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Speaker：Qaing Du
Time： Mon 16:30-17:30，2019-9-23
Venue：Lecture Hall, Jin Chun Yuan West Bldg.
Nonlocality has become increasingly noticeable in nature. The interests in the effective modeling and the numerical simulation of its presence bring on new challenges to mathematicians. In this talk, we will discuss nonlocal models with a finite horizon of interactions and theirs roles in various applications. We will also reveal some practical risks due to inappropriately developed nonlocal models and numerical discretizations. We will show how systematic mathematical analysis can help making nonlocal modeling and simulations more effective and robust for problems in solid and fluid mechanics, autonomous vehicle traffic flows, and deep learning.
Dr. Du earned Ph.D. in Mathematics (1988) from Carnegie Mellon University. At present he is the Fu Foundation Professor of Applied Mathematics at Columbia. He chairs the Applied Mathematics Program Committee in the Department of Applied Physics and Applied Mathematics (APAM), Fu Foundation School of Engineering and Applied Science (SEAS).
In 2013, he was selected as a SIAM Fellow for contributions to applied and computational mathematics with applications in materials science, computational geometry, and biology. In 2017, he was selected as an AAAS Fellow for his distinguished contributions to the field of applied and computational mathematics, particularly for theoretical analysis and numerical simulations of mathematical models in various applications. Recognitions for Dr. Du’s work include Feng Kang prize in scientific computing (2005), Eberly College of Science Medal (2007), SIAM Outstanding Paper prize (2016), ACM Gordon Bell Prize finalist (2016). He was also an invited speaker at the International Congress of Mathematicians (2018). He was elected into the One hundred Outstanding Young Chinese Scientists, Chinese Academy of Sciences and the chief expert of the “Large-scale scientific computing research” program of Ministry of Science and Technology of China.
Dr. Du's research interests are in numerical analysis, mathematical modeling and scientific computation with selected applications in physical, biological, materials, data and information sciences.
