Wolfram Computation Meets Knowledge

Wolfram Summer School


Connie Loo

Technology and Innovation

Class of 2018


Connie Loo studied physics and earth system science at the University of California, Irvine. She is interested in research in geophysics, machine learning and renewable energy. She applied for the Wolfram Summer School program for the opportunity to create something useful while developing technical skills and clarifying her career goals. She likes science fiction, nature and writing.

Computational Essay

The Physics of Global Warming »

Project: Hearty—A Microsite That Helps You Reflect on Your Day


Use machine learning to analyze the sentiment of text input and facial expressions to identify actions and sources of positive, negative and neutral influences on your mood on any given day.

Main Results in Detail

This program outputs word clouds that show the user how much certain activities or actions may influence their mood. It summarizes how negative and positive the person’s day may have been based on the sentiment detected from each sentence of their daily log. It also detects how the person may have felt on a given day based on the facial expression present in the profile picture they put in.

Future Work

Machine learning can be further applied to a series of daily logs and selfies to look for patterns of mood and activities that the user inputs as well as to identify stress factors. If implemented in a smartphone application, the program can be made to send notifications to the user when the algorithm determines it would be beneficial to the user’s wellbeing. With the use of neural networks and other sources of data, such as from Apple Health, more categories can be added to identify more specific moods such as anger, excitement and sadness.