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。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，围绕大型能源装备（如屏蔽电机核主泵、大型离心压缩机、燃机、大型制氢反应器、大功率风机、工业锅炉等）数字化设计、孪生建模和健康管理，发表高水平论文40+，其中ESI高被引论文2篇，影响因子>14的论文7篇，Google学术引用2000+，申请/授权发明专利6项。获得辽宁省优秀博士学位论文，2022年大连市技术发明一等奖，全国能源动力类专业百篇优秀毕业论文指导教师，“首届全国博士后创新创业大赛”优胜奖。目前担任SCI期刊IEEE Transactions on Emerging Topics in Computational Intelligence（IF：5.3）副主编（Associate Editor）。

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. He is now an associate editor of IEEE Transactions on Emerging Topics in Computational Intelligence.

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. 国家自然科学基金面上项目，受约束高维数据驱动的多任务高斯过程智能建模方法研究及应用（52375231），2024.01-2027.12，负责人

3. 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

4. 辽宁省自然科学基金面上项目，面向动力装备大数据分析的深度高斯过程模型研究，负责人

5. 辽宁重大装备制造协同创新中心重点项目，石化行业大型离心压缩机智慧运维数字孪生建模理论与应用研究，子课题负责人

6. 大连市顶尖及领军人才项目，大兆瓦海上风机基于数字孪生的智能运维平台（2022RG10），2023.01-2025.12，参与

7. 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

2023：

Hao, Y., Xie, X., Zhao, P., Wang, X., Ding, J., Xie, R., & Liu, H.* (2023). Forecasting three-dimensional unsteady multi-phase flow fields in the coal-supercritical water fluidized bed reactor via graph neural networks. Energy, 128880.

Xie, X., Wang, X., Zhao, P., Hao, Y., Xie, R., & Liu, H.* (2023). Learning time-aware multi-phase flow fields in coal-supercritical water fluidized bed reactor with deep learning. Energy, 263, 125907.

Liu, H., Wu, K., Ong, Y. S., Bian, C., Jiang, X., & Wang, X. (2023). Learning Multitask Gaussian Process Over Heterogeneous Input Domains. IEEE Transactions on Systems, Man, and Cybernetics: Systems. Online.

Zhao, P., Liu, H.*, Xie, X., Wang, S., Liu, J., Wang, X., ... & Zuo, S. (2023). Efficient Surrogate-Assisted Parameter Analysis for Coal-Supercritical Water Fluidized Bed Reactor with Adaptive Sampling. Machines, 11(2), 295.

2022:

Haitao Liu, Changjun Liu, Xiaomo Jiang, Xudong Chen, Shuhua Yang, Xiaofang Wang*, (2022). Deep probabilistic time series forecasting using augmented recurrent input for dynamic systems. Mechanical Systems and Signal Processing, 177, 109212.

Haitao Liu, Jiaqi Ding, Xinyu Xie, Xiaomo Jiang, Yusong Zhao, Xiaofang Wang*, Scalable multi-task Gaussian processes with neural embedding of coregionalization[J]. Knowledge-Based Systems, 2022, 247: 108775.

Zhendong Guo, Haitao Liu, Yew-Soon Ong, Xinhua Qu. Generative Multiform Bayesian Optimization. IEEE Transactions on Cybernetics, 2022.

Zhendong Guo, Yew-Soon Ong, Tiantian He, Haitao Liu. Co-Learning Bayesian Optimization. IEEE Transactions on Cybernetics, 2022.

Xin, J., Liu, X., Malik, A., Liu, H., Zhao, L., & Kong, X. (2022). Investigation of the Flow Field and Aerodynamic Load on Impellers under Guide Vanes with a Self-Induced Slot in Compressor Radial Inlet. Applied Sciences, 12(10), 5179.

Lusheng Zhou, Xiaofang Wang, Haitao Liu*, Jianchi Xin, The Effect of Inflow Distortion on the Rotordynamic Characteristics of a 1400-MW Reactor Coolant Pump Annular Seal, Machines, 2022, 10(1): 65.

Chen, X., Ding, X., Wang, X., Zhao, Y., Liu, C., Liu, H.*, & Chen, K. (2022). Multi-Task Data Imputation for Time-Series Forecasting in Turbomachinery Health Prognostics. Machines, 11(1), 18.

Bian, C., Wang, X., Shao, W., Xin, J., Hu, R., Lu, Y., & Liu, H. (2022). Adaptive confidence bound based Bayesian optimization via potentially optimal Lipschitz conditions. Engineering Optimization, 1-19.

 

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, 120: 108121

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

Zhendong Guo, Haitao Liu, Yew-Soon Ong, Calibrated and recalibrated expected improvements for Bayesian optimization, Structural and Multidisciplinary Optimization, 2021, 64 (6), 3549-3567

Zhenkun Wang, Qingfu Zhang, Yew-Soon Ong, Shunyu Yang, Haitao Liu, Jianping Luo, Choose Appropriate Subproblems for Collaborative Modeling in Expensive Multiobjective Optimization, IEEE Transactions on Cybernetics, 2021, 1-14

Chao Bian, Shaojie Zhang, Jinguang Yang, Haitao Liu, Feng Zhao, Xiaofang Wang*, Bayesian Optimization Design of Inlet Volute for Supercritical Carbon Dioxide Radial-Flow Turbine, Machines, 2021, 9(10): 218

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, NanChang, China

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, NanChang, China

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.