曹广福教授：

Utilizing the symbols of composition operators to construct a linearly independent function sequence, which bypasses the use of boundary behavior of reproducing kernels as those may not be applicable in our general setting.

姚正安教授：

We consider the Cauchy problem of the d‐dimensional (d=2 or 3) magneto‐micropolar equations with general fractional dissipation. We focus on the existence and uniqueness of solutions in the weakest possible inhomogeneous Besov spaces. Using the technical tools of Litttlewood–Paley decomposition and Besov spaces theory, we obtain the local existence in the functional setting of inhomogeneous Besov spaces. Furthermore, such solutions are unique only in 2D case.

刘继军教授：

一类非常重要的应用问题是不适定问题的数学建模。导致不适定问题数学模型的原因可能有三条： 输入数据不足、输入数据彼此矛盾以及问题本身就是一个不稳定的系统。不适定问题模型的数学困难有三条：解不唯一、解不存在以及解不稳定。

王泽文教授：

Combined with the mollification method, the proposed finite difference inversion method can obtain more stab- le reconstructions from the nonlocal data with noise.

刘鹏程副教授：

Sampling-based motion planning algorithms are prevailing and well-established methods. More effective algorithms such as optimization-based, Probabilistic Movement Primitives (ProMPs)-based and physics-based methods are feasible research directions to explore to improve the effectiveness. The evaluation benchmarking of the algorithm is a worthy research direction. The model-based methods can improve the efficiency of the task, but it has less ability to deal with accidents. In contrast, the model-freed methods can solve this problem, but it takes a long time to compute.