Wolfram Computation Meets Knowledge

Wolfram Summer School


Yu-Wen Hsu

Science and Technology

Class of 2016


I earned my BC and MS in applied mathematics at National Chung Cheng University in Taiwan and my PhD in mathematics at Yale University. My research field was partial differential equations and geometric analysis, in particular geometric flow such as curve-shortening flow. During my studies at Yale, I developed an interest in teaching and math education. After my PhD, I stayed at Yale as a lecturer in order to continue my work on an innovative learning project that involved designing and creating an online learning system for students in the calculus courses at Yale. In 2014, I joined the Harvard preceptor group, where I taught, developed and supported sections of calculus-related courses. I am currently interested in machine learning, and would like to learn more about the Wolfram Language and how to use it in machine learning, with the goal of contributing to understanding the computational universe based on simple programs.

Project: Extracting Data from the Images of Plots

Have you ever wanted to get data out of a plot from a published paper, or from the images you see online? My project is to write a program in Mathematica that extracts a set of data points from the image of a 2D plot (a raster graphic image). It should be able to find the axes and read the numbers on the tick marks, then output sets of plotted points on the graphs. At the technical level, specific tasks include: being able to distinguish different datasets plotted in different styles, such as colors and line styles, and being able to keep track of different graphs that might intersect or overlap.

Favorite 3-Color 2D Totalistic Cellular Automaton

Rule 696965117