YingXing Cheng

YingXing Cheng is a Researcher and Postdoc at the University of Stuttgart, affiliated with the Institute of Applied Analysis and Numerical Simulation and the department of Numerical Mathematics for High Performance Computing. Their work focuses on advancing computational methods in material science and quantum chemistry, including frequency-dependent polarizable force fields, Time-Dependent Density Functional Theory (TDDFT), and machine learning applications.

Research interests include molecular density decomposition, relativistic quantum effects, and high-throughput computational studies. They contribute to software engineering for scientific computing, particularly in developing frameworks like ACKS2ω and integrating machine learning for material property prediction.

Publications highlight advancements in polarizable force fields, vacancy formation energy analysis, and algorithmic approaches for defect prediction. Their work bridges theoretical chemistry, numerical analysis, and high-performance computing to address challenges in material design and characterization.

No scientific awards are listed, though their contributions to computational methodologies are notable. Cheng collaborates on projects involving molecular dynamics simulations and electronic structure analysis, contributing to both academic and applied research in computational materials science.