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.

If you are faculty at IU (all ranks), you may join us by submitting a short form and you can manage your individual listing.

Remove Search Terms 


| A - E | F - J | K - O | P - T | U - Z |


A - E
Barnes, Priscilla Applied Health Science, School of Public Health / IUB
Bio: Dr. Priscilla Barnes' research interests are in public health systems and services. More specifically, she examines inter-organizational factors that influence the quality of preventative services that disadvantaged populations receive within the U.S. public health system. She used primary and secondary data to create network-inspired visualization maps that illustrate types of partnerships (information sharing, coordination, cooperation, collaboration) that promote delivery of health education and population health management initiatives in local communities.
Escanciano, Juan Carlos Economics, College of Arts and Sciences / IUB
Bio: Dr. Juan Carlos Escanciano is originally from Madrid, Spain. He attended Universidad Complutense de Madrid, where he received a B.S. in math, and University Carlos III de Madrid where he received a Ph.D. in Economics in 2004. Following two years on the faculty of the Universidad de Navarra, in Pamplona, Spain, Dr. Escanciano came to Indiana University in 2006 as an Assistant Professor of Economics. His research interests fall broadly into the area of econometric theory and applications, with a recent emphasis on identification of flexible econometric models.
K - O
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
Menczer, Filippo Informatics and Computer Science, School of Informatics and Computing / IUB
Bio: Filippo Menczer is a Professor of informatics and computer science, adjunct Professor of physics, and a member of the cognitive science program at Indiana University, Bloomington. He holds a Laurea in Physics from the University of Rome and a Ph.D. in Computer Science and Cognitive Science from the University of California, San Diego. Dr. Menczer has been the recipient of Fulbright, Rotary Foundation, and NATO fellowships, and a Career Award from the National Science Foundation. He currently serves as director of the Center for Complex Networks and Systems Research and is a Fellow of the Institute for Scientific Interchange Foundation in Torino, Italy, a Senior Research Fellow of The Kinsey Institute, and an ACM Distinguished Scientist. He previously served as division chair in the IUB School of Informatics and Computing, and was Fellow-at-large of the Santa Fe Institute. His research is supported by the NSF, DARPA, and the McDonnell Foundation. It focuses on Web science, social networks, social media, social computation, Web mining, distributed and intelligent Web applications, and modeling of complex information networks.
Disciplines: Computer Science
P - T
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.