题目:NeuroAI and its Applications in Model Compression
内容简介:Deep learning, represented by deep artificial neural networks, has been dominating numerous important research fields in the past decade. Although the invention of the neural network was to mimic a human's brain, the current development of deep learning is not primarily driven by the increasingly growing understanding to the brain. Brain is the most intelligent system we have ever known so far, although the brain remains vastly undiscovered, it is clear that the existing deep learning still goes far behind human brain in many important aspects such as efficiency, interpretability, memory, etc. Given the incredible capability of the human brain, we argue that neuroscience can always offer support for deep learning as a think tank and a validation means. In this talk, we discuss drawing the mechanism of genome bottleneck into deep learning, with an emphasis on solving problems in model compression, which is to facilitate the deployment of large models.
报告人:范凤磊
报告人简介:范凤磊博士是香港城市大学数据科学系的tenure-track助理教授,华为重点项目首席科学家。范凤磊博士于2017年在哈尔滨工业大学完成本科学习,并于2021年在美国伦斯勒理工学院获得博士学位,导师是国际知名医学影像学家王革教授。范凤磊博士在攻读博士学位期间获得了IBM AI Horizon Fellowship的支持,并受邀在MIT-IBM AI Watson实验室实习。随后,他在康奈尔大学和香港中文大学分别进行了为期一年和两年的博士后、研究助理教授研究。他的主要研究成果已在如JMLR、CVPR、IEEE TNNLS、IEEE TMI、IEEE TCI、IEEE TCSVT和IEEE TAI等人工智能和数据科学领域的旗舰期刊上发表,共计二十余篇。他的博士论文获得了国际神经网络学会(INNS)2021年杰出博士论文奖。他的一篇研究论文被选为2024年CVPR最佳论文奖候选作品之一(超过1万份提交中26篇),一篇论文获得IEEE TRPMS最佳论文奖,一篇论文获得ESI高被引论文。范凤磊博士还多次在顶级会议如AAAI2023,WWW2025,IJCNN2025组织教学教程,受到了广泛关注。范凤磊博士荣获多项项目资助,所领导的校企合作成果成功落地产品线中。
时 间:2025年5月27(周二)下午15:30开始
地 点:石牌校区南海楼124会议室
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信息科学技术学院
2025年5月21日