2006-2010  Xiamen University, BSc

2010-2016  Institute of Process Engineering, Chinese Academy of Sciences, PhD

2021-2022   The University of Sheffield, Assistant Professor

2020-2021   University College Cork Ireland, Eli Lilly Lecturer

2018-2020   The University of Cambridge, Research Associate

2016-2018   The University of Edinburgh, Marie Curie Postdoctoral Fellow

In 2023-2026, we would like to recruit several graduate students and postdoctoral researchers in the fields of chemical engineering, computer simulation, intelligent manufacturing, particle technology, and artificial intelligence. Please do not hesitate to contact us if you are interested in these fields!

Led/participated in multiple major Government, industrial, academic, and research projects in the European Union, the United Kingdom, and China, and conducted extensive and in-depth cooperation with multinational chemical companies (BASF, Johnson Matthey, Nestle, etc.), pharmaceutical giants (Pfizer, AstraZeneca, GSK, etc.), and software companies (IBM, Siemens, EDEM, etc.)

Presided over the Young Scientists Fund, General Program, and Outstanding Young Scientists Fund for Overseas Researchers of the National Natural Science Foundation of China (NSFC), a sub-project of the National Major Science and Technology Program, the "AI for Engineering" special project under the Artificial Intelligence Leapforward Program of the Shanghai Municipal Education Commission (SMEC), and "AI + Chemical Engineering" project under the Ministry of Education (MOE) Industry-University Cooperative Education Program.

Liu, C., Liu, T., Jiang, Y., Zhou, Y., Li, Y., *Hong, K., & *Chen, X. A Differentiable Deep Learning Approach for Inverse Optimization of Hopper Flows in Particulate Manufacturing. AIChE Journal, (2025), e18825.

Yaqub, M. W., &  *Chen, X. Vision transformers for three‐phase flow classifications with data augmentation through generative adversarial networks. AIChE Journal, (2025), e70002.

Yang, K., Liu, C., Hong, K., *Chen, X., & Luo, Z. An elastoplastic beam bond model for DEM simulation of deformable materials and breakage behaviors. AIChE Journal, (2025), 71(2), e18624.

Liu, T., Meng, Z., Du, W., Liu, C., & *Chen, X. Multi-objective differential optimization of fixed bed reactor geometries driven by graph convolutional neural network. Chemical Engineering Journal, (2025), 511, 161913.

Liu, T., Jiang, Y., Zhou, Y., Chen, S., Cao, L., *Chen, X., & Luo, Z. Enhanced Long-Time prediction of Gas-Solid flows via Integrating Reduced-Order model with Cluster-Based network model. Chemical Engineering Science, (2025), 121634.

Yaqub, M. W., & *Chen, X. Interpretable machine learning for three-phase flow pressure drop prediction: A Comparative Study with CFD and Empirical Models. Chemical Engineering Science, (2025), 310, 121542.

Liu, C., Liu, T., Yang, K., *Hong, K., & *Chen, X. Differentiable simulation and optimization of particle-fluid flows using graph neural networks. Powder Technology, (2025), 121143.

Lin, L., Yang, K., Zhang, X., Liu, C., Hong, K., & *Chen, X.. Experimental and Numerical Analysis of an Interactive Motion Drum for Enhanced Mixing and Segregation of Mixtures. Industrial & Engineering Chemistry Research, (2025), 64(14), 7516-7526.

Yang, K., Zhou, Y., Shen, C., *Chen, X., & *Cao, L. A mechanical-thermal-chemical coupling discrete element method model for simulating hotspot generation and ignition in HMX-based explosives. Particuology, (2025), 104, 68-87

Pan, M., Wang, Z., Mu, L., Liu, C., & *Chen, X. Comparison of Erosion Characteristics in Complex Pipeline Configurations Using CFD–DEM: A Study on Bends, Reducers, and Tee-Reducers. Industrial & Engineering Chemistry Research, (2025), 64, 4, 2465–2476. (共同一作为课题组毕设本科生)

Zhou, Y., Wang, H., Wu, B., Wang, L., & Chen, X. Physics informed neural network model for multi-particle interaction forces. Particuology, (2025), 96, 126-138

*Jiang, Y., Byrne, E., Glassey, J., & *Chen, X. Integrating Graph Neural Network-Based Surrogate Modeling with Inverse Design for Granular Flows. Industrial & Engineering Chemistry Research, (2024), 63 (20), 9225-9235.

Lin, L., Zhang, Y., Wang, L., & *Chen, X. A comprehensive review of characterization techniques for particle adhesion and powder flowability. International Journal of Pharmaceutics, (2024), 125029.

Gao, X., Yan, W. C., Chen, X., & Luo, Z. Multiscale Modeling and Artificial Intelligence for Multiphase Flow Science. Industrial & Engineering Chemistry Research, (2024), 63(22), 9609-9610.

Lin, L., Zhang, X., Yu, M., Mujtaba, I. M., & *Chen, X. Optimized structure design for binary particle mixing in rotating drums using a combined DEM and Gaussian process-based model. Digital Chemical Engineering, (2024), 12, 100175. (共同一作为课题组毕设本科生)

Lin, L., Yu, M., Liu, Y., *Chen, X., & Luo, Z. A comparative analysis of techniques for characterizing particle-scale adhesion and cohesion. Powder Technology, (2024), 447, 120203.

Dai, S., Meng, F., Wang, Q., & Chen, X. DP2-NILM: A distributed and privacy-preserving framework for non-intrusive load monitoring. Renewable and Sustainable Energy Reviews, (2024), 191, 114091.

*Jiang, Y., Byrne, E., Glassey, J., & *Chen, X.  Reduced-order modeling of solid-liquid mixing in a stirred tank using data-driven singular value decomposition. Chemical Engineering Research and Design,(2023), 196, 40-51.

X Chen, L Wang, F Meng and Z Luo, Physics-Informed Deep Learning for Modelling Particle Aggregation and Breakage Processes, Chemical Engineering Journal, (2022), 131220

Wang L G, Ge R, Chen X. Establishing an oblique impact breakage master curve using a DEM bonded contact model. Computers and Geotechnics, (2022)

Wang L G, Ge R, Chen X, et al. Multiscale digital twin for particle breakage in milling: From nanoindentation to population balance model. Powder Technology, (2021), 386: 247-261.

X Chen, James Elliott, On the scaling law of JKR contact model for coarse-grain cohesive particles, Chemical Engineering Science, (2020), 227, 115906

P Gajjar, I Styliari, T Nguyen; J Carr, X Chen, J Elliott, …, D Murnane, 3D Characterisation of Dry Powder Inhaler Formulations: Developing X-ray Micro Computed Tomography Approaches. European Journal of Pharmaceutics and Biopharmaceutics, (2020), 151, 32-44

X Chen, J Wang. Mesoscale-structure-based dynamic multiscale method for gas-solid flow. Chemical Engineering Science ( 2018), 192, 864-881

X Chen, J Wang. Dynamic Multiscale Method for Gas-Solid Flow via Spatiotemporal Coupling of Two-Fluid Model and Discrete Particle Model. AIChE Journal (2017), 63, 3681-3691.

X Chen, J Wang. A comparison of two-fluid model, dense discrete particle model and CFD-DEM method for modeling impinging gas–solid flows. Powder Technology (2014), 254, 94-102. 

X Chen, J Wang, J Li. Coarse grid simulation of heterogeneous gas–solid flow in a CFB riser with polydisperse particles. Chemical Engineering Journal (2013), 234, 173-183. 

X Chen, Z Luo, W Yan, Y Lu, I Ng. Three-dimensional CFD-PBM coupled model of the temperature fields in fluidized-bed polymerization reactors. AIChE Journal (2011), 57, 3351-3366.

Supervised 3 postdoctoral researchers (one of whom was awarded the title of Shanghai Super Postdoctoral Fellow), 3 doctoral students, and a number of master’s students;

Supervised students to win the Grand Prize of the Baidu PaddlePaddle AI Co-creation Program

The Technical Innovation Award of the GPU Hackathon co-hosted by Alibaba Cloud and NVIDIA

The First Prize of the 1st Guangdong-Hong Kong-Macao Greater Bay Area AI for Science Technology Competition

Innovation Pioneer Award and Merit Award of the First National Chemical Industry Artificial Intelligence Application Innovation Competition.

Zhiyuan Future Scholar Program Advisor

Guest Lecturer at the National University of Singapore

Member of the Editorial Board of Mathematical Problems in Engineering Journal, and Resources Chemicals and Materials Journal

Youth Editorial Board of Particology Journal, and Green Chemical Engineering Journal

Guest Editor of Processes Journal, and Int J. Chem Reactor Eng. Journal

Editors of journals such as Frontiers in Chemical Engineering, and Frontiers in Nanotechnology Research

National High-Level Talent Program (Excellent Youth)

Shanghai Overseas High-Level Talent Plan

Emerging Stars in Digital Chemical Engineering

Future Chemical Engineering (GCCES)

Exceptional Promise (The Royal Academy of Engineering)

Outstanding Mentor Award of the First National Chemical Engineering AI Competition

PhD students and postdoc positions are available, please get in touch with me at chenxizh@sjtu.edu.cn