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for environmental pollution sciences. It focuses on robustness to distribution shifts, degraded inputs, and out-of-distribution conditions, while also addressing uncertainty quantification, explainability, fairness
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. Still, many challenges are ahead. Expanding their impact in real-world deployments requires addressing the heterogeneity of hardware, data, and resource availability in distributed scenarios
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nanocrystals, hybrid perovskites and 2D materials. Development of new data-driven approaches for studies of optoelectronic properties using EM, including machine learning / machine vision algorithms. The balance
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, and concentration-effect patterns. By comparing healthy PBMCs with PBMCs exposed to inflammatory stimuli, the project will clarify how inflammation alters MN distribution and function, ultimately