Dr. Zongrui Pei holds a Ph.D. in materials science and engineering. He currently serves as a senior computational staff member at New York University. His current research focuses on developing physics-based methods and AI-for-science models, and utilizing these methods in conjunction with high-performance computing to investigate various materials. Dr. Pei’s areas of expertise include computational materials science, high-performance computing, classical/quantum machine learning, and mathematical physics.

• Introduction.- Material properties, Crystallography and Defects.- Quantum Mechanics and Machine Learning.- Fundamentals of High-performance Computing.- First-principles Methods and Atomistic Simulations.- Computational Thermodynamics and Statistical Mechanics.- Mechanics of Materials.- Applications to Materials.- Machine Learning for Materials Science.- More Topics in Condensed Matter Physics.- Selected Topics in Mathematics and Mathematical Physics.

Dr. Zongrui Pei holds a Ph.D. in materials science and engineering. He currently serves as a senior computational staff member at New York University. His current research focuses on developing physics-based methods and AI-for-science models, and utilizing these methods in conjunction with high-performance computing to investigate various materials. Dr. Pei’s areas of expertise include computational materials science, high-performance computing, classical/quantum machine learning, and mathematical physics.

• Introduction.- Material properties, Crystallography and Defects.- Quantum Mechanics and Machine Learning.- Fundamentals of High-performance Computing.- First-principles Methods and Atomistic Simulations.- Computational Thermodynamics and Statistical Mechanics.- Mechanics of Materials.- Applications to Materials.- Machine Learning for Materials Science.- More Topics in Condensed Matter Physics.- Selected Topics in Mathematics and Mathematical Physics.

Dr. Zongrui Pei holds a Ph.D. in materials science and engineering. He currently serves as a senior computational staff member at New York University. His current research focuses on developing physics-based methods and AI-for-science models, and utilizing these methods in conjunction with high-performance computing to investigate various materials. Dr. Pei’s areas of expertise include computational materials science, high-performance computing, classical/quantum machine learning, and mathematical physics.

• Introduction.- Material properties, Crystallography and Defects.- Quantum Mechanics and Machine Learning.- Fundamentals of High-performance Computing.- First-principles Methods and Atomistic Simulations.- Computational Thermodynamics and Statistical Mechanics.- Mechanics of Materials.- Applications to Materials.- Machine Learning for Materials Science.- More Topics in Condensed Matter Physics.- Selected Topics in Mathematics and Mathematical Physics.