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Dr. Tian obtained a B.Sc. and M.Sc. in Chemistry from Tsinghua University, and completed his Ph.D. in Chemical Engineering at ETH Zürich under the supervision of Prof. Chih-Jen Shih, focusing on multiscale simulation of engineering interfacial properties of two-dimensional materials. Between 2021 and 2023, he received the Swiss National Science Foundation (SNSF) Postdoc Mobility Fellowship to conduct postdoctoral research at Carnegie Mellon University with Prof. Zachary W. Ulissi, working on machine-learning-assisted material simulations. His work involves fine-tuning pretrained graph neural network models for computational catalysis and developing workflows that integrate machine learning with computational materials science. Prior to joining the University of Alberta, he briefly held a postdoctoral position at the Georgia Institute of Technology, working on software communication layers for machine-learning-enabled density functional theory packages. His research group focuses on developing machine learning–accelerated simulation methods to design interfacial materials, addressing challenges in vast configurational spaces that influence interfacial behavior. His contributions to open-source computational tools and machine-learning frameworks aim to enhance material property optimization and synthesis processes.
University of Alberta • Edmonton, AB, Canada
Conducts research and teaches courses in the Faculty of Engineering focusing on Chemical Materials Engineering.
Department: Mechanical Engineering and Engineering Management