Christian Pieringer
Assistant Professor · Universidad de Las Américas
I am an assistant professor at Universidad de Las Américas (Chile) working on machine learning and computer vision from limited labeled data, applied to industrial inspection and scientific data, and currently exploring self-supervised learning.
Research Areas
- Industrial inspection: X-ray object recognition and nondestructive testing, including multi-view detection and public benchmarks such as GDXray.
- Machine learning for scientific and biomedical data: learning under data scarcity and class imbalance, from medical data to phage–host interaction prediction and variable star classification.
- Applied perception systems: vision-language models for quality assessment and tactile object recognition in robotic grippers.
- (Emerging) self-supervised learning and representation learning: learning representations from unlabeled data, with ongoing work on object counting and re-identification.
Teaching & Mentoring
Current
Capstone Project (CDD7028 y CDD9028)
Applied final project sequence for the Magíster en Ciencia de Datos, from problem definition to delivery.
Contents: Problem framing · Data pipeline and modeling · Experiment design · Technical writing and defense
Algorithms and Data Structures (ACI600)
Course focused on fundamental algorithms and data structures for computer science and data-oriented programs.
Contents: Algorithm analysis · Arrays and linked lists · Stacks and queues · Trees and graphs · Sorting and searching
Introduction to Data Science (DIP2627)
Course focused on providing fundamental concept for data science.
Contents: Introduction to Data Science · Data Science methodologies · Exploratory data analysis · Python fundamentals for Data Science
Past
Computer Vision (EIC-371)
Course focused in provide fundamental theory in computer vision.
Contents: Geometric transformations · Camera calibration · Multiple-view geometry · Object detection and segmentation
Advanced Computer Programming
Course focused in the provided advanced programming concept for computer science.
Contents: Oriented programming · Data structures · Functional programming · Event-based simulation (EBS)
Selected Publications
Articles
A machine learning approach to predict strain-specific phage-host interactions
Scientific Reports, 2025
From Classification to Captioning: Adapting Vision-Language Models for Fruit Quality Description
IEEE CHILECON, 2025
AI for Biomedical Data, 2025
Poultry Science, 2023
Books
Advanced Computer Programming in Python
CreateSpace, 2017
Students
Students I advise or co-advise
Current
Marcelo Yáñez -- Graduate
Co-advisor: R. Coronado
Matías Labraña -- Graduate
Co-advisor: R. Coronado
Felipe Goicolea -- Graduate
Co-advisor: R. Coronado
Alumni
Jorge Meléndez -- Graduate
Failure prediction in telecontrol equipment using survival analysis
Co-advisor: R. Coronado
Jorge Cáceres -- Graduate
Estimating acceptance propensity for credit card limit increases using machine learning models
Co-advisor: F. Pérez-Galarce
Marcos Chupica -- Undergraduate
A data augmentation framework to improve variable star classifiers
Code
Open-source code and datasets
Official Python toolbox for Computer Vision for X-Ray Testing (companion to the Springer book).
Colaborador. Public X-ray image database for nondestructive testing and computer vision research.
Teaching materials for an introduction to programming in Python.
Curated list of datasets commonly used in computer vision.