Nicole is an undergraduate student at Boston University, majoring in computer engineering. This summer, she is working in the Scanning Probe Microscopy Lab at Mount Holyoke College, studying domain wall formation and motion in ferromagnetic nanorings and nanowires. Nicole studies these ferromagnetic structures experimentally using atomic force microscopy (AFM) and theoretically using Object Oriented MicroMagnetic Framework (OOMMF) based in C++ and Tcl/Tk. Nicole is also volunteering in a computer science lab working on a RaspberryPi robot using Robot Operating System (ROS). Nicole hopes to expand her knowledge in the fields of physics and computer science as she continues her undergraduate education and is looking forward to the Wolfram Science Summer School to help her achieve this.
Project: Male and Female Classification
Machine learning enables computers to learn through experience. The goal of this project is to develop a machine learning algorithm that classifies people in photos as either male or female. A training set will be compiled and normalized using face detection, allowing the algorithm to learn patterns within the data. If this algorithm is successful, the computer will be able to determine gender from an image not contained in the training set.
Huang, G. B., M. Ramesh, T. Berg, and E. Learned-Miller. “Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments.” University of Massachusetts Amherst, Technical Report (2007): 7–49.
Favorite Outer Totalistic r=1, k=2 2D Cellular Automaton