadas
    • Por definir
    • Foundation Models for Industrial Time Series
    • Semi-Supervised Learning Approaches for Fault Detection and Isolation in Automotive Powertrain Systems
    • Combining Foundation Models with Classical State Estimation
    • Foundation Models for Dynamical Systems
    • AI Enhanced Fatigue Strength Prediction for Ductile Cast Iron
    • Application of Explainable Artificial Intelligence (XAI) for Time Series Data in Industrial Robotics
    • Classifying deformation behavior in crash analysis using spatial-temporal information from few samples
    • Establishing Interpretability of Neural Networks for Time Series Sensory Data Analysis
    • Assessment of a machine learning model for defect detection in steel production
    • Model-Based Object Tracking using Robust Gaussian Filters on RGB-D Images of a Moving Camera
    • An Automatic Approach for Global Interpretability of Image-Based Classification
    • Extracting Human-Understandable Highlevel Concepts from Deep Learning Based Classification Models for Industrial Use Cases Utilizing Concept Activation Vectors
    • Analysis of Hierarchical Reinforcement Learning for Robotics
    • Investigation of Behavior in Deep Reinforcement Learning Agents via Activation Pattern Analysis

Docencia

Clases

Learning-based Control Seminar

DSME - Universidad RWTH Aachen | WS2025, WS2023, WS2022, WS2021

Artificial Intelligence and Data Analytics for Engineers

IMA (Laboratorio de Cibernética) - Universidad RWTH Aachen | SS2020, SS2019

Seminarios de la Academia Internacional RWTH

Universidad RWTH Aachen | 2018 – 2019

  • “Production Technology Meets Industry 4.0” — Escuela de verano de 1 semana (agosto 2019)
  • “Smart Factories” — Escuela de invierno de 1 semana (febrero 2019)
  • “Smart Engineering for Smart Factories” — Escuela de invierno de 1 semana (junio 2018)
  • “Industry 4.0” — Escuela de invierno de 1 semana (abril 2018)

Diseño Mecatrónico

Universidad EIA | Colombia | 2014

Charlas

Invertible Neural Networks in Production

Keio International Mini-Symposium | Noviembre 2020

Tesis Supervisadas

Por definir

Lukas Haverbeck | Tesis de Maestría | 2026

Foundation Models for Industrial Time Series

Noah Drein | Tesis de Maestría | 2026

Semi-Supervised Learning Approaches for Fault Detection and Isolation in Automotive Powertrain Systems

Jonas Kneppe | Tesis de Maestría | Co-supervisor: Tobias Brinkmann | 2025

Combining Foundation Models with Classical State Estimation

Tobin Holtmann | Tesis de Maestría | Co-supervisor: David Stenger | 2025

Foundation Models for Dynamical Systems

Martin Ziegler | Tesis de Maestría | Co-supervisor: Friedrich Solowjow | 2024

AI Enhanced Fatigue Strength Prediction for Ductile Cast Iron

Yao Yao | Tesis de Maestría | Co-supervisor: Felix Weber | 2022

Application of Explainable Artificial Intelligence (XAI) for Time Series Data in Industrial Robotics

Tobias Kastenholz | Tesis de Maestría | Co-supervisor: Minh Trinh | 2022

Classifying deformation behavior in crash analysis using spatial-temporal information from few samples

Revan Kumar Dhanasekaran | Tesis de Maestría | 2021

Establishing Interpretability of Neural Networks for Time Series Sensory Data Analysis

Nils Hütten | Tesis de Maestría | 2021

Assessment of a machine learning model for defect detection in steel production

Antonia Holzapfel | Tesis de Licenciatura | 2021

Model-Based Object Tracking using Robust Gaussian Filters on RGB-D Images of a Moving Camera

Tobias Vogel | Tesis de Licenciatura | Co-supervisor: Henrik Hose | 2021

An Automatic Approach for Global Interpretability of Image-Based Classification

Nikita Surya | Tesis de Maestría | 2020

Extracting Human-Understandable Highlevel Concepts from Deep Learning Based Classification Models for Industrial Use Cases Utilizing Concept Activation Vectors

Lukas Kreisköether | Tesis de Maestría | 2020

Analysis of Hierarchical Reinforcement Learning for Robotics

Malte Mosbach | Tesis de Maestría | 2020

Investigation of Behavior in Deep Reinforcement Learning Agents via Activation Pattern Analysis

Melanie Lu | Tesis de Maestría | 2019

© 2025 Andres Felipe Posada Moreno. Licenciado bajo CC BY-NC-SA 4.0.

 

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