Opportunities

This is a list of topics I am interested in. The list is not exhaustive! If you are interested in a particular topic, email me to discuss a potential research project or BSc/MSc thesis.

Topics

• Machine Learning for Genetic Data
  We would like to apply ML techniques to genetica data to infer some properties, e.g., the biogeographical ancestry.

• Machine Learning for Social Sciences
  We would like to apply DL techniques to social sciences. I am particularly interested in the application of graph-based models to economic data.

• Machine Learning for Anomaly Detection
  We would like to use ML for anomaly detection. In particular, we are interested in investigating approaches such as unsupervised learning (i.e., generative models) and continual learning.

• Latent Space Organization of Generative Models
  Pushing generative models, such as VAE, to organize their latent space based on the semantics of the input. Such an organization should be inferred automatically by porividing to the model some examples of data manipulations (e.g., the sum operator for images that represent digits).

• Tensor-based Recursive Neural Networks for Static Code Analysis
  Deepening the use of tensor-based RecNN to infer properties of code snippets from their syntactic trees.

• Deep Learning for Soccer Data Analysis
  We would like to apply DL techniques for images to extract players’/teams’ stats directly from soccer match videos/data.