I'm a current PhD student in the Carnegie Mellon Human Computer Interaction Institute (HCII) working under Niki Kittur. My current research focuses on the topic of Sensemaking — or how individuals come to an understanding of a difficult subject from a large set of information. This is normally in the context of online search or information seeking — such as planning a large vacation, learning about a medical disease, or investigating a new hobby. In our lab, we've build a number of interventions to assist users while they're sensemaking, using techniques such as crowdsourcing, visualization, and natural language processing.
Bento Browser is a prototype iOS application that helps people organize their complex online searching tasks. By removing the typical tab based structure of the browser and replacing it with a task hierarchy, we let people seamlessly organize, suspend and resume their searching tasks. Check it out on the App Store!
Many crowd clustering approaches have difficulties providing global context to workers in order to generate meaningful categories. Alloy uses a sample-and-search technique to provide global context, and combines the deep semantic knowledge from human computation and the scalability of machine learning models to create rich structures from unorganized documents with high quality and efficiency
The Knowledge Accelerator (KA) uses crowdworkers to synthesize different information sources on the web in response to a query. We prototyped this system in order to explore crowdsourcing complex, high context tasks in a microtask enviornment. Our system performed quite well, checkout the answers it produced!