NYU-ECNU Center for Computational Chemistry at NYU Shanghai
Advances in modern computational methodologies and high-performance computing have vastly expanded the ability of computational chemists to model chemical, material, and biological systems; to predict their structures, functions, and various properties; and to design new molecular systems with desired properties.
The mission of the NYU-ECNU Center for Computational Chemistry at NYU Shanghai is to provide a platform for world-class research, for training students and young scientists, and for international collaboration in computational chemistry. The center has a core group of outstanding faculty members from New York University, East China Normal University, and NYU Shanghai who are conducting frontier research in various fields of computational chemistry, biology, and material sciences. The center carries out a variety of academic activities, including a seminar series featuring international and domestic speakers who are leading scientists in frontier research, symposiums and workshops, and a visiting scientist program.
The unique synergy of the center in international scientific exchange and collaboration, especially between American and Chinese scientists, provides a strong foundation for researchers to carry out truly challenging and innovative research at a premier international center for computational research in chemistry and related fields.
Shanghai Frontiers Science Center of Artificial Intelligence and Deep Learning
The newly founded Shanghai Frontiers Science Center of Artificial Intelligence and Deep Learning at NYU Shanghai focuses deeply on the field of artificial intelligence and deep learning, and fully explores the mathematical foundation behind artificial intelligence by intersecting with mathematics, physics, chemistry, and other disciplines. By bringing together researchers across various disciplines at NYU Shanghai, the center aims to develop the next generation of interpretable, adaptable, and "human-centered" artificial intelligence learning algorithms, and applies deep learning to fields such as biochemistry, neuroscience, and smart city engineering to achieve major breakthroughs.