My research interests include auditing algorithms, security and privacy, and online social networks. Much of my work focuses on using measured data to analyze and understand complex phenomenon on the Web. In many cases, I have leveraged the knowledge gained from measurements of the Web to build systems that improve security, privacy, and transparency for users.
As a new professor, I am actively recruiting new students. If you are interested in auditing algorithms, personalization algorithms, online tracking and privacy, or security on the Web, read the prospective students section of my webpage, and then send me an email.
- Auditing Algorithms: In recent years, there has been growing awareness of and concern about powerful algorithms that mediate information on the Web. For example, Google Search and Facebook both personalize the information shown to each user, while e-commerce sites leverage purchase history to drive advertisements and product recommendations. These algorithms can lead directly to harmful outcomes, such as politically-polarizing "echo chambers", Filter Bubbles, price discrimination by e-commerce sites against consumers, and even racial discrimination.
In our work, we are focused on auditing algorithms: we use carefully controlled experiments to understand the data and algorithms used by companies, and assess the impact of these algorithms on normal people. Examples of our work include personalization on Google Search, price discrimination on major e-commerce sites, and Uber's surge price algorithm. Our ultimate goals are to make algorithmic systems more transparent to the public, and to develop tools that help users avoid unwanted or harmful systems. We are also actively collaborating with regulators like the European Commission to turn our research findings into practical policy outcomes.
- Understanding Online and Offline Tracking:Tracking is ubiquitous on the Web today, and yet we have only the most basic understanding of who collects data about us, and how this data is shared with third-parties. We are currently engaged in several projects that are delving inside the tracking ecosystem to answer these questions, including looking at how information collected about consumers in the offline world gets moved into online contexts. Based on our findings, we plan to empower users with tools to help protect their privacy.
- Improving the SSL/TLS Ecosystem:The SSL/TLS protocol is a critical element of online security that protects everything from online banking to e-commerce to health records. However, recent events like the Heartbleed vulnerability have demonstrated that SSL/TLS is vulnerable to both software and human-induced failures. We are working with researchers at University of Maryland, Duke, and Stanford to understand the threats to SSL/TLS on the modern Web, and develop novel systems to address these challenges. Our work on SSL/TLS has appeared at IMC 2014 and IMC 2015.
|PhD in Computer Science||College of Engineering at UCSB||2008-2012|
|Masters in Computer Science||College of Engineering at UCSB||2006-2007|
|BS in Computer Science||College of Creative Studies at UCSB||2002-2006|
|CCIS Best Teacher Award||2015|
|Nominated for ACM Doctoral Dissertation Award||2012|
|Outstanding Dissertation Award from UCSB||2012|
|Best Paper Award: Honorable Mention at SIGCOMM||2011|
|Dean's Fellowship from UCSB||2010-2011|
|Distinguished Graduate Research Fellowship from UCSB||2008-2009|
|Best Poster Award at UCSB Graduate Student Workshop||2007|
|Nominated for Best Student Paper Award at IWQoS||2007|
|Microsoft Research Redmond||Cheng Huang and Jin Li||Summer 2011|
|Microsoft Research Cambridge||Thomas Karagiannis and Ant Rowstron||Summer 2010|