PhD Electrical and Electronic Engineering

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I am studying how to use radio signals, specifically focusing on WiFi, to detect vital signs, provide location information indoors, and to classify activity. Together with data for other sensors, such as bluetooth wearable devices, I will be using this information to study behavioural patterns and how these can be related to traceable alterations in the person. To automate annotation of experimental data, of which there will be an amount large enough to make any manual effort too tedious and time consuming, either of, or a combination of, lidar, radar, and commercial indoor positioning systems (such as Pozyx), will be used. I am currently studying and applying techniques for data extraction and fusion from these various sensors. In a bigger-scale experiment, where there will be no ground truth labels, and the sensors will be trusted to varying degrees of accuracy, I will look into how to best transfer the learning done in the supervised case and into casting the inference problem into reinforcement learning "language". To achieve this, I will learn about generative models as well as memory.