Wolfram 2020 08-20 China Student Ambassador Presentation

The following topics are of interest to me, and I am currently starting my own business in Wolfram and Python, with Wolfram being the main language for prototyping and exploring initial ideas. After watching the following presentations, I will focus on biomedical and retinal image analysis as a deep learning research topic.

• 18:00-19:00

  Jingxian Wang, Department of Physics, Peking University.

  Meta-programming Basis in Mathematica.

  This section introduces the Mathematica computation flow, related functions and mechanisms, programming ideas, and case studies. The main idea is to start with Mathematica’s computational flow, explain how to do Meta-programming in Mathematica and some basic tools, and focus on big and small cases.

• 19:00-19:30

  Compilation in the Wolfram Language: Wu Ke, Shanghai Jiao Tong University.

  As you know, in Mathematica, the most common way to execute commands is through front-end communication with the kernel; in the Wolfram Engine, it is needed as an interpreter to run commands, but this interpreter style of operation usually requires memory for the virtual machine and is slow. The interpreter needs to be deployed on any machine that wants to execute the Wolfram language. In this talk, we’ll look at compile acceleration and the possibility of deploying code in Wolfram using Compile and the new CompileFunction function in version 12.

• 19:30-19:40 Intermission.

*19:40-20:10

Jing Zeyu, Shanghai Jiao Tong University School of Medicine: Processing Biological and Medical Information Using R-Link in Mathematica

The R language is the first choice of many researchers dealing with medical and bioinformatic processes. Because of its open-source nature, R has many extension packages for processing bioinformatics, but the complexity of R programming limits its use. The magical Wolfram language has complementary characteristics of simplicity, intelligence, and aesthetics, and the combination of R and Mathematica has given rise to R-Link, a powerful tool for processing bioinformatics. This Student Ambassador presentation will introduce the installation and use of R-Link, and demonstrate the power of R-Link with real-life examples that we hope will help our audience in the future.

• 20:10-20:40

  Deep retinal image analysis using Matheamtica, Mo-Rei Zhu, Department of Chemical Engineering, Southwest University of China

  Mathematica is used to segment and classify the retina of the human eye, and the segmentation task requires clear segmentation of the retinal vessels and the optic disc. The classification section provides categories for diabetic retinopathy (DR), glaucoma, and age-related macular degeneration.

• 20:40-21:10

  Yudi Wu, East China Tech Computer.

  Interaction of Python with Mathematica.

Multilingual interaction is a very interesting thing, and Python has a wide audience and a rich ecology. In this tutorial, we introduce Mathematica calls to Python, an easy-to-use method for calling Mathematica from Python, and examples of how to use Mathematica’s powerful functions to solve problems in Python. We’ll also present examples of how to use Mathematica’s powerful functions to solve problems in Python.