Zhou Qi


Assistant Professor

Phone: +86-15207196701

Email: qizhouhust@gmail.com &qizhou@hust.edu.cn

Academic Areas: Machine Learning; Structural Optimization; Additive Manufacturing



Academic Degrees

8/2016-9/2017 Visiting scholar Georgia Institute of Technology Mechanical Engineering

8/2014-1/2018 Doctoral of Science Huazhong University of Science and Technology Mechanical Engineering

8/2013-7/2014 Master of Science China Ship Development & Design Center Marine Engineering

8/2012-7/2013 Master of Science Huazhong University of Science and Technology Marine Engineering

9/2008-7/2012 Bachelor of Science Ocean University of China Marine Engineering



Selected Publications

A. Refereed Publications and Submitted Articles

B1. Published and Accepted Journal Articles

1. Zhou, Q., Wu, J., Xue, T., & Jin, P.* (2019). A two-stage adaptive multi-fidelity surrogate model-assisted multi-objective genetic algorithm for computationally expensive problems. Engineering with Computers, 1-17.

2. Shu, L., Jiang, P., Song, X., & Zhou, Q.* (2019). A novel approach for selecting low-fidelity scale factor in multi-fidelity metamodeling. AIAA J, 1-15.

3. Jiang, P., Cheng, J., Zhou, Q.*, Shu, L., & Hu, J. (2019) .Variable-fidelity lower confidence bounding approach for engineering optimization problems with expensive simulations. AIAA J, 1-16.

4. Hu, J., Jiang, P., Zhou, Q.*, Austin, M., & Choi, S., (2019). Model validation methods for multiple correlated responses via covariance-overlap based distance. Journal of Mechanical Design, 1-19.

5. Shu, L., Jiang, P., Zhou, Q.*, & Xie, T. (2019). An online variable-fidelity optimization approach for multi-objective design optimization. Structural and Multidisciplinary Optimization, 1-19.

B. Conference Presentation with Proceedings (Refereed)

1. Zhou, Q., Wang, Y., Choi, S., & Jiang, P.* (2017). An on-line multi-fidelity metamodel assisted multi-objective genetic algorithm. Proceedings of the ASME 2017 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, IDETC/CIE 2017, August 6-9, 2017, Cleveland, Ohio, USA.

2. Xie, T., Zhou, Q., Hu, J., Shu, L., & Jiang, P.* (2017). A Sequential Multi-objective Robust Optimization Approach under Interval Uncertainty Based on Support Vector Machines. 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM2017), December 10-13, 2017, Singapore.

C. Presentations

1. Zhou, Q., Jiang, P.*, Zhou, H., & Shu, L. (2015, December). An active learning variable-fidelity metamodeling approach for engineering design. In Industrial Engineering and Engineering Management (IEEM), 2015 IEEE International Conference on (pp. 411-415). IEEE.

2. Zhou, Q., Wang, Y., Choi, S., & Jiang, P.* (2017). An on-line multi-fidelity metamodel assisted multi-objective genetic algorithm. Proceedings of the ASME 2017 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, IDETC/CIE 2017, August 6-9, 2017, Cleveland, Ohio, USA.

Courses Taught

1. Experiment Design and Statistical Analysis

2. Structural design and optimization theory and approach

Project

Project of young science foundation of national natural science foundation of China: Research on robust design optimization method based on multi-input multi-output variable reliability approximation model

Project of young science foundation of national natural science foundation of China: Research on multidisciplinary robust design optimization method based on adaptive sampling and variable complexity approximation

National natural science foundation of China: Research on multi-objective robust design optimization method based on variable complexity approximation model uncertainty quantization

National 973 project: Basic research on Marine dynamic positioning equipment manufacturing with high service performance

National Science Foundation Project of America: Analytic Certification for Additively Manufacturing Parts and Processes under Uncertainty

National Natural Science Foundation Innovation Research Group Project: Basic research on high performance digital manufacturing equipment

Award

A. International or National Awards

Ø National defense innovation award

B. Institute or School Awards

Ø Outstanding young researcher from HUST