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                and algorithms for event-based fusion of two physically-colocalized event-based and depth vision sensors, simulate and analyse these models, and explore possibilities to realize them in CMOS ASICs 
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                Disse), the Chair of Geoinformatics (Prof. Thomas H. Kolbe), and the Chair of Algorithmic Machine Learning & Explainable AI (Prof. Stefan Bauer). The project aims to develop an integrated urban flood 
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                funding, Profs. Himanshu Gupta and CR Ramakrishnan conduct research in the general area of quantum networks, quantum sensor networks, and distributed quantum computing. The center includes other quantum 
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                this PhD project, you will investigate the co-design between event-based learning algorithms and neuronal hardware units with multi-scale time constants. The algorithmic methodology will exploit recent 
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                electrical power, enabling smart sensors to operate without batteries. You will explore novel capacitor-based rectifier architectures, adaptive impedance-matching algorithms, and on-chip protection mechanisms 
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                ). The successful candidate will join the Integrated Intelligent Systems (I2S) Lab , led by Prof. Gianluca Setti, and contribute to the design, development, and deployment of cutting-edge AI- and IoT-based systems 
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                the security and cyber domain, with special focus on ethics and algorithmic transparency; Human-Technology Interaction: Developing robots, simulations, and games, which use a variety of AI technologies to learn 
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                communication Autonomous driving algorithms and technologies (e.g. vehicle control, path planning, scheduling) and sensors (e.g. lidars, radars, cameras, and GNSS) High-level integration of autonomous driving 
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                University's Department of Computer Science. Supported by significant funding, Profs. Himanshu Gupta and CR Ramakrishnan conduct research in the general area of quantum networks, quantum sensor networks, and 
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                -based prediction. This includes instrumenting a high-power APS torch with video and acoustic sensors, developing machine learning algorithms for feature extraction, and building predictive models