Recurrent neural networks
The human brain is a recurrent neural network (RNN): a network of neurons with feedback connections. It can learn many behaviors / sequence processing tasks / algorithms / programs that are not learnable by traditional machine learning methods.
Machine learning of temporal data
A time series is a sequence of observations of the same variable, collected over time.
At IDSIA, we cover different research areas related to time series, such as forecasting, time series classification and anomaly detection.
Bayesian Networks (BNs)
Bayesian Networks are foundational model in machine learning and artificial intelligence.
Causal analysis and Knowledge Engineering
To understand the causal relations between model variables, dedicated mathematical tools are required.
Reinforcement learning and POMDPs
Work at IDSIA has led to the first universal reinforcement learner for essentially arbitrary computable environments.
Graph and geometric deep learning
Graph and geometric deep learning are machine learning fields that combine graph representations for data and machine learning to exploit the inductive bias associated with the presence of functional dependencies among data
Security for Machine Learning, Machine Learning for security
Security is both a key enabler and an extremely relevant application for machine learning

Department of Innovative Technologies
Dalle Molle Institute for Artificial Intelligence USISUPSI
Polo universitario Lugano  Campus Est, Via la Santa 1
CH6962 LuganoViganello
T +41 (0)58 666 66 66
info@idsia.ch

Faculty of Informatics
Università della Svizzera italiana
Polo universitario Lugano, Campus Est, via La Santa 1
6900 LuganoViganello
T +41 (0)58 666 46 90
decanato.inf@usi.ch