Taking Privacy to a New Level

Rebecca Patterson '18
 

Giulia Fanti ‘10 has been attending UC Berkeley, where she received her M.S. in Electrical Engineering and Computer Science and is currently in pursuit of her PhD.  Giulia was recently awarded Best Paper at this year’s ACM SIGMETRICS conference, which is quite an achievement! We reached out to congratulate her on the award and to ask her about her time at grad school.

 

What has grad school been like? What are the ways it differs from undergrad?
For me, grad school has really been an exercise in persistence. It can be difficult, frustrating, and very solitary. However, grad school has taught me to think more sharply, and it has been exciting to shape my own research directions. That's something that Olin really encourages, but having a stronger technical background makes the process easier, and also helps you choose better problems, in my opinion.

Why did you chose to pursue a PhD, and when will you finish your degree?  Do you have plans for what comes next?
I pursued a Ph.D. because I wanted to go into academia. I am planning to graduate by May 2016 and have not nailed down any plans for afterwards.

Tell us bit about the research you have been doing.
My research focuses on privacy-preserving algorithms: anonymous communication and private search. The goal of anonymous communication is to let people share their thoughts (e.g., on social media) without being identifiable as the author of a message--like a truly anonymous Twitter. The goal of privacy-preserving database searches is ultimately to let people search the web without telling search engines what they are searching for. It seems very counterintuitive, but there are algorithms that can do this. Along with my adviser, Prof. Kannan Ramchandran, I'm trying to make these algorithms efficient enough to build a privacy-preserving search engine.

Let’s talk a little about your award. What is it, why did you get it, and how did it make you feel?
Most conferences have a Best Paper Award, meant to recognize interesting and novel work presented at the conference. At this year's ACM Sigmetrics conference, my collaborators (Peter Kairouz, Prof. Sewoong Oh, and Prof. Pramod Viswanath) and I received the award, which was really exciting and surprising! In the last few years, there has been a lot of research on trying to infer the "patient zero" of an epidemic. We flipped the problem around and asked how to spread a message so that it's impossible to infer the source reliably. This might be relevant if you're trying to communicate with a lot of people anonymously, e.g., to organize a political protest in a country under heavy government surveillance. It's a very timely problem, and it turned out to have a nice mathematical formulation and solution, which we present in our paper.

What do you do for fun?
I enjoy soccer, sailing, and playing the piano.

 
 
Posted in: Alumni Speak, Graduate School, Research