Qiang Zhao, PhD
Associate Professor | Doctoral Supervisor
School of Resources and Civil Engineering, Northeastern University, China
Email: zhaoqiang@mail.neu.edu.cn
Biography
Dr Qiang Zhao is an Associate Professor and Doctoral Supervisor in Mineral Processing Engineering at Northeastern University. He received his BEng and PhD degrees in Mineral Processing Engineering from Northeastern University and conducted joint doctoral research in Chemical Engineering at the University of Leeds, UK. Before joining the faculty as an Associate Professor, he worked as a postdoctoral researcher in Metallurgical Engineering at Northeastern University.
His research interests include coarse preconcentration of complex mineral resources, high-density dense medium separation, hydrocyclone classification, multiphase-flow modelling, and process intensification in mineral processing. His work combines theoretical analysis, laboratory experiments, numerical simulation, and process optimisation, with particular emphasis on the flow-field regulation, separation mechanism, and performance prediction of hydrocyclones and dense medium cyclones.
Dr Zhao has led and participated in a number of national, provincial, laboratory-level, and industry-funded research projects, including projects supported by the National Natural Science Foundation of China, the China Postdoctoral Science Foundation, national key R&D programmes, state key laboratories, and industrial partners. He has published more than 40 peer-reviewed papers, including over 16 SCI-indexed papers as first or corresponding author. His representative publications have appeared in Chemical Engineering Science, Powder Technology, Advanced Powder Technology, and Minerals Engineering.
ResearchInterests
Coarse preconcentration and waste rejection of complex mineral resources
Dense medium separation and high-density multiphase separation equipment
Hydrocyclone classification, modelling, design, and optimisation
CFD/DEM-based numerical simulation of mineral processing equipment
Multiphase-flow dynamics, slurry rheology, and process intensification
Digitalisation and intelligent control of mineral processing systems
Education and Professional Experience
2024–present
Associate Professor, Mineral Processing Engineering, Northeastern University, China
2022–2024
Postdoctoral Researcher, Metallurgical Engineering, Northeastern University, China
2019–2021
Visiting PhD Researcher, Chemical Engineering, University of Leeds, UK
2015–2022
PhD in Mineral Processing Engineering, Northeastern University, China
2011–2015
BEng in Mineral Processing Engineering, Northeastern University, China
Honours and Awards
Young Elite Scientists Sponsorship Program, China Association for Science and Technology
Excellent Young Scholar Program, Northeastern University, Category C
Selected Publications
Zhao Q., Cui B., Shen Y., et al. Understanding the characteristics and functions of axial velocity fluctuation zone in hydrocyclones: Part 1 — Flow pattern. Chemical Engineering Science, 2024, 283: 119368.
Zhao Q., Cui B., Shen Y., et al. Understanding the characteristics and functions of axial velocity fluctuation zone in hydrocyclones: Part 2 — Particle classification. Chemical Engineering Science, 2024, 284: 119444.
Zhao Q., Cui B., Ji A., et al. Experimental and numerical study of the effect of particle size distribution on hydrocyclone classification. Advanced Powder Technology, 2024, 35(4): 104398.
Zhao Q., Cui B., Wei D., et al. Linking separation sharpness with the characteristics of axial velocity wave zone in a hydrocyclone. Powder Technology, 2021, 386: 467–482.
Zhao Q., Liu W., Wei D., et al. Effect of copper ions on the flotation separation of chalcopyrite and molybdenite using sodium sulfide as a depressant. Minerals Engineering, 2018, 115: 44–52.
Student Recruitment
Dr Zhao welcomes applications from motivated PhD and MSc students with backgrounds in mineral processing, fluid mechanics, computational fluid dynamics, multiphase flow, artificial intelligence, or process equipment design. Students with experience in CFD, DEM, Python, machine learning, experimental fluid mechanics, or mineral separation processes are particularly encouraged to apply.