The Center for the Study of Complex Systems supports a diverse body of research. Research specialties of our core faculty can range from social networks, to the spread of infectious disease, to thermodynamics, bee pollination to any number of other complex systems. Below you will find a statement about the research interests of each of our Core faculty members, a link to their lab or personal website, a list of three recent/selected publications as well as a list of any books/book chapters.
To see a list of faculty by 'fields of study' go to the People page and click the 'Browse: Fields of Study' drop-down near the top right of each page. To search by LSA department, type the department name in the 'Profile Search' box above Fields of Study - ie 'sociology' will return faculty members affiliated with the Sociology Department.
I am an Associate Professor in Sociology and Complex Systems at the University of Michigan, and an External Faculty member at the Santa Fe Institute. I lead the Computational Social Science Initiative at the University of Michigan.
My research focuses on the quantitative study of human behavior, and what it implies for larger scale social patterns.
Bruch, Elizabeth and Mark Newman. 2018. “Aspirational Pursuit of Mates in Online Dating Markets.” Science Advances 4: eaap9815.
Bruch, Elizabeth and Mark Newman. 2019. “The Structure of Online Dating Markets in U.S. Cities.” Sociological Science 6: 219-234.
Bruch, Elizabeth and Joffre Swait. 2019. “Choice Set Formation and its Implications for Segregation Dynamics.” Demography Available via Online First.
Bruch, Elizabeth, Ross Hammond, and Peter Todd. 2015. “The Co-Evolution of Decision Making and Social Environments.” Chapter in Emerging Trends in the Social and Behavioral Sciences, edited by Robert Kaplan and Stephen Kosslyn. Hoboken NJ: John Wiley and Sons.
TAGS: sociology, dynamical systems, networks, information diffusion, social choice theory, computational social science, formal modelling
Charles Doering’s research is focused on the analysis of mathematical models with the aim of extracting reliable, rigorous, and useful predictions. These models range from stochastic, dynamical systems arising in biology, chemistry and physics, to systems of nonlinear partial differential equations such as those that (ostensibly) describe turbulent fluid flows. The techniques employed range from the development of exact solutions to the application of modern mathematical methods including rigorous estimation, careful numerical computations and simulations, and the use of abstract functional and probabilistic analysis --- often a combination of all three approaches.
On the optimal design of wall-to-wall heat transport, Charles R. Doering and Ian Tobasco, Communications on Pure and Applied Mathematics 72, 2385-2448 (2019).
Turning up the heat in turbulent thermal convection, Charles R. Doering, Proceedings of the National Academy of Sciences of the United States of America 117, 9671-9673 (2020).
Heat transport bounds for a truncated model of Rayleigh-Bénard convection via polynomial optimization, Matthew L. Olson, David Goluskin, William W. Schultz and Charles R. Doering, Physica D 415, 132748 (2021).
TAGS: Mathematics, Physics, dynamical systems, agent-based modeling, formal modeling
I am an associate professor in the departments of Epidemiology, Complex Systems,& Mathematics at the University of Michigan, Ann Arbor. My lab’s research program is in mathematical epidemiology, and is focused on using and developing parameter estimation and identifiability techniques to model disease dynamics.
Much of our work is in building multi-scale models of infectious diseases, including examining cholera, environmentally driven diseases, and HPV dynamics. Our research blends mathematics, statistics, and epidemiology to understand transmission dynamics, inform optimal intervention strategies, and improve forecasting.
Brouwer, A. F., Delinger, R. L., Eisenberg, M. C., Campredon, L. P., Walline, H. M., Carey, T. E., & Meza, R. (2019). HPV vaccination has not increased sexual activity or accelerated sexual debut in a college-aged cohort of men and women. BMC public health, 19(1), 821.
Brouwer, A. F., Eisenberg, M. C., Love, N. G., & Eisenberg, J. N. (2019). Phenotypic variations in persistence and infectivity between and within environmentally transmitted pathogen populations impact population-level epidemic dynamics. BMC infectious diseases, 19(1), 449.
Hayashi, M. A., Eisenberg, M. C., & Eisenberg, J. N. (2019). Linking Decision Theory and Quantitative Microbial Risk Assessment: Tradeoffs Between Compliance and Efficacy for Waterborne Disease Interventions. Risk Analysis.
TAGS: epidemiology, mathematics, dynamical systems, agent-based modeling, networks, formal modeling, mathematical biology
Jordan Horowitz is an assistant professor of Biophysics and Complex Systems at the University of Michigan. His research has ranged broadly in the area of nonequilibrium statistical thermodynamics, with a focus on developing universal thermodynamic constraints to far-from-equilibrium dynamics. His work has been profiled in New Scientist Magazine and Quanta Magazine.
“Universal thermodynamic bounds on nonequilibrium response with biochemical applications”
JA Owen, TR Gingrich, JM Horowitz
Physical Review X 10 (1), 011066 2 2020
“Thermodynamic uncertainty relations constrain non-equilibrium fluctuations”
JM Horowitz, TR Gingrich
Nature Physics 16, 15-20 71 2020
“Inferring broken detailed balance in the absence of observable currents”
IA Martínez, G Bisker, JM Horowitz, JMR Parrondo
Nature communications 10 (1), 1-10 15 2019
TAGS: Biophysics, dynamical systems, statistical and biological physics, formal modeling, information diffusion, mathematical biology
I am a computational social scientist and an Assistant Professor at the University of Michigan in the School of Information and the Center for the Study of Complex Systems.
My current research interests are around structure, governance, and inequality in sociotechnical systems; measurement; and social networks.
Jacobs, A. Z. (2018). Assembly in populations of social networks. arXiv preprint arXiv:1811.01452.
Jacobs, A. Z. (2017). Comparative, population-level analysis of social networks in organizations. https://scholar.colorado.edu/
Jacobs, A. Z., Way, S. F., Ugander, J., & Clauset, A. (2015, June). Assembling thefacebook: Using heterogeneity to understand online social network assembly. In Proceedings of the ACM Web Science Conference (p. 18). ACM.
TAGS: Information, networks, information diffusion, social choice theory, computational social science
In the King Lab, we use sophisticated mathematical, computational, and statistical tools to advance our theoretical understanding of ecological and evolutionary processes. We formalize scientific hypotheses as mathematical models to make precise predictions and powerful inference. One major focus of our research is the ecology and evolution of infectious diseases. We formulate mathematical models and confront them with data to learn about the mechanisms that operate in the host-pathogen interaction and about how they are likely to evolve. Students and postdocs in the lab have a wide range of interests; the common thread is the use of rigorous theoretical approaches on fundamental questions in ecology and evolutionary biology.
N. Wale, M. J. Jones, D. G. Sim, A. F. Read, and A. A. King (2019) “The contribution of host cell-directed vs. parasite-directed immunity to the disease and dynamics of malaria infections” Proc. Natl. Acad. Sci. U.S.A., in press.
M. Domenech de Cellès, P. Rohani, and A. A. King (2019) “Duration of Immunity and Effectiveness of Diphtheria-Tetanus-Acellular Pertussis Vaccines in Children” JAMA Pediatrics, in press.
C. Bretó, E. L. Ionides, and A. A. King (2019) “Panel data analysis via mechanistic models” J. Am. Stat. Assoc., in press.
A. A. King, Matthieu Domenech de Cellès, Felicia M. G. Magpantay, and P. Rohani (2018), “Pertussis Immunity and the Epidemiological Impact of Adult Transmission: Statistical Evidence From Sweden and Massachusetts” in P. Rohani and S. Scarpino (eds.) The Integrative Biology of Pertussis. Oxford University Press, Oxford.
TAGS: ecology and evolutionary biology, dynamical systems, agent-based modeling, statistical and biological physics, networks, formal modeling, information diffusion, mathematical biology
Our group conducts research on the structure and function of networks, particularly social and information networks, which we study using a combination of empirical methods, analysis, and computer simulation. Among other things, we have investigated scientific coauthorship networks, citation networks, email networks, friendship networks, epidemiological contact networks, and animal social networks; we've studied fundamental network properties such as degree distributions, centrality measures, assortative mixing, vertex similarity, and community structure, and made analytic or computer models of disease propagation, friendship formation, the spread of computer viruses, the Internet, and network navigation.
Network structure from rich but noisy data, M. E. J. Newman, Nature Physics 14, 542-545 (2018)
Structure and inference in annotated networks, M. E. J. Newman and Aaron Clauset, Nature Communications 7, 11863 (2016)
Power-law distributions in empirical data, Aaron Clauset, Cosma Rohilla Shalizi, and M. E. J. Newman, SIAM Review 51, 661-703 (2009)
Hierarchical structure and the prediction of missing links in networks, A. Clauset, C. Moore, and M. E. J. Newman, Nature 453, 98–101 (2008)
Modularity and community structure in networks, M. E. J. Newman, Proc. Natl. Acad. Sci. USA 103, 8577-8582 (2006)
Mark Newman, Networks, 2nd edition, Oxford University Press, Oxford (2018).
Mark Newman, Computational Physics, Createspace Independent Publishing (2012).
Daniel Dorling, Mark Newman, and Anna Barford, The Atlas of the Real World, Thames & Hudson, London (2008).
TAGS: physics, networks, dynamical systems, agent-based modeling, formal modeling, information diffusion, social choice theory, computational social science
My research focuses on the myriad roles that diversity plays in complex systems. For example, how does diversity arise? Does diversity make a system more productive? How does diversity impact robustness? Does it make a system prone to large events?
I have also published papers in a variety of disciplines including economics, political science, computer science, management, physics, public health, geography, urban planning, engineering, and history.
"When Order Affects Performance: Culture, Behavioral Spillovers, and Institutional Path Dependence." American Political Science Review. 112(1):82–98, 2018. (with Jenna Bednar).
“Directional behavioral spillover and cognitive load effects in multiple repeated games." Experimental Economics. 21: 1–30, 2018. (with Tracy Liu, Jenna Bednar, and Yan Chen)
“Optimal Team Composition for Tool Based Problem Solving” forthcoming Jour- nal of Economics and Management Strategy (with Jon Bendor).
The Model Thinker: What You Need to Know to Make Data Work for You. Basic Books, 2018
The Diversity Bonus. Princeton University Press and Andrew W. Mellon Foundation, 2017
Diversity and Complexity. Princeton University Press, 2010.
The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies - New Edition Princeton University Press; Revised ed. Edition 2008
Complex Adaptive Systems: An Introduction to Computational Models of Social Life. Scott E Page, John H Miller, Princeton University Press, 2007
Computational Models in Political Economy, Various Authors, MIT Press, 2003
TAGS: economics, management, agent-based modeling, networks, diversity, formal modeling, information diffusion, social choice theory, computational social science
My main research interest is the empirical and theoretical analysis of Social and Information Networks. I am particularly interested in understanding the mechanisms involved in network evolution, information diffusion, and interactions among people on the Web and in complex organization.
H. Peng, A. Nematzadeh, D.M. Romero, and E. Ferrara "Network Modularity Controls the Speed of Information Diffusion." Phys. Rev. E, 102, 052316, 2020.
D. Maldeniya, C. Budak, L. Robert, and D.M. Romero. "Herding a Deluge of Good Samaritans: How GitHub Projects Respond to Increased Attention." Proc. of The Web Conference (WWW), 2020.
V.G.V Vydiswaran, D.M. Romero, X. Zhao, D. Yu, I. Gomez-Lopez, J.X. Lu, B.E. Iott, A. Baylin, E.C. Jansen, P. Clarke, V.J. Berrocal, R. Goodspeed, T.C. Veinot. "Uncovering the relationship between food-related discussion on Twitter and neighborhood characteristics." Journal of the American Medical Informatics Association (JAMIA), 2019.
TAGS: information, dynamical systems, agent-based modeling, networks, formal modeling, information diffusion, social choice theory, computational social science
His research centers on the theory and application of dynamical systems: from economic systems in search of equilibrium, to political systems in search of optimal policies, ecosystems responding to human interactions, and especially to the dynamics of the spread of contagious diseases. His current research centers on the spread of crime, the initiation of teenage smoking, and health issues that affect SES. He was named the LSA Distinguished Senior Lecturer for 2007 and received the U-M Distinguished Faculty Achievement Award in 2012. He teaches calculus at the Ford School, including "algebraic aerobics." He received his PhD in mathematics from Northwestern University.
“An anthropologically based model of the impact of asymptomatic cases on the spread of Neisseria gonorrhoeae.” (with Ashley Hazel). Journal of the Royal Society Interface (2015) 12. [12 20150067; DOI: 10.1098/rsif.2015.0067. 25 March 2015]
“Complications With Complexity in Requirements.” (with John King). ACM Transactions on Management Information Systems. Special Issue on Complexity of Systems Evolution: Re- quirements Engineering Perspective. (2015) 5(3)
.“BACH and Progeny.” In: Exploring Complexity–Volume 1: Aha...That is Interesting! (J. Vasbinder, editor.) World Scientific Publishing, Singapore (2014) 110-118.
Kaplan, George A., Diez Roux, Ana V., Simon, Carl P., Galea, Sandro. Growing Inequality: Bridging Complex Systems, Population Health, and Health Disparities. Westphalia Press, an Imprint of the Policy Studies Organization, 2017.
Mathematics for Economists (with L. Blume). New York: W. W. Norton & Co. (1994) 930 pages.Answers Pamphlet for Mathematics for Economists (with L. Blume). New York: W.W. Norton &Co. (1995) 243 pages.
Translation of: Martinet, Jean. Singularities of Smooth Functions and Maps. Cambridge: Cam- bridge University Press. (1982) 270 pages.TAGS: public policy, mathematics, economics, dynamical systems, agent-based modeling, statistical and biological physics, formal modeling, mathematical biology,
My lab studies the mechanisms behind the structure, dynamics, and function of complex ecological networks, at ecological and evolutionary scales; including their resilience to biodiversity loss, biological invasions, climate change, and exploitation by humans. This research focuses on pollination networks, food webs and fisheries. I mainly use mathematical models and computational tools, but I also conduct field work to understand and predict the structure and function of pollination networks.
Specific areas of current research:
1. Pollination network ecology
2. Food web ecology and evolution
3. Application of food web theory to fisheries
Valdovinos, F.S. (2019) Mutualistic Networks: Moving closer to a predictive theory. Ecology Letters. doi: 10.1111/ele.13279 Ponisio, L.C., Valdovinos, F.S., Allhoff, K.T., Gaiarsa, M., Guimarães Jr., P.R., Hembry, D. H., Morrison, B., Gillespie, R. (2019)
A network perspective for community assembly. Frontiers in Ecology & Evolution https://doi.org/10.3389/fevo.2019.00103Baiser, B, Gravel, D, Cirtwill, A, Dunne, J.A., Fahimpour, A.K., Gilarranz L.J., Grochow, J.A., Li, D., Martinez, N.D., McGrew, A., Poisot, T., Romnuk, T.N., Stouffer, D.B., Trotta, L.B., Valdovinos, F.S., Williams, R.J., Wood, S.A., Yeakel, J.D. (2019).
Ecogeographical Rules and the Macroecology of Food Webs. Global Ecology and Biogeography DOI: 10.1111/geb.12925.Bland, S., Valdovinos, F.S., Hutchings, J.A., Kuparinen, A. (2019) The role of fish life histories in allometrically scaled food-web dynamics. Ecology and Evolution, 00:1–10. https://doi.org/10.1002/ece3.4996
TAGS: ecology and evolutionary biology, dynamical systems, agent-based modeling, networks, information diffusion, mathematical biology
Much of our work focuses on host-parasite coevolution both computationally using populations of self-replicating computer programs (sort of like computer viruses), and experimentally in the lab with bacteria and their viruses (bacteriophage). But that's not all! We're deeply interdisciplinary, and broadly interested in ecology and evolution.
We study host-parasite coevolution using a mixture of computational and microbial experiments. I treat computer systems as another experimental system, much like E. coli and Elephants are two living systems that can be studied in surprisingly similar ways.
Fortuna, M. A., Barbour, M. A., Zaman, L., Hall, A. R., Buckling, A., & Bascompte, J. (2019).Coevolutionary dynamics shape the structure of bacteria‐phage infection networks. Evolution, 73(5), 1001-1011.
Zaman, L. (2018, July). Investigating open-ended coevolution in digital organisms. In Artificial Life Conference Proceedings(pp. 258-259). One Rogers Street, Cambridge, MA 02142-1209 USA journals-info@ mit. edu: MIT Press.
Wiser, M. J., Zaman, L., Connelly, B. D., & Ofria, C. (2018, June). Threshold for cooperation on irregular spatial networks. In Artificial Life Conference Proceedings. MIT Press One Rogers Street, Cambridge, MA 02142-1209 USA journals-info@ mit. Edu.
TAGS: ecology and evolutionary biology, dynamical systems, agent-based modeling, formal modeling, information diffusion, mathematical biology, experimental complex systems
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