
图像是信息呈现的主要形态,是电子商务和电子政务信息的重要载体。当今社会在信息化和数字化领域已经趋于成熟,网络技术和多媒体技术的迅速发展,使得用户可频繁地利用网络传输和获取大量的多媒体信息。对数字图像进行复制、编辑、篡改己经不是难事。在信息传输过程中,如何保证图像的完整性、内容的真实性己经成为了一个亟待解决的问题,比如侵犯版权、非法篡改、机密泄露等。通过本项目对图像认证和语义篡改检测的训练,学生将了解图像信息和图像数据,图像的分类和编码等,掌握图像的语义表达,特征抽取和内容保护方法等。
武汉大学 计算机学院 教授
英国伦敦大学 博士
爱尔兰DCU大学 外聘博士生导师
研究方向:
计算机科学、图像和视频处理、软件工程、信息安全、人工智能等
讲授课程:
《随机信号分析》、《计算机网络》、《多媒体技术应用》、《数字图像处理》、《数字逻辑电路》、《C++程序设计》、《信息安全》、《信息系统导论》、《数据库系统》、《Linux操作系统》、《数字信号处理》、《信号与系统》、《通信原理》等
曾先后在名校从事教学和科研,以及华为从事科技开发近30年,先后主持完成科研项目20多项,开发高科技产品10多项。近10年发表包括在IEEE TIP内的国际学术期刊和会议论文60多篇,科技专著1本(Science Press),授权发明专利8项。担任国际学术大会主席20+次,作大会报告30+次。曾担任2个国际学术期刊主编。
L1:无任何学科经验的高中生
L2:对学科基础知识有了解的高中生;跨专业大学生
L3:对行业有相当研究,优秀的高中生;本专业大学生
L4:优秀的大学生;研究生
工程
生命科学专题:癌症发生相关蛋白质研究与抗癌药物研制【大学组】
吴老师 上海交通大学生命科学技术学院 教授 博导 Memorial Sloan Kettering癌症中心/Howard Hughes医学研究所 博士后 哈佛大学医学院 博士后 普林斯顿大学 化学系 博士 上海生物物理学会理事 科技部国家重点研发计划合成生物学重点专项课题组长 研究方向: 物理化学合成生物学、冷冻电镜结构生物学 独立建立了上海交通大学第一个结构生物学实验室。在Science、Nature(2篇)、Molecular Cell(3篇)、PNAS、Nature Microbiology、Nature Communications(4篇)、Nature Chemical Biology、Cell Research(2篇)、Nucleic Acids Research(3篇)、Cell Discovery(3篇)、mBio(3篇)、Journal of Molecular Biology、Journal of Molecular Cell Biology、Molecular Microbiology(4篇)等发表论文,被引用2600余次。发表的APC-Asef复合物结构论文被英国皇家学会院士Mariann Bienz选入生物医药类论文权威数据库Faculty of 1000(Faculty Opinions数据库的前身),并在此基础上与同事合作开发抑制结肠癌细胞迁移的化合物(Nature Chemical Biology, 2017)。发表的TSCC复合物冷冻电镜结构论文被权威数据库Faculty Opinions录入。发表的Smac-XIAP复合物晶体结构被Novartis、Genentech等公司作为开发抗癌药物的基础。

人工智能
计算机网络与信息安全专题:机器学习在优化域名解析与分配、丢包及垃圾邮件等网络异常检测中的应用
Nick 导师现任芝加哥大学计算机科学讲席终身正教授,同时担任芝加哥大学数据与计算中心主任与网络运营与安全实验室主任,曾在普林斯顿大学担任计算机科学终身教授、信息技术政策中心副主任,也曾在佐治亚理工学院担任计算机学院教授。他的研究侧重于网络安全和性能。Nick 导师拥有麻省理工学院计算机科学博士学位、电气工程和计算机科学的硕士和学士学位。 Nick 导师是美国计算机协会院士(ACM Fellow),该协会为计算机科学领域大约1%的顶尖专业人士保留。 导师曾荣获NSF “美国青年科学家与工程师总统奖”(PECASE,美国青年科学家和工程师的最高荣誉)和“IBM优秀教师奖“,被《麻省理工学院技术评论》评为35岁以下最佳创新者之一。 Dr.Nick is Neubauer Professor of Computer Science and Director of the Center for Data and Computing at the University of Chicago. He also directs the Network Operations and Internet Security research lab, where we develop data-driven tools and systems to improve Internet security, performance, and adoption. He designs and deploys network protocols and systems that make the Internet work better. Prof.Nick uses empirical network measurement and machine learning to understand and improve network performance, security, and privacy. The results of his research often have policy implications. I regularly work with federal and municipal organizations, including the Federal Communications Commission (FCC) and the City of Chicago on equitable Internet access, security, and privacy.
项目内容包括无监督学习和监督学习等机器学习入门概念,以及如何将以上概念应用于网络的实践活动。学生将完成导师布置的课堂作业,以及将机器学习应用于网络的项目,在项目结束时,提交项目报告,进行成果展示。 This course will provide students with a background in machine learning concepts, as well as how they apply to concepts in computer networking, ranging from network performance to network security. The course will include a primer in a range of machine learning concepts in both unsupervised and supervised learning, as well as hands-on activities that apply these machine learning concepts to network applications and data. Students will complete several hands-on lab assignments as well as a course project that involves the application of machine learning to networking. 个性化研究课题参考 Suggested Research Field: 利用机器学习算法进行网络安全风险预测中的收敛性控制 Machine learning-based convergence control of network security risk prediction Android恶意软件检测方法性能比较 Review of performance comparison of Android malware detection methods 基于朴素贝叶斯分类器的恶意网站自动分类 An automatic classifier of Malicious Websites based on Naive Bayes

工程
工程项目管理专题:建筑工程项目安全风险控制和管理决策分析【大学组】
Paolo导师现任伊利诺伊大学香槟分校(UIUC)土木与环境工程学院讲席终身正教授、杰出研究学者;社会风险和危害缓解项目联合主任,工程风险研究&控制中心主任、美国三大建筑工程研究中心MAE中心主任;美国土木工程学会(ASCE)的工程力学学会(EMI)、国际土木工程风险与可靠性协会(CERRA)的成员;国际期刊《可靠性工程与系统安全》的主编,国际期刊《可持续与弹性基础设施》的创始人。Professor Paolo is a tenured full professor and distinguished research scholar in the School of Civil and Environmental Engineering at the University of Illinois at Urbana-Champaign. Co-director of the Social Risk and Hazard Mitigation Program, Director of the Center for Engineering Risk Research & Control, and Director of the MAE Center, one of the three major architectural engineering research centers in the United States; Member of the Engineering Mechanics Society (EMI) of the American Society for Civil Engineering (ASCE) and the International Society for Risk and Reliability in Civil Engineering (CERRA); Editor in chief of the international journal Reliability Engineering and Systems Safety and founder of the international journal Sustainable and Resilient Infrastructure.
Paolo导师科研生涯成果颇丰:曾获得美国土木工程师学会颁发的“土木基础设施风险分析和管理Alfredo Ang奖”,共发表200多篇参考期刊论文、并发表了超过60次全体会议和主题演讲。Paolo has achieved a lot in his scientific research career: he was awarded the Alfredo Ang Award for Risk Analysis and Management of Civil Infrastructure by the American Society of Civil Engineers, published more than 200 refereed journal papers, and delivered more than 60 plenary meetings and keynote speeches.
Paolo导师还曾担任英国拉夫堡大学、武汉江汉大学任职教授。目前他的研究领域为建筑可靠性、建筑工程风险和建筑生命周期分析、智能建造与土木建筑机器学习工程不确定因素、多危害分析建筑风险评估等。Paolo has also served as a professor in Loughborough University and Wuhan Jianghan University. His current research interests include building reliability, building engineering risk and building life cycle analysis, intelligent construction and civil construction machine learning engineering uncertainties, multi-hazard analysis and building risk assessment.
本项目关于建筑工程与人工智能的交叉领域,我们将从高层建筑的结构系统入手,探究高层结构的安全与设计原理,并着重分析房屋结构的设计流程、设计时应考虑的安全因素、环保的设计理念。随后,导师将带领学生一起分析建筑中的结构系统和荷载问题,最后,导师将带领我们探究人工智能在建筑安全风险方面的应用,如何将安全、环保的理念融入房屋设计。通过本项目的学习,学生将进一步了解和掌握大楼结构的设计原理,并实现对现实生活中房屋建筑的设计分析,在项目结束时提交报告,进行成果展示。个性化研究课题参考:智能建造在土木工程施工中的应用综述、机器学习LGBM回归算法预测混凝土强度、机器学习的结构缺陷检测研究
This project is about the intersection of architectural engineering and artificial intelligence, we will start from the structural system of high-rise buildings, explore the safety and design principles of high-rise structures, and focus on the analysis of the design process of housing structure, the design should consider safety factors, environmental protection design concept. Then, the tutor will lead the students to analyze the structural system and load problems in the building. Finally, the tutor will lead us to explore the application of artificial intelligence in the building safety risk and how to integrate the concept of safety and environmental protection into the house design. Through the study of this project, students will further understand and master the design principle of building structure, and realize the design analysis of real life housing construction. At the end of the project, the report will be submitted and the results will be displayed. Personalized research topic reference: Overview of the application of intelligent construction in civil engineering construction, prediction of concrete strength by LGBM regression algorithm based on machine learning, structural defect detection based on machine learning