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This research aims to design a sustainable framework for optimizing distributed computing systems to enhance performance while minimizing energy consumption. Existing scheduling algorithms often
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of Machine Learning as the problem of approximating function f from the pair of measurements (x,y), and Optimization as the problem of finding the value of input x that maximizes the output y given
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In EdgeVLMOpt (EVO): Optimizing Vision-Language Models for Resource-Constrained Edge Devices, we aim to develop efficient and scalable techniques to enable the deployment of advanced vision-language
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available full-scale option for PFAS. While shown to be capable of complete PFAS breakdown, further research into thermal treatment is required to optimize process efficiency and ensure safe treatment without
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This research focuses on developing and evaluating methodologies for the optimal design of control charts within the framework of Statistical Process Control (SPC). The study aims to determine the
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In NeuroDistSys (NDS): Optimized Distributed Training and Inference on Large-Scale Distributed Systems, we aim to design and implement cutting-edge techniques to optimize the training and inference
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Adobe Experience Manager (AEM) and Adobe Journey Optimizer (AJO). Working across Digital Experience, Sales, Analytics, Marketing and IT, you will use customer insights, behavioural data and journey
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and deeply engaged with staff and students, supporting wellbeing and belonging while creating the conditions for bold ideas, strong performance and shared success. They will bring energy, optimism and
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., Boruta) and statistical imputation methods (e.g., KNN/Iterative Imputer) are applied to optimize variable efficiency and handle missing data. Ensemble algorithms—specifically Gradient Boosting, LightGBM
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registers, agendas, minutes and board paper preparation with timely follow-up. Lead benefits realisation and lessons learned reviews to optimize ongoing program delivery and operational effectiveness. Provide