刘海涛

个人信息Personal Information

副教授

博士生导师

硕士生导师

主要任职:Associate Professor

性别:男

毕业院校:大连理工大学

学位:博士

所在单位:能源与动力学院

学科:动力机械及工程. 流体机械及工程

办公地点:大连理工大学西部校区能源与动力学院619

联系方式:htliu@dlut.edu.cn

电子邮箱:htliu@dlut.edu.cn

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个人简介Personal Profile

大连理工大学能源与动力学院副教授、博士生导师,大连理工大学“星海青千”。2016年10月毕业于大连理工大学,获得博士学位及“辽宁省优秀博士学位论文”。2016年10月到2019年11月在新加坡南洋理工大学Rolls-Royce@NTU Corp Lab担任Research Fellow。合作者为南洋理工大学校长讲席教授、数据科学和人工智能中心负责人Ong Yew-Soon教授,澳大利亚莫纳什大学机器学习部门负责人Cai Jianfei教授,以及英国罗罗公司高级技术专家Wang Yi博士。2019年11月加入能源与动力学院叶轮机械及流体工程研究所,现为研究所副所长。

近年来的研究方向主要围绕机器学习特别是贝叶斯统计学习中的关键问题展开,服务于动力机械(如航空发动机等)的数字化、智能化设计分析。围绕大数据驱动的主动学习(试验设计)、贝叶斯统计模型(如高斯过程)、多任务协同学习、深度表征学习和基于机器学习模型的动力机械优化设计,在机械设计、航空和人工智能领域高水平期刊,如Journal of Mechanical Design (JMD), Structural and Multidisciplinary Optimization (SMO), AIAA Journal, Knowledge-Based Systems (KBS), IEEE Transactions on Neural Networks and Learning Systems (TNNLS),IEEE Transactions on Cybernetics (TCYB)等,发表了一系列有影响力的论文。相关研究成果在英国罗-罗公司航发智能设计系统、沈阳606所航发关键部件优化设计平台、国产CAP1400核主泵过流部件形性设计、大连机车厂某电力机车冷却风扇设计等得到应用。

个人学术链接[Researchgate]


Dr Liu received the Ph.D. degree from the School of Energy and Power Engineering, Dalian University of Technology, China, in 2016. From 2016 to 2019, he was a research fellow with Rolls-Royce@NTU Corp Lab at Nanyang Technological University, Singapore. He is currently an associate professor at Dalian University of Technology, China. His main research interests include Gaussian process, representation learning, multi-task learning, active learning and intelligent design of turbomachinery.


科研项目

1. 国家重点研发计划,超临界水热化学还原制氢装备的材料-结构-反应一体设计与制造,2020.12-2025.11,子课题负责人

2. 国家自然科学基金青年项目,面向大规模复杂数据的多任务高斯过程协同演化建模方法研究(52005074),2021.01-2023.12,负责人

3. 中央高校基本科研业务费,大数据驱动的高斯过程模型中关键技术研究及应用(DUT19RC(3)070),2020.01-2022.12,负责人


近年来代表性论著

2021:

Haitao Liu*, Yew-Soon Ong, Ziwei Yu, Jianfei Cai, Xiaobo Shen, Scalable Gaussian process classification with additive noise for non-Gaussian likelihoods, IEEE Transactions on Cybernetics, 2021, 1-13

Haitao Liu, Yew-Soon Ong, Xiaomo Jiang, Xiaofang Wang*, Modulating scalable Gaussian processes for expressive statistical learning, Pattern Recognition, 2021, 1-31

Haitao Liu, Yew-Soon Ong, Xiaomo Jiang, Xiaofang Wang*, Deep latent-variable kernel learning, IEEE Transactions on Cybernetics, 2020, 1-14

Haitao Liu, Changjun Liu, Xiaomo Jiang, Xudong Chen, Shuhua Yang, Xiaofang Wang*, Deep Probabilistic Time Series Forecasting using Augmented Recurrent Input for Dynamic Systems, arXiv:2106.05848, 2021, 1-25


2020:

Haitao Liu*, Yew-Soon Ong, Xiaobo Shen, Jianfei Cai, When Gaussian process meets big data: A review of scalable GPs, IEEE Transactions on Neural Networks and Learning Systems, 2020, 1-19.

Haitao Liu*, Yew-Soon Ong, Jianfei Cai, Large-scale heteroscedastic regression via Gaussian process, IEEE Transactions on Neural Networks and Learning Systems, 2020, 1-14.

Jianchi Xin, Xiaofang Wang, Haitao Liu, Wei Wang, Lushen Zhou, Numerical investigation of aerodynamic load on the impellers of centrifugal compressor with leakage flow, International Journal of Fluid Machinery and Systems, 2020, 13(2): 409-424.

Lusheng Zhou, Xiaofang Wang*, Haitao Liu, Jianchi Xin, Numerical Investigation of Operational Conditions Effects on the Annualr Seal Rotordynamic Characteristics of a 1400-Mw Canned Motor Reactor Coolant Pump, Solid State Technology, 2020, 63(3), 4915-4926

Chao Bian, Xiaofang Wang, Changjun Liu, Xinyu Xie, Haitao Liu*, Impact of exploration-exploitation trade-off on UCB-based Bayesian Optimization, Proceedings of the Fourth Chinese International Turbomachinery Conference (CITC), 30-Oct-2-Nov, 2020, NanChangChina

Changjun Liu, Haitao Liu, Chao Bian, Xudong Chen, Shuhua Yang, Xiaofang Wang*, Investigation of Time-series Prediction for Turbine Machinery Condition Monitoring, Proceedings of the Fourth Chinese International Turbomachinery Conference (CITC), 30-Oct-2-Nov, 2020, NanChangChina

吴锴,王晓放,边超,刘海涛*,面向变精度仿真数据建模分析的多任务学习方法比较研究,中国国际透平机械会议,2020,南昌


2019:

Haitao Liu*, Jianfei Cai, Yew-Soon Ong, Yi Wang, Understanding and comparing scalable Gaussian process regression for big data, Knowledge-Based Systems, 2019, 164:324-335.

Bingshui Da*, Yew-Soon Ong, Abhishek Gupta, Liang Feng, Haitao Liu, Fast Transfer Gaussian Process Regression with Large-Scale Sources, Knowledge-Based Systems, 2019, 165: 208-218


2018:

Haitao Liu*, Jianfei Cai, Yew-Soon Ong, Remarks on multi-output Gaussian process regression, Knowledge-Based Systems, 2018, 144:102-121.

Haitao Liu*, Yew-Soon Ong, Jianfei Cai, A survey of adaptive sampling for global metamodeling in support of simulation-based complex engineering design, Structural and Multidisciplinary Optimization, 2018, 57(1):393-416.

Haitao Liu*, Jaime-Rubio Hervas, Yew-Soon Ong, Jianfei Cai, Yi Wang, An adaptive RBF-HDMR modeling approach under limited computational budget, Structural and Multidisciplinary Optimization, 2018, 57(3):1233-1250.

Haitao Liu, Shengli Xu, Xiaofang Wang, Shuhua Yang, Jigang Meng, A multi-response adaptive sampling approach for global metamodeling, Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2018, 232(1):3-16.

Haitao Liu*, Jianfei Cai, Yi Wang. Yew-Soon Ong, Generalized robust Bayesian committee machine for large-scale Gaussian process regression, International Conference on Machine Learning (ICML), 2018.07, Stockholm, Sweden.

何曦,徐胜利,刘海涛,王晓放,陈旭东,基于谐响应分析的水环境下核主泵叶轮动应力研究,风机技术,2018,2,53-59


2017:

Haitao Liu*, Jianfei Cai, Yew-Soon Ong, An adaptive sampling approach for Kriging metamodeling by maximizing expected prediction error, Computers & Chemical Engineering, 2017, 106: 171-182.

Haitao Liu*, Yew-Soon Ong, Jianfei Cai, Yi Wang, Cope with diverse data structures in multi-fidelity modeling: A Gaussian process method, Engineering Applications of Artificial Intelligence, 2017, 67C:211-225.

Haitao Liu, Xiaofang Wang, Shengli Xu, Generalized radial basis function-based high-dimensional model representation handling existing random data, Journal of Mechanical Design, 2017, 139(1):011404.

Haitao Liu, Shengli Xu, Xudong Chen, Xiaofang Wang, Qingchao Ma, Constrained global optimization via a DIRECT-type constraint-handling technique and an adaptive metamodeling strategy, Structural and Multidisciplinary Optimization, 2017, 55(1):155-177.


2016:

Haitao Liu, Shengli Xu, Yi Ma, Xudong Chen, Xiaofang Wang, An adaptive Bayesian sequential sampling approach for global metamodeling, Journal of Mechanical Design, 2016,131(1), 011404.

Haitao Liu, Shengli Xu, Xiaofang Wang, Jigang Meng, Shuhua Yang, Optimal weighted pointwise ensemble of radial basis functions with different basis functions, AIAA Journal, 2016, 54(10):3117-3133.

Haitao Liu, Shengli Xu, Xiaofang Wang, Junnan Wu, Yang Song, A global optimization algorithm for simulation-based problems via the extended DIRECT scheme, Engineering Optimization, 2015, 47(11): 1441-1458.

Haitao Liu, Shengli Xu, Ying Ma, Xiaofang Wang, Global optimization of expensive black box functions using potential Lipschitz constants and response surfaces, Journal of Global optimization, 2015, 63(2): 229-251.

Haitao Liu, Shengli Xu, Xiaofang Wang, Sequential sampling designs based on space reduction, Engineering Optimization, 2015, 47(7): 867-884.

Jianchi Xin, Xiaofang Wang, Haitao Liu, Numerical investigation of variable inlet guide vanes with trailing-edge dual slots to decrease the aerodynamic load on centrifugal compressor impeller, Advances in Mechanical Engineering, 2016, 8(3): 1687814016640653.  

Haitao Liu, Shengli Xu, Xiaofang Wang. Sampling strategies and metamodeling techniques for engineering design: comparison and application. 2016.06, ASME Turbo Expo 2016: Turbine Technical Conference and Exposition, Seoul, South Korea.

Ying Ma, Shengli Xu, Haitao Liu, Xiaofang Wang. Optimization of reinforcing ribs of a hollow blade using metamodel-based optimization algorithm. ASME Turbo Expo 2016: Turbine Technical Conference and Exposition, 2016.06, Seoul, South Korea.

Jinzhi Huang, Shengli Xu, Haitao Liu, Xiaofang Wang. Robust performance optimization of centrifugal compressor volute with a rectangular cross-section. ASME Turbo Expo 2015: Turbine Technical Conference and Exposition, 2016.06, Montreal, Canada.



  • 教育经历Education Background
  • 工作经历Work Experience
  • 研究方向Research Focus
  • 社会兼职Social Affiliations
  • 基于深度学习的流场预测和分析

  • 主动学习(试验设计)
  • 动力机械优化设计
  • 贝叶斯统计学习