I'm Jordan Kemp, a complex systems scientist at Oxford's Institute for New Economic Thinking (INET), working in the Complexity Economics group. I research how the unpredictable world we perceive shapes our lives. I think about how our physical, natural and social environments influence our decisions drive patterns of inequality, collective action, and social change.
My research is all about connecting science and society. By using the tools of physics and theoretical ecology, I intend to help rethink how we study and apply data. This perspective isn't just academic; it's about understanding the forces that shape our everyday lives to rethink the design paradigms of both policy and our built environments.
Feel free to explore my work, and please get in touch if you'd like to discuss any of these ideas!
Survival Under Uncertainty
optimization, information, organization
Studying how intelligent beings adapt their life-course strategies under uncertainty to long term payoffs, life expectancy, environmental uncertainy, and more. I then study decisions among individuals affect long term inequality and social mobility. I also study how collectives balance decide to share information or resources, and more specifically, how structural features of knowledge drive collaboration and inequality across disciplines.
Demography and Urban Dynamics
spatial analyses, complexity, prediction
Recent advancements in information theory and statistical modeling provide new tools to understand the social and physical determinants of socioeconomic outcomes. In this work, we use information to disentangle confounding effects of location, demographic, and educational variables on income over life courses. I am also interested in developing new models of wealth dynamics, urban mobility, and the resilience of small businesses.
Projecting the Green Transition
ABMs, forecasting, network reconstruction
Climate change is here, but the green energy transition is not far behind. To prepare, we must diagnose the transitions' speed, ask how should economies should prepare for labor and infrastructure changes, and how will the global supply network change and be changed by this transition. At INET, I'm working on several projects to answer these questions
Originally trained in physics, I now take an interdisciplinary approach, combining methods from statistical physics (e.g. stochastic nonequilibrium processes, phase transitions), theoretical ecology (e.g. selection, multiplicative growth), and the cognitive and learning sciences (e.g. perception, information theory, machine learning). Generally, I'm interested in how statistical information can be used to understand not only uncertain behavior (as in my previous work), but also as an emerging tool for uncovering relationships in data--influencing everything from urban dynamics and demographic trends to small business resilience. Examples of some of my prior projects are found here.
At INET, I'm actively involved in projects that predict new technology adoption, and that reconstruct and study global supply chains---topics that are critical for guiding more resilient policies as the world undergoes the green energy transition.
I completed my PhD in physics as an NSF Graduate Research Fellow at the University of Chicago Department of Physics. I studied in the Urban Science Lab under the advice of Luís Bettencourt and Arvind Murugan. In the past, I have conducted experimental research in both quantum computing and simulation using neutral cold atoms with the Bernien Lab at UChicago, and in gravitational wave detection with Rana Adhikari and the LIGO Group at Caltech
Ultimately, my goal is to bridge the gap between research and real-world impact. By uncovering the hidden patterns in complex systems, I aim to contribute to policies and practices that promote equitable, resilient communities. I welcome collaboration and discussion with fellow researchers, policy makers, and community advocates who share an interest in harnessing science to drive positive change.