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scintillator-based radiation sensors combining multiple materials with complementary functions, offer a promising route to overcome these limits and achieve unprecedented timing resolution (sub-70ps), enabling
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opportunities for embedding storage at multiple points within the HVDC architecture—on the AC side, DC side, or directly within converter submodules. The research will tackle several key technical, economic, and
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physical laws, or an implicit form of extra data examples collected from physical simulations or their ML surrogates. In medical domains, patient data is typically distributed across multiple hospitals
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the MATSim agent-based transport simulation framework. The main task is to enable simulated agents to choose transportation modes, such as car, bus, bike, or walking, based on real-time feedback from
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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through theory and simulation and/or experimental design and testing; developing new image reconstruction algorithms for providing more information with less radiation; and applying our techniques
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and the effects of disordered correlated microstructures on diffusion; iii) development of energy-based models and numerical simulations of hyperuniform assemblies; iv) development and application
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biomedical engineering. We currently host several Ph.D. and postdoctoral fellows from Denmark and multiple nationalities. The group’s research interest spams from musculoskeletal simulations to design and
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portfolio across multiple sectors and disciplines, serve as a key member of the ACEP leadership team, contribute to strategy, operations, and collaboration across programs, lead research teams, build new
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environments—such as fleets with multiple aircraft types. Objectives Objective 1: Map current data types, structures, and interoperability challenges to build a detailed "as-is" understanding of current