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Modern neural networks are widely applied in a variety of learning tasks due to their exceptional performance, but fail to express uncertainty about predictions. For example, if a neural network is trained to predict whether an image contains a cat or a dog and is given an elephant as input, it will not admit that it is unsure. With a relatively high probability the machine learning model will instead still choose cat or dog. For high-risk domains like healthcare and autonomous driving this is not the best approach. In these areas, the cost and damage caused by overconfident or underconfident predictions can be catastrophic.

Dr. Sergi Abadal completed his NEC Student Research Fellowship with NEC Laboratories Europe on the topic, iGNNspector: Graph-Driven Acceleration of Graph Neural Networks. He recently received a 2022 European Research Council Starting Grant to continue his research.

Recent studies show that human gut microbiome plays a key role in regulating human health. Yet despite this, there are no clinical diagnostic tools that use microbiota to identify imbalances within our gut that can lead to serious disease, or tools for identifying existing disease. To help overcome this NEC have developed the machine learning model and system, NEC MicrobiomePredict, which analyzes a person’s gut microbiome to predict whether they are suffering from a disease.

NEC Laboratories Europe is helping lead the way for NEC with its core and applied research. In this recent article, Dr. Xavier Costa, Head of 5G &6G Networks at NEC Laboratories, recently discussed some of our latest research with the Spanish newspaper, Elmundo, including our open RAN solutions, cross-border autonomous driving edge approach, automated search and rescue drone technology (SARDO) and the future of smart surfaces.