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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A - E
Allen, Colin History and Philosophy of Science and Medicine, College of Arts and Sciences / IUB
Baggetta, Matthew Governance and Management, School of Public and Environmental Affairs / IUB
Bio: Matthew Baggetta studies the civic implications of membership organizations. Such groups can be seen as sites where social network ties are formed and reinforced among individuals and as nodes in networks of membership and non-membership organizations. Baggetta is particularly interested in the selection of individuals into and out of membership groups and the possible causal effects of the organizations on the individuals within them.
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.
F - J
Gesselman, Amanda Kinsey Institute / IUB
Bio: Dr. Gesselman is a social psychologist and a research scientist at the Kinsey Institute. Dr. Gesselman's research examines dating and sexuality of single adults — with an emphasis on technology and health behaviors — and on the psychology, sexuality, and health of romantic couples.
Disciplines: Social Psychology
Harezlak, Jaroslaw Epidemiology and Biostatistics, School of Public Health-Bloomington / IUB
Bio: Dr. Harezlak is an Associate Professor interested in brain connectivity. He has been working with groups both at IU and at other US institutions on statistical models to incorporate both structural and functional connectivity in regularized regression models.
José, Jorge V. Physics, Stark Neurosciences Institute, College of Arts and Sciences, School of Medicine / Bloomington
Bio: The research in my lab goes from computational neuroscience studies of neurons and neuronal networks modeling animal behaviors to studies in humans affected by neurological disorders, including translational research applications. All research done in my lab is guided by a general principle of connecting neuronal dynamics to behavior. Autism Spectrum Disorder (ASD) is characterized by the lack of communicative and cognitive abilities. The current clinical diagnostic models have focused almost exclusively on the deficits providing qualitative behavioral treatments to improve the individual’s condition. In collaboration with Rutgers University and members of the Indiana University School of Medicine, we have been thinking about autism in a very different way. Recent technical advances in wearable sensing technology have helped us bridge the gap between observational clinical practices and quantitative objective research outcomes. The instruments we used in our laboratory settings allow motion tracking kinematics for different parts of the body, including the eyes’ minute motions, facial micro-expressions and body micro-movements. To analyze the “big data sets” produced by these recordings we developed new statistical analytics. Our analyses provide novel physiologically biometrics which may be used to characterizing sensory-motor signatures many which occur largely beneath detection of our naked eye capabilities. Our recent results offer new avenues for connecting the cognitive abilities of individuals by quantitatively studying their moment-by-moment natural micro-movements at a millisecond time scales. Synchronization of inhibitory neurons as a possible mechanism for attentional gain modulation. Naturally occurring visual scenes contain large amounts of spatial and temporal information that are transduced into neuronal spike trains along the visual sensory pathway. Human psychophysics indicates that only a small part of that information is attended. We have developed Hodgkin-Huxley neuronal models to analyze data obtained from electrophysiological experiments with nonhuman primates. We have suggested that attentional modulation of the synchrony of local interneuronal networks could potentially account for these observations. We also considered the case when two stimuli are presented simultaneously. The neuronal response is in between those for each stimulus presented separately (stimulus competition) and when one stimulus is attended. The neuronal response gets closer to the response to this stimulus presented alone (biased competition). When the stimulus contrast is varied, several types of gain responses have been found with attention. We introduced a biophysical neural network model of V4, constraining it to reproduce the dynamics observed in the absence of attention. We were able to reproduce some of the detailed neural activity reported experimentally and the stimulus competition. We are exploring the possibility that our model may provide a unified framework for attentional modulation in V4. From neuronal to an hydrodynamic model describing larvae zebra fish rich swimming repertoire. Larval zebrafish (LZF) provide a unique opportunity to study realistic neuronal models since the fish is transparent and most of its neuronal properties are measured. The LZF exhibits a variety of complex undulatory swimming patterns. This repertoire is controlled by the 300 neurons projecting from brain into spinal cord. We developed a segmental oscillator model (using the NEURON program) to investigate this system. By adjusting NMDA strengths and glycinergic synapses produced the generation of oscillation (tail-beat) frequency patterns over the range exhibited experimentally. To describe visually the experimentally observed bending patterns we also developed a biomechanical-hydrodynamic model to better understand how those outputs are generated by the neuronal model we developed.
K - O
Macklin, Paul Intelligent Systems Engineering, School of Informatics and Computing / Bloomington
Bio: I work in the newly-formed Department of Intelligent Systems Engineering, where I am helping to start the bioengineering track. My work involves developing sophisticated, multiscale models of tissues and organisms that show dynamical cross-talk and feedbacks between networks at multiple scales: genetics, epigenetics, RNA transcription, protein dynamics, cell phenotype, cell and tissue mechanics, multicellular communications through chemical and mechanical signals, tissue remodeling, networked physiologic subsystems (e.g., immune system, cardiovascular system, etc.), organism-scale health/behavior, and the epidemiologic scale that emerges from the distribution of individual traits. Most of my prior work has focused on cancer and tissue biology, and I am now expanding to other areas such as cognitive health. I have developed and maintain several open source packages for simulation investigations of these dynamical multiscale systems, and I also lead an international group in creating a data standard / data model for these problems.
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
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
Perry, Brea Sociology, College of Arts and Sciences / IUB
Bio: Brea Perry is an Associate Professor of Sociology at Indiana University, and received a Ph.D. in Sociology from IU in 2008. Prior to returning to Indiana in 2014, she was an Associate Professor at the University of Kentucky, where she founded and directed the interdisciplinary Health, Society, and Populations Program. Her research and teaching interests include social networks, medical sociology, mental illness, biosociology, social genetics, and quantitative methodology. One line of research focuses on complex interactions between genotypes, social statuses, and social environmental conditions (GxExE) in substance use pathways. Dr. Perry also studies personal social network dynamics and processes that accompany progression through illness careers. Much of her work employs egocentric social network analysis and multilevel and longitudinal modeling. Dr. Perry’s research has been funded by the National Institutes of Health, the National Science Foundation, the Spencer Foundation, and the McManus Foundation. She is currently the series editor of Advances in Medical Sociology.
Disciplines: Sociology
Pullen, Erin L. IU Network Science Institute / IUB
Bio: Erin Pullen is an Assistant Research Scientist at the Indiana University Network Science Institute. She came to Indiana University in 2015 after completing her PhD at the University of Kentucky. Her primary research interests include egocentric networks, medical sociology, health disparities, and quantitative methodologies. Broadly, she is interested in how relationships between personal social networks, health behaviors, and health outcomes co-evolve over time, particularly in the context of disadvantage and inequality.
Disciplines: Sociology
Razo, Armando Political Science, College of Arts and Sciences / IUB
Bio: Professor Razo's research interests are in the field of comparative politics, with special interests in the political economy of development and comparative analysis of networks and institutions. His research and teaching center around two themes: (1) how political institutions in developing countries affect economic performance; and (2) the study of political institutions and political organization in nondemocratic settings. Current research projects include the development of an ontology and linguistic corpus for comparative analysis of networks in international development. He teaches courses on networks and institutions, quantitative contextual analysis, development, positive political economy, and Latin American politics. He is the author of Social Foundations of Limited Dictatorship, published by Stanford University Press in 2008, which advances a network theory of private policymaking. A student of economic history, he is also co-author with Stephen Haber and Noel Maurer of The Politics of Property Rights (2003).
Disciplines: Political Science
Saykin, Andrew J. Radiology and Imaging Sciences, School of Medicine / IUPUI
Bio: Dr. Saykin is the Raymond C. Beeler Professor of Radiology and Imaging Sciences at Indiana University School of Medicine where he serves as director of the Indiana Alzheimer Disease Center and of the IU Center for Neuroimaging. He also holds appointments in Medical and Molecular Genetics, Neurology and Psychiatry. Before joining Indiana University in 2006 he served on the faculties of Dartmouth Medical School and the University of Pennsylvania. Dr. Saykin serves as Genetics Core leader of the NIA-sponsored multicenter Alzheimer’s Disease Neuroimaging Initiative (ADNI). Other collaborative federally sponsored projects examine cognitive changes associated with cancer chemotherapy, brain injury and schizophrenia. Dr. Saykin is the founding Editor-in-Chief of Brain Imaging and Behavior. His current research program focuses on the integration of structural, functional and molecular brain imaging with genomic and biomarker methods to study mechanisms of memory dysfunction and therapeutic response. Major goals include development of tools for early detection of dysregulated brain networks in older adults at risk for Alzheimer’s disease and identification of novel therapeutic targets based on imaging genetics association studies.
Shen, Li Radiology and Imaging Sciences, School of Medicine / IUPUI
Bio: Dr. Li Shen holds a B.S. degree from Xi'an Jiao Tong University, an M.S. degree from Shanghai Jiao Tong University, and a Ph.D. degree from Dartmouth College, all in Computer Science. Dr. Shen is an Associate Professor of Radiology and Imaging Sciences at Indiana University School of Medicine (IUSM), and Associate Director of IU Center for Computational Biology and Bioinformatics (CCBB). He is the Executive Director of the MICCAI Society Board of Directors. He is a member of the Center for Neuroimaging, the Center for Computational Biology and Bioinformatics, and the Stark Neurosciences Research Institute at IUSM, and IU Network Science Institute. He is also affiliated with Departments of CIS, ECE and Biostatistics, and School of Informatics and Computing at IUPUI. His research interests include medical image computing, bioinformatics, data mining, and network science. The central theme of his lab is focused on developing computational and informatics methods for integrative analysis of multimodal imaging data, high throughput "omics" data, fluid and cognitive biomarker data, and rich biological knowledge such as pathways and networks, with applications to various complex disorders. The ultimate goal is to improve mechanistic understanding of disease processes and treatment responses for early diagnosis and therapeutics. His research is primarily funded by NIH (NLM, NIA, NIBIB, NIAAA, NCATS), NSF, DOD and NCAA. Further information about Dr. Shen's research activities is available at http://www.iu.edu/~shenlab/.
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.
U - Z
Winecoff, William Political Science, College of Arts and Sciences / IUB
Bio: I am Assistant Professor of Political Science at Indiana University Bloomington. Most of my research considers the politics of global finance and other networked systems. Within this, I primarily focus on structural power in the world economy, the political nature of supposedly-technocratic economic institutions, theories of hegemonic financial (in)stability, the relationship between firm-level economic agents and political systems, and the ways in which changes in demographics and predominant technologies impact political economy. Most of this research employs quantitative methodologies. I teach courses pertaining to international political economy, international relations, and network methodologies. I took a Ph.D. in Political Science from the University of North Carolina at Chapel Hill in 2013 and a B.A. in Economics from Southern Illinois University at Carbondale in 2007.
Disciplines: political science
Wu, Xiaogang Center for Computational Biology and Bioinformatics, School of Informatics and Computing / IUPUI
Bio: Xiaogang Wu received his PhD degree in 2005 on Control Science and Engineering from Huazhong University of Science & Technology (HUST), Wuhan, China. One year after that, he was appointed to associate professor of the Institute for Pattern Recognition and Artificial Intelligence (IPRAI) in HUST. He has over 10 years of research experience in image processing, machine learning, artificial intelligence, pattern recognition, chaotic dynamics and complex systems. His previous research focused on nonlinear dynamical analysis of complex models, especially estimating parameters of chaotic systems by nonlinear time series analysis, symbolic dynamics and chaos synchronization, etc. He is currently a Bioinformatics Scientist in the Hood Lab at Institute for Systems Biology (ISB). Before he joined ISB, he was a Research Scientist in the School of Informatics and Computing (SoIC) at Indiana University-Purdue University Indianapolis (IUPUI). He was also affiliated with Indiana Center for Systems Biology and Personalized Medicine (CSBPM, a signature center in Indiana University-Purdue University at Indianapolis). His current research focuses on bioinformatics and systems biology, e.g., applying machine learning, swarm intelligence, and complex network modeling techniques into identifying systems biomarkers for early diagnosis and predicting drug responses based on systems pharmacology. He is also an Associate Editor of Frontiers in Systems Biology since 2009.
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