Brown CS News

This fall, Peihan Miao joins Brown CS as assistant professor. She’s the latest hire in the multi-year CS With Impact campaign, our largest expansion to date. She specializes in cryptography and security with a focus on secure multi-party computation (MPC).

Why has computer science always sparked Peihan’s interest? One answer is that she’s repeatedly seen the seemingly impossible become a reality.  “I remember the first time I took a cryptography class,” she says. “It was magic to me, how anyone could do things like this! In a lot of other areas, you first have the application and then try to find the solution, but in cryptography we often have the solution in hand, and then a chance to employ it appears. RSA public-key encryption is a great example, developed almost two decades before its use on the internet. And the nice thing about working with math is that as you learn more, you can start making connections, looking at the same problem from different angles, getting new insights and ideas. That’s something I’m always trying to convey to my students: I want them to be impressed and fascinated in the same way that I’ve been, to share that experience.”

Peihan’s first exposure to computer science came a few years before high school, when some friends invited her to join a team of students at a summer camp that taught programming. “It wasn’t something I’d planned,” she says, “but I’d always loved math and I could see right away how it related to algorithms and programming. I really enjoyed it.” 

Leaving home for Shanghai Jiao Tong University, the idea of a career in computer science was still unformed: “But I found algorithms and complexity so fascinating, and my teachers thought I had potential. I’m so grateful that they encouraged me. ‘If you want to do research in theory,’ they said, ‘you should go out and see a bigger world, what people are doing in top universities.’ I was lucky enough to get into one of the top PhD programs in computer science and work with some of the best researchers in the world. The experience was just wonderful.”

Paging through Peihan’s CV, there are so many awards dating back as early as 2009 that I’m compelled to ask: does she consider herself a competitive person? Her response is as noteworthy as it’s unexpected.

“The short answer is no,” Miao says. She pauses for a moment. “But I’d like people to understand why. Like many women in STEM, I felt I had to prove myself twice as much, because some people tend to think that successful women have only gotten to where they are because they’re female. And yet these same women are doing fantastic research at the same time that they may have major family responsibilities and other struggles.”

“And they’re doing it,” she notes, “with very few role models. The vast majority of the time, their first instructor in computer science will be male, and those instructors might not understand that their women students have challenges that men aren’t able to solve for them. When I was getting my PhD, I went to a workshop for women theorists, and the experience of interacting with our women peers was so important for all of us. Since I became a faculty member, I’ve had more women students than average, and I’ve been trying to build a supportive community for them. We need to do that proactively, because it won’t be there unless we make an effort to make it happen.

“But I notice that cryptography has more women researchers than other areas, and I believe an important factor is that we have more female role models. For example, we’ve had Shafi Goldwasser, a Turing Award winner, since the 1980s. She has had amazing women students, and those students have produced others. Her success has also encouraged many young women students to start a career in cryptography. You can’t imagine how a single person can affect the gender ratio in our whole field! And this applies not just to women but to members of all historically underrepresented groups, who may have as many challenges or more. In my opinion, women and minority group members often have greater than average potential. Not only do we think differently, which is an asset, we’ve faced more challenges and overcome them in the past, so we can likely do so again in the future.”

Initially focusing on algorithmic game theory, Peihan became increasingly interested in cryptography and completed a PhD at UC Berkeley with Sanjam Garg. Working in cryptography felt, she says, like practical applications were appearing right in front of her eyes. Her current research in secure multi-party computation (recent papers include “Updatable Private Set Intersection” and “Private Set Intersection in the Internet Setting From Lightweight Oblivious PRF”) is a perfect example.

“Chrome, Firefox, and other browsers have the ability to check if your passwords have been leaked due to data breaches,” Peihan explains, “but how? Do they have access to your passwords in the clear? Do you have to be willing to share them? Absolutely not, because they’re doing it in a privacy-preserving way. This is the whole idea of MPC: you learn what you need to learn, but everything is encrypted, all your private information remains confidential.” 

And she feels that a technology transfer similar to the adoption of public key cryptography brought about by the rise of the internet is in the works: “Secure multi-party computation certainly looks equivalent. Thanks to the recent data privacy regulations in Europe as well as in California, Virginia, Colorado, and a lot of other states, people are more and more aware of privacy issues, and the industry is paying more attention. When the notion of MPC was introduced in the 1980s, barely anyone thought that one day it would be practical or deployed in our daily life, but we’re seeing it now, which is really exciting.” 

And the ramifications for socially responsible computing are clear. “We still rely on the big tech companies to take care of our data privacy,” Peihan says, “and in our community there’s a lot of debate around the idea that the individual has so much less power – limited storage, limited connectivity, limited processing – than a big company, and we want the user to get a better sense of what’s going on instead of just trusting huge corporations. Could it be possible for us to verify and audit them in a very cheap and efficient way and make sure that they’re doing the right thing? I don’t have a good answer, but the general public should know that many researchers in our community are aware of the problem and seeking good solutions.”

To her surprise, Miao says, the two halves of her background ended up having a lot in common: in game theory, intelligent agents have differing incentives, and in cryptography, users have private data that they don’t want to leak: “I’m trying to connect them now, finding out what the differences and similarities are. When I was just working on game theory, I didn’t think about privacy, and when I began working on cryptography, I didn’t think about rationality – why would users cheat? Now that I have experience in both, I’d love to try finding their connections.”

Connections of another kind are a big part of what Peihan is excited about experiencing at Brown. “There are a lot of natural collaborators for me,” she says, “such as Anna Lysyanskaya, Seny Kamara, Roberto Tamassia, just to name a few, and Brown is the sort of place where you can easily have a conversation with someone from another discipline, find common interests, and start a research project. And the students want to learn more: they have expectations for you to teach them more, to show them things that are really exciting. I’m also looking forward to becoming part of the Brown CS junior faculty community because they’re not just colleagues but all good friends, it’s definitely a welcoming community.”

And looking just a bit farther into the future, Peihan sees the seemingly impossible becoming a reality once again. “During the pandemic,” she says, “Apple and Google jointly deployed privacy-preserving contact tracing using secure multi-party computation technologies. It’s just one application, but people are becoming aware of the notion of MPC. People didn’t think this could happen, but here we go – we can do it, and we can do it efficiently! There are extremely interesting research problems coming up that I can’t wait to address, and the more we collaborate with industry, the more exciting it gets, because we see theory coming into practice in the real world, and having even more impact than we had ever imagined.”

For more information, click the link that follows to contact Brown CS Communications Manager Jesse C. Polhemus.