iDiary is a system that collects data from smartphones and wearable devices and allows people to ask it questions about their lives in an intuitive manner such as “Who did I meet yesterday?” or “How many hours did I spend with my family this month?”. Novel algorithms are needed to efficiently process and store this vast amount of contineously-generated sensor data. I will be working on such algorithms that are not only useful for the iDiary project, but are also essential for lifelong-learning in autonomous robotic systems.

During my previous internships at Leaf, Dropbox, and D. E. Shaw, I worked on several projects ranging from developing web apps to designing and building systems and researching new machine learning techniques. Last summer, I worked on novel research that involved learning financial signals using deep neural nets, and I designed and implemented a custom in-memory database for financial data.