Qijun Hong

Qijun Hong is an Assistant Professor of Materials Science and Engineering at Arizona State University's School for Engineering of Matter, Transport and Energy. He holds a PhD in Physical Chemistry from Caltech (2014) and BS in Chemistry from Fudan University, China (2009). Prior to joining ASU, he completed postdoctoral research at Brown University (2014-2020) and worked as a Machine Learning Scientist at Amazon.com (2020-2021).

Education:

• PhD, Physical Chemistry, California Institute of Technology, 2014
• BS, Chemistry, Fudan University, China, 2009

His research integrates materials science, machine learning, and density functional theory to predict material properties. Key focus areas include melting temperature prediction, heat capacity calculations, thermal expansion, and enthalpy via first-principles molecular dynamics. His group developed SLUSCHI software for melting point calculations and the MAPP framework used globally for materials property prediction. Notably, his prediction of the world's highest melting temperature material (confirmed experimentally) received widespread media coverage including Washington Post and Science.

Analysis of his recent publications reveals a strong trend toward machine learning applications in materials discovery, particularly graph neural networks for predicting thermodynamic properties. His work bridges computational modeling with experimental validation, focusing on refractory materials and high-entropy alloys.

Scientific Recognition:

• NSF, DoD, and DOE-funded research projects
• SLUSCHI software with 3,000+ downloads
• MAPP framework with 7,000+ web uses and 300,000+ API calls
• CDC-featured COVID-19 forecasting model
• Extensive media coverage for materials breakthroughs

As a dedicated educator, Hong teaches graduate courses including MSE 457 (Quantum Mechanics), MSE 511 (Math and Computational Methods), and specialized topics in materials science. His research group actively recruits graduate students for projects at the intersection of AI and materials science. He leads multiple federally funded projects including Rare Earth Materials Under Extreme Conditions (NSF) and Emergent Refractory Behaviors (DoD).