Welcome to InfoSeeking Lab

InfoSeeking Lab is situated in School of Communication & Information at Rutgers University. The lab is directed by Dr. Chirag Shah, and includes iSchool and Computer Science faculty, as well as several PhD, Masters, and undergraduate students. The funding for the lab, more than a million dollars so far, has come from federal agencies such as NSF, IMLS, and Smithsonian Institution, as well as private organizations such as OCLC, Amazon, Google, and Yahoo!

The lab engages in research and education activities in the larger fields of Information and Data Sciences, with a focus on information seeking/retrieval/behavior and social media. Current topics of interest include extracting search intentions, prediction and recommendations in exploratory search processes, big data analytics with social media, behavioral analytics with mobile and wearable tech, collaborative information seeking, and social/community-based Q&A. Interested in joining the lab as a funded student or a volunteer? Contact Us.

Sensor-aware Information Seeking Behavior

Everything on and around you explains yourself. We are investigating human (information) behavior via personal and socio-contextual signals from people. The signals are collected through mobile and wearable technologies.

Extracting Movers and Shakers in Community Question-Answering

Who should answer a given question? Who is going to be a rising star? Who will drop? This research aims to build statistical models to explain and predict behaviors of users in online communities.

Prediction and Recommendation in Exploratory Search

Can we predict if a search is likely to fail before it's too late? And if we could, how do we help? This research looks at data mining and machine learning approaching to prediction and recommendations in search processes.



A developer-friendly framework for investigating information retrieval and interaction activities.



A unique system that lets you work on multi-session or multi-user projects without leaving your browser.



Highly usable social-computational platform that collect, analyze, and explore social media data.



An system to automatically collect data and metadata from blogs, YouTube, Twitter, Flickr, and more.