课程号：PY206007

课程名：人工智能及其应用

英文课程名：Artificial Intelligence and its Applications

开课单位：物理与光电工程学院

授课教师：Lin Gu

责任教师：周慧鑫   宋江鲁奇

学分/学时：1学分/16学时

教师简介：Lin Gu于2014年获澳大利亚澳大利亚国立大学博士学位，2014年至2016年在新加坡 A*STAR担任博士后研究员。2016年加入日本国立情报学研究所担任特任研究员并兼任京都大学客任研究员。2016年至今加入日本内阁府领导的ImPACT项目，致力于研发新一代光超声医学诊断设备，具体负责其中的图像分析以及病理临床研究工作。目前任理化学研究所研究员及东京大学客任研究员，为我校客座教授。

Lin Gu博士一直从事人工智能的基础研究以及在医学，无人驾驶等领域的具体应用，并提出全新的医学可解释性模型、半监督学习以及快速算法。于2017-2018年获得微软亚洲研究院CORE计划资助，进行医学图像的增强现实技术的研究。在无人驾驶方面，结合计算摄影学，他着力研发极低光照下的行人检测和场景分割算法。目前作为第一作者或者通信作者在人工智能顶级会议期刊发表CCF A类文章十余篇，并分别获 International Conference on Pattern Recognition (ICPR) 2012, International Conference on Digital Image Computing: Techniques and Applications (DICTA) 2013 最佳学生论文奖。

Lin Gu received the Ph.D. degree from the Australian National University, Australia, in 2014. He worked as a Post-Doctoral Researcher at A*STAR in Singapore from 2014 to 2016. In 2016, he joined the National Institute of Informatics as a special researcher and worked also as a guest researcher at Kyoto University, Japan. Since 2016, he has joined the ImPACT project led by the Cabinet Office of Japan. He is committed to developing a new generation of photo-ultrasonic medical diagnostic equipment, and is specifically responsible for image analysis and pathological clinical research. He is currently a research fellow at the Institute of Physical Chemistry and a visiting fellow at the University of Tokyo. He is a visiting professor in our college.

He has been engaged in artificial intelligence and specific applications in the fields of medicine, unmanned driving, etc., and has proposed new medical interpretable models, semi-supervised learning and fast algorithms. He was funded from the Microsoft Asia Research Institute CORE program in 2017-2018 to conduct research on augmented reality technologies for medical images. In terms of unmanned driving, combined with computational photography, he focused on developing pedestrian detection and scene segmentation algorithms under extremely low light. Currently, he has published more than 10 CCF A-type articles in the top artificial intelligence conference journals as the first author or correspondence author. In addition, he was awarded the Best Student Paper Award in International Conference on Pattern Recognition (ICPR) 2012, International Conference on Digital Image Computing: Techniques and Applications (DICTA) 2013.

课程简介：本课程将系统介绍人工智能算法其基础以及具体应用。本课程将从传统机器学习方法开始，系统介绍随机森林、SVM等方法，然后拓展到神经网络的理论基础以及具体的训练以及测试方法。在此基础上，将具体介绍所学习的算法在医学、工业以及遥感的最前沿研究方向以及具体应用。

This course systematically introduces the basics and specific applications of artificial intelligence algorithms. Starts with traditional machine learning methods, this course introduces random forest, SVM and other methods, and then expands to the theoretical basis of neural networks and specific training and testing methods. Based on these theories, the cutting-edge research direction and specific application of the learned algorithm in medicine, industry and remote sensing will be illuminated.

先修课程：无