Teaching

2019-2020. Speech and Language Processing with Deep Learning

In charge of the practical project, consisting of training word embeddings, language models, speech classification models.

2019-2020. Introduction to Deep Learning

In charge of project sessions in Pytorch: Linear and logistic regression, Multilayer perceptron, Multiclass classification, ConvNets.

2019-2020. Deep Learning for AI

Final project instructor, guiding students in topic selection, deep learning framework selection, technical approach to follow, implementation, etc.

2018-2019. Natural Language Processing with Deep Learning

Lectures: * Contextual Word Embeddings. * Summarization. * Unsupervised Neural Machine Translation. * Generative Adversarial Networks in NLP.

2018-2019. Introduction to Deep Learning

Polytechnic University of Catalonia (UPC).

In charge of project sessions, including:

  • Linear and logistic regression in Pytorch.
  • Multilayer perceptron in Pytorch.
  • Multiclass classification and ConvNets in Pytorch.

2018-2019. Deep Learning for AI

Polytechnic University of Catalonia (UPC).

Final project instructor, guiding students with their final projects, from topic selection, deep learning framework selection, technical approach to follow, implementation, cloud environment setup, etc.

2017-2018. Deep Learning for AI

Polytechnic University of Catalonia (UPC).

Teaching assistant at the practical sessions, including:

  • Keras and TensorBoard
  • PyTorch
  • TensorFlow

2017-2018. Introduction to Deep Learning

Polytechnic University of Catalonia (UPC).

In charge of project sessions, including:

  • Linear and logistic regression in Keras.
  • Multilayer perceptron in Keras.
  • Multiclass classification and ConvNets.
  • Model performance evaluation metrics.

2017-2018. Matlab and its Applications in Engineering

Polytechnic University of Catalonia (UPC).

Subject taught online. In charge of preparing and grading assingments and final project.

2012-2013. Probability and Statistics

Polytechnic University of Madrid (UPM). Same syllabus as the next entry.

2011-2012. Probability and Statistics

Polytechnic University of Madrid (UPM)

Part-time lecturer, teaching:

  • Descriptive statistic analysis.
  • Foundations of probability theory.
  • Random variables, discrete and continuous.
  • Confidence intervals.
  • Hypothesis testing, parametric and non-parametric.
teaching experience

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