My current initiative and curiosity centres on the interdisciplinary field of brain science, where I explore extensive research in computational neuroscience, biological data mining, machine learning, AI, and neuron-inspired robot design. This commitment to science is evident in my recent publication in Nature Neuroscience (2020). As the only theorist involved to this work, I contributed computational modelling work to explain other author’s experimental findings. Moreover, my publication on mutational and selection pressures on dinucleotides in genomics, my paper on protein synthesis rate with sequence information, and my published work on nonlinear waves, showcases my expertise in diverse data-related domains, mathematical modelling and computational skills. I have valuable teaching experience and successfully delivered various mathematical courses to both undergraduates and postgraduates, such as Probability and Statistics, Linear Algebra, Ordinary Differential Equations Qualitative Theory, Practical Large-scale Optimization, Mathematical Modelling in Ecology and so on. During the pandemic, I taught online for three years, offering a different yet enriching teaching experience. Specifically, I conducted the Data Mining course in English for undergraduates in the Sino-foreign Cooperative Education program, preparing them for academic pursuits in the US/UK. Emphasizing teamwork, I guided students in coding various data mining methods, leveraging my extensive research experience involving diverse programming languages such as Python/C/C++/Java/R. I got high score around 95/100 from online feedback systems each year for this course. I also have successfully supervised undergraduates and postgraduates in their dissertation/thesis projects, covering diverse topics from mathematical modelling to machine learning/data mining.