学术信息

Big Data Analysis and LLM: Towards Big Science

报告人简介

王子栋,现任英国伦敦Brunel University讲席教授,欧洲科学院院士,欧洲科学与艺术院院士,IEEE Fellow,International Journal of Systems Science主编,Neurocomputing主编。多年来从事控制理论、机器学习、生物信息学等方面研究,在SCI刊物上发表国际论文六百余篇。现任或曾任十二种国际刊物的主编、副编辑或编委。曾任旅英华人自动化及计算机协会主席、清华大学国家级专家。

报告摘要

The rise of Large Language Models (LLMs) and the explosion of big data are redefining how we discover knowledge. This talk explores the powerful convergence of big data analytics and LLM intelligence, highlighting how LLMs can act as scientific co-pilots to help with data processing, hypothesis generation, code automation, experimental documentation, and cross-disciplinary knowledge integration. By addressing limitations such as hallucination, energy cost, and domain adaptation, we look toward a future where human expertise and machine reasoning collaborate at scale. This synergy opens a new era of Big Science, enabling transparent, reproducible, and more creative discovery across scientific domains.


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