Peter Washington is a fourth year Bioengineering Ph.D. candidate at Stanford University. Peter’s thesis works on using machine learning to measure human behavior, particular symptoms related to pediatric autism for diagnostics, and longitudinal tracking. Before his Ph.D., he did a Master's in Computer Science at Stanford University and undergrad at Rice University in Texas studying Computer Science. In general, he is interested in advancing AI that can understand human behavior and using the resulting AI to help people.
HOW DID YOU CHOOSE WHAT YOU STUDIED IN COLLEGE? HOW DID YOU END UP STUDYING AI?
“I originally wanted to study political science and economics, but I took a programming class my freshmen year that highlighted how programming can be applied to any field. I was instantly intrigued.”
WHAT RESEARCH/INDUSTRY WORK WITHIN AI HAVE YOU BEEN FOCUSED ON? WHAT EXCITES YOU ABOUT THE FUTURE OF AI?
“I work on building computer vision models for quantifying human behavior and using these models for digital therapeutics for developmental delays. I am excited about how AI-powered technologies can be used to help people in a scalable, accessible, and affordable manner.”
WHAT HAS BEEN THE HIGHLIGHT OF YOUR TEACHING EXPERIENCE IN INSPIRIT AI?
“It has been amazing to see how quickly all students have learned many advanced concepts in such a short time. I am also impressed with all of the insightful questions that students come up with - I always learn something new from finding out the answers to student questions every time I teach!”
WHAT ADVICE WOULD YOU GIVE TO YOUNG PEOPLE WHO ARE INTERESTED IN STUDYING AI OR PURSUING A CAREER IN AI IN THE FUTURE?
“You have learned the basics of what you need to know to start building your own models now! Use the Inspirit notebooks as a reference.”
