I am a PhD candidate in the iSchool at University of Michigan, advised by Mark Newman.
My work centers around context-aware computing. Consider my CV
and Projects.
Contact:
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Projects
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Crowd-generated Contextualized Behavior Change Messages
We present a crowdsourcing algorithm that enables paid workers to create context-appropriate and tone-sensitive behavior messages. Our approach is the first to leverage crowd-workers for generating “fresh” messages.
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Recommending Lifestyle and Behavior Changes
Modeling people’s context, habits, lifestyles, wellness goals and their achievements and failures allow interventions that are personalized to the needs of the individual. Proposed a recommender system that leverages user-similariy to recommend the most effective lifestyle choices.
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Interactive DVD as a Platform for Education
The project leveraged the capabilities of the standard TV DVD player to view interactive educational content like Wikipedia, children books and PowerPoint slides.
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StoneSoup: A Community Driven Proactive Display
A community driven proactive display system that detects the nearby users and allow its users to personalize content for the display with reduced the burden of updating content.
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Understanding Lending Behaviors on Online Microlending Platforms: The Case for Kiva
Our in-depth analysis of a kiva.com shows that lenders appear to lend more to highly rated institutions, and with what appears to be better planned lending decisions; and that smaller, homogeneous teams seem to drive more lending activity and to achieve larger team lending agreements.
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Twitter Quakes
Developed a technique to measure the impact of global events on different geographic locations. Our technique measures significant increase in the volume of tweets during specific time periods, which are generally caused by some significant happening of the event.
Notes
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Crowd-sourced Financial Support: Kiva lender networks20 Apr 2014
This study looks at how the lender network of Kiva based on the team membership correlates with the fulfillment of loans and the outcomes of the fulfilled loans. In particular, we are interested in predicting (1) how soon a loan is funded, as well as (2) whether the loan gets funded by the deadline. -
G-Money: Earning Calls Predict Stock Performance20 Dec 2012
We show that the beliefs of informed investors can be learned during earning conference calls. This can be used to explain variations in stock price performance not accountable by current asset pricing theory. -
Artificially Intelligent Grid Assistant (A.I.G.A)20 Feb 2008
We present a Grid based application which works in collaboration with natural language processing (NLP), to act as a virtual assistant. The application can answer queries in a conversational manner and is capable of being deployed in various scenarios.
News
| [07/02/14] | Had an excellent time at HCIC’14 |
| [05/04/14] | CHI’14: SVing, workshop, and a lot of fun! |
| [02/17/14] | CHI’14 Workshop paper accepted |
| [02/15/14] | CSCW’14 SVing was a lot of fun |