Teaching

Neural networks

Assistant professor (in charge) since 2022, Data Mining Master, Universidad Austral.
Introduction to neural networks for industry oriented applications.

Deep learning

Assistant professor since 2021, Informatics Engineering & graduate course, Universidad Nacional del Litoral. Introduction and deep dive on deep learning techniques and applications. I’m in charge of autoencoders, generative models and (introduction to) NLP modules.

Final project

Assistant professor (in charge) since 2022, Robotics and Automation Associate degree, Universidad Nacional del Litoral.
Last subject in the program, with the aim of giving tools to and mentoring students to complete an integrative project of their choosing.

Digital Image Processing

Teaching assistant since 2017, Informatics Engineering, Universidad Nacional del Litoral.
Covers digital image basics and perception, space and frequency domain operations, restauration, color processing, compression and segmentation.

Sporadic courses

Introduction to Machine Learning

Teaching and course preparation in 2022 Bootcamp, Women in Bioinformatics and Data Science LA

Machine learning for bioinformatics

Assistant professor 2020 & 2021, Asociación Argentina de Bioinformática y Biología Computacional
Machine learning methods used in bioinformatics, including clustering, dimensional reduction, supervised learning and neural networks.

Machine learning with applications

Assistant professor in 2019 & 2021, graduate course, Universidad Nacional de Entre Ríos
The course includes basic machine learning techniques applied on signals, images and structured data using the Python ecosystem.

Courses for the industry

• 2021: Introduction to autoencoders, assistant professor (in charge), YPF-Tec
• 2021: Introduction to data science, assistant professor, Knowledge economy training program for regional governments
• 2019: LabAI: Fundamentals of deep learning, teaching assistant, Folder IT

Thesis and projects supervision

Completed

• Development of a tool for automatic identification of foraging rhythm of leaf-cutting ants from video records, 2022, F. Sturniolo, Informatics Eng., U. Nacional del Litoral
• Automation system for data extraction from digitized invoices, A. Gorostidi, E. Claucich, Informatics Eng.
• Classification of telegram digits from the legislative elections in Santa Fe using domain adaptation techniques, F. Lianza, Master’s degree in data science, U. Austral

Ongoing

-Representation learning for secuential data applied to structure prediction in bioinformatics, tesis doctoral Luciano Zablocki, UNL, 2023

• Development of a framework based on machine learning for research on relationships between non-coding RNA and diseases, M. Ramonell, Bioengineering, U. Nacional de Entre Ríos
• Use of a machine learning model for the prediction of interactions between bioactive Bacillus metabolites and their possible target proteins in the wheat pathogens Xanthomonas translucens and Pseudomonas syringae (co-advisor), V. Fumero, Master’s degree in data science, U. Austral
• Computational biomechanical modeling and learning techniques Machine to estimate Gait Dynamics in the absence of force Platforms (co-advisor), J. Beret, Ph.D. in Engineering
• Prediction of risk of accidents in the steel industry from reports of incidents from personnel applying text mining techniques, C. Couste, Master’s degree in data science, U. Austral
• Automatic assistant for mushroom harvesting, Specialization in artificial intelligence, M. Hunkeler, U. Nacional de Buenos Aires