Day 10: Chats with the camp founders and more research!

Day 10 of SAILORS kicked off with a delicious breakfast and plenty of time to continue research.

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Photo by Jimin Lee.

After breakfast, everyone split up into the four research groups – Natural Language Processing (NLP), Computer Vision, Self Driving Cars/ Robotics, and  Cancer Genomics. Having just a couple of days before the presentations of finalized projects, all four projects got together and started to wrap up their work. The Natural Language Processing research group built a classifier and learned about neural networks. The Computer Vision research group finished coding for mapping out poverty in Uganda. The Self Driving Cars/ Robotics research groups applied the Dijkstra Algorithm to their robots and is a step closer to their final challenge. The Cancer Genomics research groups worked with three classifiers for five different types of cancers.

After lunch, we had some more time to work on our projects.

Olga Russakovsky, co-founder of SAILORS, shared her experiences as a woman in STEM, sharing many insights of her career with the us. Her story was so inspiring and motivational for us all to listen to and learn from.

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Photo by Lauren Yang.

After dinner, everyone gathered around a warm campfire for the classic 4th of July activity – s’mores!

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Photos by Lauren Yang.

The day concluded with the campers having a conversation with Fei-Fei Li. It involved Fei-Fei giving us encouragement and advice for the future, visions for SAILORS, and her personal experience of how she became passionate about AI.

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Photo by Lauren Yang.

The girls all learned so much these past two weeks, and can’t wait to start working on posters, share our projects with others, and see what other groups have been working on!

Blog post by Jimin Lee and Esther Cao. Photos by Jimin Lee and Lauren Yang.

Day 9: Research groups, human-car interaction demo, and Invoke string quartet!

The second week of SAILORS commenced with a highly anticipated meeting in their research groups. Our research projects were led under the guidance of Stanford Artificial Intelligence Laboratory’s students and assistant professors.

Here’s a sneak peak of the research project meetings, NLP and computer vision, that we, Sarah and Kyra, attended.

To kick off the natural language processing (NLP) meeting, the group was introduced to the nest of NPL research, the linguistics building. Enjoying a new spacious environment, we settled into transferring last week’s Bayes Rule into the this week’s AI Naive Bayes model. Using the example of a game show, red and green balls, and two boxes, the group set off with Python-refreshers and exercises to conquer their very own Naive Bayes algorithms. After a sufficient time on Jupyter Notebook, the group moved on discuss the multiple uses of Naive Bayes and chatbots, old and new.

Soon, the NLP group will apply their new knowledge to their main project and use Naive Bayes to classify text tweeted during Hurricane Sandy.

In the computer vision research group, led by CS master students Shane and Alex, we began coding for our research project of ‘The poverty map of Uganda.’ Using Python, we coded classes in machine learning and poverty identification on Jupyter Notebook. We debated about different features that would be crucial in identifying poverty (with satellite images from the Ermon Lab) in Uganda such as roads, lights, cars, and property value.

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Photo by Sarah Chun.

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Above is a photo from the robotics research project. Photo by Lauren Yang.

After our morning research project, we had the opportunity to listen to a lecture on ‘Decoding the Human Genome to Decipher the Genomic Basis of Disease’ by Anshul Kundaje, Associate Professor of Genetics and Computer Science at Stanford University. Prof. Kundaje spoke about using artificial intelligence to decode and identify genome functions within the human DNA. Using deep conventional neural networks (CNN), we can learn about hundreds of novel made patterns in cell-specific control elements in our genes. We also learned about the future of genome sequences, which can identify possible disease associated variants within our DNA and allow the public have access to their personal genome sequence and diagnosis.

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Photo by Hank Tian.

Before dinner, we had a demo called ‘Human Car Interactions’ where we learned about human behavior alongside artificially-intelligent cars.  

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Photo by Lauren Yang.

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Photo by Lauren Yang.

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Photo by Lauren Yang.

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Above are the bloggers of this post. Left: Sarah. Right: Kyra. Photo by Lauren Yang.

Upon arrival, the SAILORS were met with the contemporary string quartet, Invoke. With both strings and banjos, a capella and special sound effects, the musicians bestowed a mystical, mesmerizing, and exhilarating performance. We were quick to follow up questions and contact requests, as always.

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Photo by Lauren Yang.

Blog post by Kyra Mo and Sarah Chun. Photos by Lauren Yang, Kyra Mo, Sarah Chun, and Hank Tian. 

Day 7: Carnival and SAIL-ON alumni panel

Day 7 was filled with lots of fun and well deserved relaxation. Students had the morning to themselves; many of them explored the campus. After lunch, students headed over to the carnival, which featured a petting zoo, a photo booth, henna, Zorb balls, mini golf, and more. Students cooled off with popsicles and snacked on popcorn and cotton candy.

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After the carnival, campers attended an event SAIL-ON members organized. SAIL-ON is an organization comprised of SAILORS alumni. Previous SAILORS students from 2015 and 2016 came back to the Synergy dorm to share their experiences in the STEM field. Many talked about what they have accomplished since SAILORS and emphasized that campers should take initiative to spread AI.

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After that, campers had free time. The day ended with a house meeting.

Blog post and pictures by Lauren Yang.

Day 6: Dinner Banquet, Classification Lecture, and Computer Vision Applications

On Day 6, Google engineer Eugene Davydov gave a lecture on classification methods including decision trees, Naive Bayes, and k-nearest neighbors.

Stanford professor Stefano Ermon then presented his lab’s work on using artificial intelligence to serve the UN’s 17 Sustainable Development Goals for 2030. Ermon’s lab fed AI algorithms satellite images of locations around the world to measure poverty levels using identifiers for economic development such as night light intensity. Another project used satellite images to predict crop yield in various agricultural communities.

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Following lunch, students worked with their research mentors and groups. They prepared for presentations to be held at a banquet later in the evening.

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Students from the robotics group code their robots.

The dinner banquet opened with an introduction by program director and Professor Fei-Fei Li.

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The event featured a talk by Dr. Alison Okamura, a well-known robotics researcher and professor at Stanford.

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Students also gave speeches, which summarized their respective research topics. The students especially thanked Professors Fei-Fei Li and Olga Russakovsky and their PhD research mentors.       

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Various AI4ALL board members pose for a photo.

Blog post by Amelie Buc and Meili Gupta. Pictures by Lauren Yang.

Day 5: Machine Learning Lesson, Jack Rabbot, and AI and government policy

Day 5 began with a lecture on machine learning, in which students learned about supervised, unsupervised, and semi-supervised AI systems as well as regression and classification.

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Students then went to a demonstration of a robot designed by numerous Stanford PhD students and professors. The robot, affectionately named Jack Rabbot, is capable of using various sensors to navigate crowded areas whilst maintaining a human-like sense of social etiquette. More information can be found at http://cvgl.stanford.edu/projects/jackrabbot.

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Later in the day, Stanford professor Noah D. Goodman presented a summary of the intersection of psychology and artificial intelligence. In particular, he focused on the use of probabilistic programs in uncertain situations to model human decision-making.

Students worked in their research groups, many beginning to code algorithms. The day proceeded with a talk by David Wallerstein, the Chief Exploration Officer of Chinese internet conglomerate Tencent. He inspired students with his vision of AI as capable of solving the world’s greatest problems.   

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Back at the house, Terah Lyons described her career in AI policymaking under the Obama administration. Her dedication to public service and STEM representation in government were incredibly empowering.

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Photo by Fiona Hall-Zazueta.

20170629_195344.jpg Photo by Fiona Hall-Zazueta.

Blog post by Amelie Buc and Meili Gupta. Pictures by Lauren Yang and Fiona Hall-Zazueta.

Day 4: Field trip to the Computer History Museum, Graph Search, and AI and Airplanes!

The girls began the day with a lesson on graph search. Campers learned about the main graph search algorithms, such as Dijkstra’s algorithm, breadth-first search, and depth-first search.

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After that, campers listened to a lecture by Professor Mykel Kochenderfer about airplanes and artificial intelligence. Prof. Kochenderfer discussed how his research in AI algorithms has greatly improved aircraft and aeronautic safety. The girls learned how artificial intelligence is key in maintaining safety and preventing crashes in dynamic environments.

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After that, the campers took a field trip to the Computer History Museum. Edward Feigenbaum, a notable computer scientist and artificial intelligence researcher,  led a tour through the museum. Campers not only learned about the birth of computing but also about notable female computer scientists like Ada Lovelace.

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The day concluded with a personal growth session about scientific writing, blogging, and sharing research. Guest speakers included Sherol Chen, Melanie Warrick, and Ayman Nadeem.

 

Day 3: Autonomous car demo, classifier lecture, and NLP lesson

Day 3 started with a classifier lecture. Campers learned about the characteristics of classifiers, such as its features, how to train them, evaluate them, and test them.

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After the classifier lecture, the girls had the opportunity to see and demo an autonomous car. The car, named Junior, was a winning submission in the Urban Challenge, an autonomous car competition held in 2007. Campers learned about not only the technical aspect of such cars but also the potential benefits and harms that self-driving cars could have on the world. After the demo, the girls had a chance to eat lunch with members of Zoox, an autonomous car company.

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Pictured above: campers pose for a silly group picture with Zoox engineers.

After lunch, the girls engaged in a lecture about natural language processing (NPL) from Professor Percy Liang. The girls broke out into their respective research projects after the lecture.

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Pictured above: A camper engages in discussion in the “Assisting Disaster Relief with Natural Language Processing” research project.

The day concluded with a creative writing and spoken word activity and a house meeting.

Blog post and photos by Lauren Yang.