报告题目：人工智能在医学与生物工程中的应用

演讲摘要：Artificial Intelligence (AI) is the science of mimicking human intelligences and behaviors. Machine Learning (ML), a subset of AI, trains a machine how to use algorithms or statistics to find hidden insights and learn automatically from data. Deep learning (DL) is one of machine learning methods where we use deep neural networks with advanced algorithms such as auto-encoding or convolution to recognize patterns in data. AI has become very successful recently due to the availability of huge data and powerful supercomputers. Many applications such as speech and face recognition, image classification, natural language processing,bioinformatics, health informatics such as disease prediction and detection suddenly took great leaps due to the advance of AI.Although various AI architectures and novel algorithms have been invented for many bio and health applications,better explainability,increasing prediction accuracy and speeding up the training process are still challenging tasks among others. In this talk, I will outline recent developments in AI research for bioinformatics and health informatics. The topics discussed include proposing more effective architectures, intelligently freezing layers, gradient amplification, effectively handling high dimensional data, designing encoding schemes, mathematical proofs, optimization of hyper-parameters, effective use of prior knowledge, embedding logic and reasoning during training, result explanation and hardware support. These challenges create a huge number of opportunities for people in both computer science and health care. In this talk, some of our solutions and preliminary results in these areas will be presentedand future research directions will also be identified.

讲者简介：清华大学计算机系1977级系友，以江苏省理科状元的成绩进入清华大学计算机系学习，后在计算机系攻读硕士，1991年获得美国匹兹堡大学计算机科学博士学位。他长期从事计算机与生物信息领域的交叉研究，已发表SCI期刊论文250余篇。曾任乔治亚州立大学计算机系主任、生物系主任、副院长、终身教授、杰出教授、州校董教授，2021年当选美国医学与生物工程院院士。2021年初，潘毅回归祖国，正式全职担任中科院深圳理工大学计算机科学与控制工程学院院长，拥有国际化视野和丰富管理经验的他，致力于引领学院更好发展，也为国内引进和培养更多优秀的青年人才。