Academic: I joined the BU Department of Computer Science in 1999 after completing my
Ph.D. at UC Berkeley. My research interests are broadly focused on algorithmic and economic
aspects of e-commerce, networking, and large-scale data management, striking a balance between
theoretical foundations and rigorous data-driven experimentation.
Entrepreneurial: I am Chief Scientist and a member of the Board of Directors
at Cogo Labs,
a start-up based in Cambridge, MA, where I've had an executive role since the company's
founding (as Adverplex, Inc.) in 2005. Cogo leverages a proprietary technology
platform for online advertising, algorithmic marketing, and data analytics to guide incubated portfolio
companies from inception to profitability and beyond.
In 2010, the XIA team from CMU, BU, and U Wisconsin
was awarded $7.1M from the NSF under the Future
Internet Architectures solicitation.
We are actively recruiting BU students to conduct research on core XIA technology, applications and deployments of XIA, and to
help build the XIA implementation for Linux.
On sabbatical AY 2013-2014!
Current Students and Alumni.
Courses I Teach:
CS 330 -
Intro to Algorithms (Last taught: Spring '13)
CS 112 -
Intro to Data Structures (Spring '12)
CS 455/655 -
Computer Networks (Fall '10)
CS 559 -
Algorithmic Aspects of Computer Networks (Spring '10)
CS 591 - Electronic Commerce
CS 697 -
Computer Science Graduate Initiation Course (Spring '10)
The Networks Research Group
at Boston University meets regularly on Monday mornings. All are welcome.
My main research interests are in designing algorithms, conducting measurements
and building systems in networking, electronic
commerce, and large-scale data management. I'm a member of the
Networks Research group
and I regularly collaborate with several members of the
Data Management Group @ BU.
As Chief Scientist at Cogo Labs, I've been working on a
fascinating problem domain since the company's founding in 2005: the
algorithmic, data management, and systems-building challenges that arise on the buy
side of pay-per-click advertising, a canonical Big Data optimization problem.
I've also collected a few useful
pointers to helpful advice for prospective or
current graduate students.