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efficient. We develop new optimization methods, machine learning algorithms, and prototypical systems controlling complex energy systems like electric grids and thermal systems for a sustainable future. These
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03.06.2021, Wissenschaftliches Personal The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and
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03.06.2021, Wissenschaftliches Personal The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and
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scientific work on design automation for quantum computers and develop methods and software tools dedicated to the design and realization of quantum algorithms/circuits. One of the main challenges in
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and adaptability. This research project aims to pioneer the next generation of recommender systems by moving beyond static methods. The core of this PhD is to develop a generative multimodal recommender
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to serious and costly accidents due to human error. Solutions to these problems, such as sustainable drives and autonomous navigation, are not yet fully developed and are still at the experimental stage
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. The project focuses on developing information theory, coding schemes, and other algorithmic methods for DNA data storage. Here is a video on the topic: https://www.bbc.com/future/article/20151122-this-is-how
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the possibility of an extension. TASKS: Mathematical modeling and development of inverse methods (e.g. Bayesian inversion, optimization based methods, sparsity promoting methods based on L1-norm minimization and
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develop methods and software tools that aid the design of microfluidic devices (also known as Labs-on-a-Chip). While these devices are mainly designed manually thus far, we investigate methods
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Smart Cities Applications at the soonest possible date. About us The Professorship of Data Science in Earth Observation (Prof. Xiaoxiang Zhu) develops modern signal processing and AI solutions to extract