Welcome!

I'm Li Yihai, currently pursuing a Postgraduate Degree in High Performance Computing at Trinity College Dublin.

The teaching assistant of modules MAU11E01-Engineering Mathematics-202324, MAU22C00-Discrete Mathematics-202324, MAU11S01-Mathematics for Scientists-202324. Previously, I earned a Bachelor's Degree in Mathematics and Applied Mathematics from the Mathematics Institute at ShanXi University in 2020, graduating with a GPA of 86.07/100. I have engaged in research work in PA ST 806: Deep Learning with Professor Pavlos Protopapas's team for three months in 2021.

At present, I am dedicating myself to various research fields, including further honing my mathematical skills and coding proficiency in projects related to artificial intelligence. As I continuously strive to improve as a learner, I am also endeavoring to become a better teacher, believing that teaching and communicating are fundamental to the process of self-improvement.

Research

Data Science and Artificial Intelligence: Deep Learning—Upper Intermediate, Harvard University Jan. 2021-Mar. 2021

  • Familiarized with machine learning modules, such as Tensorflow 2.0+.
  • Acquired algorithms of machine learning specifically in Convolutional Neural Networks
  • Understood several methods of evaluation model like Bootstrap algorithm and knew how to build Proxy model to evaluate the model
  • Learned methods of Grad-CAM Map, Saliency Map to check the internal learning process of neural networks

Rank of Matrix, Final Project of CS50: Introduction to Computer Science, Harvard University Dec. 2020

  • Made a comparison of C and Python, and decided to use C to achieve the rank function of arbitrary elements’ non-0 matrix
  • Added a value that can transform the matrix to an upper triangle or lower triangle format so as to test whether the input data meets the requirement
  • Calculated the determinant value of required matrix

Mathematical Modeling, Online Project, Temperate University Oct. 2018-Nov. 2018

  • Took courses of Dimensional Analysis and Data Mining; acquainted with the application of Dimensionalanalyysikone to deal with actual problems
  • Understood how to use LISp_Miner to solve problems about data mining

Diagnosability of One-way K-ary N-cube under PMC Model. Leader of a Five-member team Nov. 2017-Nov. 2018

  • Participated in the topic meeting each week and discussed research contents with graduates
  • Studied and arranged the theorem used in the research; utilized it to derive the result of diagnosability under PMC model
  • Confirmed the 1-good-neighbor connectivity, diagnosability, and 1-good-neighbor diagnosability of directional k-ary n-cube and nondirectional k-ary n-cube

Technology of Big Data, Hot Words Statistics, Oracle Nov. 2018

  • Learned how to build virtual machine on the computer and Linux Ubuntu system
  • Assembled X-shell to connect Ubuntu system remotely; configured encrypted Hadoop clusters distributed processing environment through X-shell
  • Updated Hadoop configuration file with the newest configuration parameters on Apache website