The final day of the program began with a few hours for campers to prepare for their presentations by rehearsing and adding finishing touches to their posters.
Then came time for the presentations! The first group to present was computational biology. Students in this group worked to detect various cancers by using public data on the human genome. They explained the classifiers they tried, including decision trees, k-nearest neighbors, and k-means clustering. The group noted that their work could help identify cancer-causing genes that could potentially be eliminated with new technology.
Next up was the computer vision group, which has been working to map out poverty in Uganda. The group used public satellite images, transfer learning, and convolutional neural networks to extract features in the images. These features can then be inputted into a logistic regression, which can be used to determine a “poverty score” for the image. The group explained that in the future, this research could also help predict droughts and farm productivity.
The computer vision was followed by the NLP group, which used NLP for disaster relief by sorting tweets from the Haiti earthquake and Hurricane Sandy into five categories based on what kind of aid the tweets were providing – food, water, medical, energy, or none. Students described the data pre-processing methods they used, such as simplifying words via stemming or lemmatization and removing stop words (“a”, “the”, “and”) that might slow down the model, and they explained how a Naive Bayes classifier works and why they chose it.
Last but not least, the robotics group presented their work on autonomous vehicles. Students described how they used proportional-integral-derivative (PID) controllers to make sure the car stayed on the line and implemented Dijkstra’s algorithm into code so that the robot could determine the shortest path between two locations.
After a catered lunch with their mentors, campers had a poster session, where they answered questions from their peers, alumni, graduate students, AI4ALL staff, and other community members who stopped by.
Several presentations on how to stay involved in computer science and artificial intelligence followed the poster session. Campers heard from representatives for Stanford Pre-Collegiate Studies, Stanford Online High School, the National Center for Women & Information Technology (NCWIT), and Girls Teaching Girls to Code. They then took a post-program survey to reflect on how their views have changed since the start of the program.
After the girls thoughtfully completed the survey, they headed back to their dorms, where they had a delicious dinner with several AI4ALL board members. During dinner, campers learned about the many opportunities available to them through the alumni program. An AI4ALL alum from last year, Stephanie Tena, gave a presentation about her research using k-means clustering to determine the water quality of a river, which was conducted as part of the alumni fellowship program.
Girls then went to their rooms to pack up their things, before having one final house meeting where they appreciated one another and said their goodbyes.
We are incredibly grateful to all the research mentors, undergraduates, graduate students, postdocs, professors, guest speakers, alumni, staff, sponsors, parents, and of course, students, for making the Stanford AI4ALL program possible. We hope the campers have had an amazing three weeks learning about AI, finding role models in guest speakers and research mentors, and making new friends. Although we’re sad to see these 30 incredible young women leave their dorms, we’re confident that they are leaving with a strong support network, and we’re so excited to see how they continue to use their knowledge for good!
Blog post and all photos by Anna Wong.