PINlab

PINlab has four main research directions.

Computer vision and machine learning for perception.

We work on methods that endow machines and robots with visual perception of the environment and the intelligence to reason about it and take decisions. Our research covers detection, recognition, re-identification and forecasting.

Distributed and multi-agent intelligent systems.

We study perception and intelligence in settings where multiple agents, robots, sensors or people interact, with a focus on robust reasoning and decision making in dynamic environments.

General intelligence and learning.

We investigate reasoning, meta-learning and domain adaptation to build models that generalize across tasks, data distributions and application scenarios.

Sustainable and interpretable AI.

We develop low-power and constrained-resource approaches for sensors and devices, with an emphasis on interpretable and verifiable artificial intelligence.