时间：2018.08.14 (本周二)  14:00-16:00
地点：宝山校区东区机自大楼604会议室
题目：Surrogate modelling, data analytics and prior knowledge: some personal experiences
Abstract: In this talk, I will share our experiences in exploiting prior knowledge in process systems engineering. The talk will commence from discussion of a recent appraisal of deep learning in the AI community. Subsequently, several specific applications in process engineering will be discussed, including surrogate modelling for complex process simulations and data driven approach to fault isolation and diagnosis. Through these discussions I hope to make a case for a hybrid approach – that is the integration of potentially big data (but sometimes small data) with fundamental engineering knowledge which goes beyond correlation towards causation.
Bio: 陈韬，英国萨里大学化学与过程工程系高级讲师（北美体系副教授），Journal of the Franklin Institute（影响因子3.576）副主编。陈韬博士与2000，2002年分别于清华大学自动化系获得学士和硕士学位，2006年于英国纽卡斯尔大学获得博士学位，2006-2007年在英国纽卡斯尔大学从事博士后研究，2007-2010在新加坡南洋理工大学任职助理教授。他目前的研究包括：（1）基于模型的过程设计，状态/参数估计，优化与控制（2）过程故障检测与诊断（3）过程统计学及信号处理，过程测量校正（4）生物医学的应用方法。他现指导7名博士生；自2005年在国际主流刊物上发表70多篇论文，Web of Science引用1100多次，过去五年研究经费50万英镑，并多次作为顾问参与大型工业项目。
欢迎有兴趣的老师与同学参加！