I am interested in analyzing people's everyday behavior(e.g. engaging/avoiding social interaction, being active/inactive) revealed by technology. This involves extracting human behaviors such as their social engagement, activeness etc. in natural settings and predicting personal characteristics such as extraversion. In order to capture behaviors unobtrusively I develop self-tracking technologies which are effective in capturing natural behaviors of people.
I am also interested to investigate how people express themselves on various platforms in digital media(expressing opinion online, engaging in discussion). The work involve finding out the relationships between users behavior patterns and various factors such as platform affordances, content, community characteristics etc. Long term goal of this work is to enhance collaborative learning and engagement in these discussions environments.
Keywords: #HCI #Crowdsourcing #Human Centered Computing #Learning #Ubiquitous Computing #Mobile Computing#Large Scale Datamining #Collaborative learning
Resume: link to my CV
Extracting workplace personalities with Online and Physical Data(KIXLab, current) : We extract workplace personality holistically by using users online and offline behavior data. We argue that social behavior extracted at workplace(online and offline), are related to extraversion. more..
Supporting learning and collaboration in online discussion(KIXLab, current) : Online discussions on various platforms such as new article comment section, on social media(e.g. facebook, twitter, reddit) are often very fragmented. We aim to build a platform which is designed to help users to learn and collaborate to generate richly labeled and well structured arguments while discussing online. more..
Crowdsourcing techniques to find Contextual Emotion Labels in videos(KIXLab) : Dialog videos contain rich contextual, emotional, and intentional cues of the characters and their surroundings. In this project we aim to find a crowdsourcing technique to leverage these rich emotion labels. more..
Emotion Analysis through Context Understanding: We developed a "scenario based" approach that focuses on created such situation with dominant emotion, using a set of context information from sensor data. Verification of each scenario is done when application detect the scenario and asks user to tag his/her current prevailing emotion.
2004-2007: B.Sc.physics from Delhi University(India).
2008-20011: MCA(Master of computer application) from BIT, Mesra(India)
Hindi, English, Korean-Beginner level.
Reading, writing short stories, sketching, and trying different foods. Apart from these i love traveling. Some of the countries travelled so far are Vietnam, USA and South Korea.