Affiliated Faculty

IUNI has over 165 faculty affiliates from across IU. You may browse through listings below – clicking on a name will expand to show you full listings. You may also search through keywords and biographies in the search bar below.

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Maupome, Gerardo Department of Cariology, Operative Dentistry and Dental Public Health, School of Dentistry / IUPUI
Bio: Gerardo Maupomé is an oral health researcher with primary interests in dental health services research and oral epidemiology, oral treatment needs among patients at high risk of disease or subject to health and social disparities, and analysis of professional practices – including how dental professionals make therapeutic decisions. He has worked in the private sector and in academia for the past 25 years. He is a Professor with Indiana University School of Dentistry since 2005, and currently has various affiliations with academic organizations in the USA (including IUNI) and in the UK. Dr. Maupomé has been involved in various research projects – spanning from epidemiological studies assessing the impact of public health fluoridation, to clinical trials of chlorhexidine varnishes; from community demonstrations to promote healthier lifestyle decisions, to quantitative appraisals of factors contributing to poor oral health and failure to access dental services; and from qualitative investigations into social and economic determinants of health, to economic analyses of the costs implied in health conditions and associated therapeutic procedures. Some of these studies have been focused on American Indians, people of Mexican and Hispanic origin, those 65 years of age and older, children, and population groups with restricted access to dental services.
Disciplines: Dentistry
McCranie, Ann Indiana University Network Science Institute / IUB
Bio: Ann McCranie is the Assistant Director of Research Administration at Indiana University Network Science Institute, responsible for proposal development, educational outreach and conference and talk planning. McCranie received her PhD in Sociology from IUB, and her research is focused on networks in several domains: personal networks and health decision making, networks within organization and how they impact change, and networks between researchers in the mental health services field. McCranie has also served as the managing editor for Network Science and as summer program faculty teaching network analysis for the University of Michigan's ICPSR Summer Program since 2011. She is the co-author of Recovery in Mental Health: A Critical Sociological Account.
Disciplines: sociology
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Smith, Eliot Psychological and Brain Sciences, College of Arts and Sciences / IUB
Bio: Distinguished Professor of Psychological and Brain Sciences Eliot Smith has pioneered the development of multi-agent models of information spread in social networks that draw on social psychological studies of social influence to incorporate realistic assumptions about how and when people will accept (and further transmit) the information they receive from others (Mason et al., 2007). Smith’s empirical studies and multi-agent modeling have focused on the cognitive and behavioral processes that occur when people receive information from others that differs from their own prior beliefs — processes that determine whether they accept the information and change their beliefs, ignore the information, or seek out further evidence to attempt to reconcile the inconsistency (Collins et al., 2011; Smith and Collins, 2009). Another investigation examined in depth strategies for processing inconsistent information and determining its validity (Smith, 2014). The multi-agent model led to the conclusion that people can best avoid misinformation by comparing incoming information to their own existing beliefs, and discarding it if it is too discrepant. Alternative strategies that are prominent in the literature — such as accepting new information if it comes from multiple independent sources — were found not to be useful. This is partly because people are not usually in a good position to know the overall structure of the social network and therefore cannot tell whether multiple information sources are truly independent of each other. That is, person A may hear the same information from both B and C and assume they are independent, when in fact both B and C might have obtained the information from a common source D.
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Yan, Xiaoran IU Network Science Institute / IUB
Bio: Xiaoran Yan is an Assistant Research Scientist at Indiana University Network Science Institute. His research concerns mathematical theories and models of networks, with a focus on community structures and dynamical processes on networks. Through cross-disciplinary collaborations, his work is being applied to diverse areas including social networks, neuroimaging and science of science studies. He worked as a Postdoctoral Research Associate at Information Sciences Institute of University of Southern California. Before that, he was a graduate fellow at Santa Fe Institute. He received a Ph.D. in Computer Science at University of New Mexico.
Disciplines: Computer science