课题基金 / 基金详情

Industrial Challenge Project Advancing and Applying the Science of Behaviour Change through Machine-Live Learning

Industrial Challenge Project Advancing and Applying the Science of Behaviour Change through Machine-Live Learning
工业挑战项目通过机器实时学习推进和应用行为改变科学
批准号:
2166011
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2019
资助国家:
英国
项目状态:
已结题
起止时间:
2019 至 --

项目摘要

项目成果

相似基金

相关文献

中文摘要
翻译
该博士学位需要高级量化方法培训,以了解、交流并潜在地开发系统内的人工智能功能,以及进一步的统计方法培训,以便进行实验和模拟。2018/19年为学生提供的正规培训将包括在伦敦大学学院内运行的模块,这两门课程都将于2019年初运行,涵盖机器学习和统计方法培训要求。2018/19年将通过国家研究方法中心的课程进行进一步的培训,使用现有的培训预算,在预算允许的情况下,还将举办关于“R‘(https://www.ncrm.ac.uk/training/show.php?article=9167)的应用数据科学”和“Python简介”(https://www.ncrm.ac.uk/training/show.php?article=8792);的“实验设计和分析实验数据”课程。我还将申请伦敦2019年机器学习暑期学校的名额,该学校将由(https://sites.google.com/view/mlss-2019/home).领域的一系列国际专家提供一系列机器学习和人工智能主题的培训还将通过工作跟踪和会议与都柏林的IBM研究团队一起安排非正式培训,并将与艾伦·图灵研究所的UCL同事一起探索进一步的培训机会。在未来几年,为了在AQM的基础上建立更多的UCL模块,将进行更多的UCL模块,包括“情感计算和人机交互”、“概率模型中的近似推理和学习”以及“用于实用统计决策和风险的计算”。此外,还将提供进一步的NCRM和其他培训,以及非正式机会。除了上述AQM之外,其他形式的培训将包括参加会议(并可能介绍我的工作);目标会议将包括Cochrane Colloplomum和APA技术、思维和社会小组未来的会议。
英文摘要
This PhD requires advanced quantitative methods training to understand, communicate and potentially develop AI functionality within systems, as well as further statistical methods training in order to run experiments and simulations.Formal training for the studentship in 2018/19 will include modules run within UCL the 'Advanced Quantitative Methods' course (MSc Social Research Methods) and the 'Introduction to Deep Learning' (MSc Machine Learning), both running in early 2019, and covering both the Machine Learning and Statistical Methods Training Requirements. Further training in 2018/19 will be undertaken through National Centre for Research Methods courses, using the available training budget, on 'Applied Data Science with R' (https://www.ncrm.ac.uk/training/show.php?article=9167) and 'Introduction to Python' (https://www.ncrm.ac.uk/training/show.php?article=8792); a course on 'Design of experiments and analysing experimental data' will also be undertaken where budget allows (https://www.ncrm.ac.uk/training/show.php?article=8731). I will also apply for a place in the 2019 Machine Learning Summer School in London, which will provide training across a range of topics in machine learning and AI delivered by a range of international experts in the field (https://sites.google.com/view/mlss-2019/home). Informal training will also be arranged with the IBM Research Team in Dublin through work shadowing and meetings, and further training opportunities will be explored with UCL colleagues at the Alan Turing Institute.In future years, to build on this grounding in AQM, further UCL modules will be undertaken, including 'Affective Computing and Human-Robot Interaction', 'Approximate Inference and Learning in Probabilistic Models' and 'Computing for Practical Statistics Decision & Risk'. This will be supplemented by further NCRM and other training, as well as informal opportunities. In addition to the AQM described above, other forms of training will include attending conferences (and potentially presenting my work); target conferences will include the Cochrane Colloquium and future meetings of the APA Technology, Mind and Society group.
期刊论文(1)
专著(0)
科研奖励(0)
会议论文
Influences on User Trust in Healthcare Artificial Intelligence: A Systematic Review
医疗人工智能对用户信任的影响:系统评价
DOI: 10.12688/wellcomeopenres.17550.1
发表时间: 2022
期刊: Wellcome Open Research
影响因子: --
作者: [Jermutus E]
通讯作者: Jermutus E
海外基金