My research interests include online social networks, security and privacy, and algorithmic society. Much of my work focuses on using measured data to analyze and understand complex phenomenon on the 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 social networks, security and privacy, or personalization algorithms, read the prospective students section of my webpage, and then send me an email.
- Filter Bubbles and Algorithmic Society: Many websites use personalization to fine-tune content for each user. For example, if you and a friend both search for identical keywords on Google, it is likely that you will each receive slightly different results. However, social scientists have begun to argue that this invisible personalization is harmful to users. In our work, we are focused on quantifying the degree to which major websites personalize content and what information they use to power their algorithms. Once we understand the underlying mechanisms behind these algorithms, we can devise new techniques to overcome them. Our work on understanding personalization algorithms has appeared at WWW 2013 and IMC 2014. You can learn more about this work, as well as download our code and data, by visiting our site dedicated to the subject. We are actively researching other areas of web and real-world personalization, as well as defense mechanisms to pop Filter Bubbles.
- Crowdturfing: There is a growing underground market on the Web for malicious crowdsourcing. For just a few cents, you can buy Facebook likes, Twitter followers, bulk social networking accounts, and fake reviews on Yelp. These types of social spam are extremely difficult for existing security systems to stop because the damage is caused by real people, not automated programs. In our work, we have measured malicious crowdturfuing systems, and we are actively engaged in devising new solutions to stop these insidious threats.
|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|
|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|