Hari Sundaramís research lies at the intersection of social network analysis and computational advertising—designing algorithms and building systems to understand and to influence collective behaviors in large social networks. His research has won awards from the ACM and IEEE societies.
He is focused on making fundamental methodological contributions while motivated by real-world applications. Some core contributions to network analysis include community discovery (Lin et. al., 2008; Lin et. al., 2011); influence maximization (Sarkar 2015); detecting the onset of coordinated behavior (de Choudhury et. al., 2009); rapid detection of large scale changes to network structure (Lin et. al., 2011); study the effects of sampling (de Choudhury et. al., 2010). Some fun research questions on networked culture include: can a video game make us more productive (Nikkila et. al., 2013)? what makes a YouTube video interesting (de Choudhury et. al., 2009)?
Sundaramís current research is motivated by the challenge: how can we persuade millions of people to adopt behaviors that would be beneficial to them? Example behaviors include: leading healthy lifestyles; reducing individual energy consumption and greater civic engagement. The widespread adoption of these behaviors would lead to large scale societal benefits such as reduced healthcare costs, sustainability and a vibrant community. But, despite knowledge of benefits, many individuals do not adopt these behaviors.
To address the challenge of behavior change, one needs to innovate beyond addressing difficult questions in network analysis. He is pushing the boundaries of network analysis in the following ways: incorporating mechanism design in shaping network behavior; using the lens of information theory to distribute messages on a network; using ideas from behavioral economics and psychology to synthesize persuasive messages; analyzing physical-world interaction of a social network, via the internet of things. Here is a map that summarizes my current research interests.
His groupís current research projects include: network sampling (Kumar, Lao), persuasive messaging (Alsaad, Ho), evolution of individual beliefs (Narang, Luber, Kothari), community equilibrium and mechanism design (Lee), privacy and data mining trade offs in the Internet of Things (De). He is also collaborating with several faculty at Illinois on research projects : continuum models for networks (Meidani, Dey), internet of things (Kravets), persuasive messaging (Karahalios), crowd clustering (Parmeswaran), network cartography (Chang).
Sundaram is an Associate Professor at the University of Illinois at Urbana Champaign and holds a joint appointment between Computer Science and Advertising. Prior to Illinois, he was an Associate Professor at Arizona State University with appointments in Computer Science and the School of Arts, Media and Engineering; he helped co-found the latter. He earned his B.Tech from the Indian Institute of Technology, Delhi (1993), M.S. from Stony Brook University (1995) and Ph.D. from Columbia University (2002), all in Electrical Engineering. He loves to take photographs, listen to jazz and spend time with his family.