About

Jean Carlson is a Physics Professor and the Group Head at the Complex Systems group at the University of California, Santa Barbara (UCSB). She leads research efforts in the field of complex systems, focusing on interdisciplinary approaches that integrate physics with biology, neuroscience, and other scientific domains. Her group includes graduate and undergraduate students working on topics such as network dynamics, sensorimotor integration, and the resilience of biological systems. Carlson collaborates with faculty across various departments and institutions, including experts in molecular biology, neuroscience, physics, and applied mathematics, reflecting a broad and integrative research agenda. The group also maintains strong connections with postdoctoral researchers and alumni who have gone on to prominent academic and research positions, indicating a vibrant and productive research environment under her leadership.

Research topics

• Computer Science
• Biology
• Psychology
• Artificial Intelligence
• Data science
• Zoology
• Paleontology
• Engineering
• Biochemistry
• Evolutionary biology
• Cognitive science
• Microbiology
• Bioinformatics
• Management science
• Genetics
• Human–computer interaction
• Endocrinology
• Epistemology
• Computational biology
• Neuroscience
• Ecology

Selected publications

• Forecasting and decisions in the birth-death-suppression Markov model for wildfires

  Physical review. E · 2025-02-27 · 2 citations

  articleSenior author

  As changing climates transform the landscape of wildfire management and suppression, agencies are faced with difficult resource allocation decisions. We analyze tradeoffs in temporal resource allocation using a simple but robust Markov model of a wildfire under suppression: the birth-death-suppression process. Though the model is not spatial, its stochastic nature and rich temporal structure make it broadly applicable in describing the dynamic evolution of a fire including ignition, the effect of adverse conditions, and the effect of external suppression. With strong analytical and numerical control of the probabilities of outcomes, we construct classes of processes which analogize common wildfire suppression scenarios and determine aspects of optimal suppression allocations. We model problems which include resource management in changing conditions, the effect of resource mobilization delay, and allocation under uncertainty about future events. Our results are consistent with modern resource management and suppression practices in wildland fire.

  PublisherDOI

• Divide (evenly) and conquer (quickly): Spatial exploration behaviors predict navigational learning and differ by sex

  Cognition · 2025-04-21 · 2 citations

  articleOpen access

  The ability to learn new environments is a foundational human skill, yet we know little about how exploration behaviors shape spatial learning. Here, we investigated the relationships between exploration behaviors and spatial memory in healthy young adults, and further related performance to other measures of individual differences. In the present study, 100 healthy young adults (ages 18–37) freely explored a maze in a virtual desktop environment to learn the locations of 9 objects. Participants then navigated from one object to another without feedback, and their accuracy and path efficiency were determined. Interestingly, participant accuracy ranged from near 0 % to 100 %. Correlations and principal component regression revealed that evenness of exploration (i.e., visiting all locations with a similar frequency) and how quickly all objects were found during exploration were related to performance. Indeed, differences in performance become apparent by the time participants found the 6th object (within the first 50 moves), emphasizing the importance of exploration quality over exploration quantity . Perspective taking ability and video game experience were also related to performance. Critically, we found no correlations between performance on matched pairs of active-passive exploration paths, suggesting that experiencing a “good” exploration path does not lead to better performance; instead, the path is more likely a reflection of the navigator's ability. Sex differences were observed, however, a serial mediation analysis revealed that even exploration had a greater explanatory effect on those sex differences compared to video game experience. Our results indicate that exploration behaviors predict navigational performance and highlight the importance of moment-to-moment behaviors exhibited during exploration and learning. • 100 healthy young adults explored a virtual maze and were tested on their knowledge • Even exploration (i.e., consistent visits to all areas) and finding objects quickly were correlated with better performance • Perspective taking and video game use were associated with performance • Exploration path is reflection of ability, rather than causing better performance • Sex differences mediated by even exploration, not video games alone

  PublisherDOI

• Deep Learning Classification of Prostate Cancer Using MRI Histopathologic Data

  Radiology Imaging Cancer · 2025-09-01 · 1 citations

  articleOpen accessSenior author

  This in silico study demonstrates the feasibility of MRI histopathology for prostate cancer detection and identifies optimal imaging parameters to guide clinical acquisition.

  PublisherDOI

• Forecasting and decisions in the birth-death-suppression Markov model for wildfires

  arXiv (Cornell University) · 2024-09-12

  preprintOpen accessSenior author

  As changing climates transform the landscape of wildfire management and suppression, agencies are faced with difficult resource allocation decisions. We analyze trade-offs in temporal resource allocation using a simple but robust Markov model of a wildfire under suppression: the birth-death-suppression process. Though the model is not spatial, its stochastic nature and rich temporal structure make it broadly applicable in describing the dynamic evolution of a fire including ignition, the effect of adverse conditions, and the effect of external suppression. With strong analytical and numerical control of the probabilities of outcomes, we construct classes of processes which analogize common wildfire suppression scenarios and determine aspects of optimal suppression allocations. We model problems which include resource management in changing conditions, the effect of resource mobilization delay, and allocation under uncertainty about future events. Our results are consistent with modern resource management and suppression practices in wildland fire.

  PublisherOA PDFDOI

• Birth-death-suppression Markov process and wildfires

  Physical review. E · 2024-01-11 · 1 citations

  articleSenior author

  Birth and death Markov processes can model stochastic physical systems from percolation to disease spread and, in particular, wildfires. We introduce and analyze a birth-death-suppression Markov process as a model of controlled culling of an abstract, dynamic population. Using analytic techniques, we characterize the probabilities and timescales of outcomes like absorption at zero (extinguishment) and the probability of the cumulative population (burned area) reaching a given size. The latter requires control over the embedded Markov chain: this discrete process is solved using the Pollazcek orthogonal polynomials, a deformation of the Gegenbauer/ultraspherical polynomials. This allows analysis of processes with bounded cumulative population, corresponding to finite burnable substrate in the wildfire interpretation, with probabilities represented as spectral integrals. This technology is developed to lay the foundations for a dynamic decision support framework. We devise real-time risk metrics and suggest future directions for determining optimal suppression strategies, including multievent resource allocation problems and potential applications for reinforcement learning.

  PublisherDOI

• Birth-death-suppression Markov process and wildfires

  arXiv (Cornell University) · 2023-07-21

  preprintOpen accessSenior author

  Birth and death Markov processes can model stochastic physical systems from percolation to disease spread and, in particular, wildfires. We introduce and analyze a birth-death-suppression Markov process as a model of controlled culling of an abstract, dynamic population. Using analytic techniques, we characterize the probabilities and timescales of outcomes like absorption at zero (extinguishment) and the probability of the cumulative population (burned area) reaching a given size. The latter requires control over the embedded Markov chain: this discrete process is solved using the Pollazcek orthogonal polynomials, a deformation of the Gegenbauer/ultraspherical polynomials. This allows analysis of processes with bounded cumulative population, corresponding to finite burnable substrate in the wildfire interpretation, with probabilities represented as spectral integrals. This technology is developed in order to lay the foundations for a dynamic decision support framework. We devise real-time risk metrics and suggest future directions for determining optimal suppression strategies, including multi-event resource allocation problems and potential applications for reinforcement learning.

  PublisherOA PDFDOI

• A symbiotic physical niche in Drosophila melanogaster regulates stable association of a multi-species gut microbiota

  Nature Communications · 2023 · 75 citations

  • Biology
  • Microbiology
  • Zoology

  The gut is continuously invaded by diverse bacteria from the diet and the environment, yet microbiome composition is relatively stable over time for host species ranging from mammals to insects, suggesting host-specific factors may selectively maintain key species of bacteria. To investigate host specificity, we used gnotobiotic Drosophila, microbial pulse-chase protocols, and microscopy to investigate the stability of different strains of bacteria in the fly gut. We show that a host-constructed physical niche in the foregut selectively binds bacteria with strain-level specificity, stabilizing their colonization. Primary colonizers saturate the niche and exclude secondary colonizers of the same strain, but initial colonization by Lactobacillus species physically remodels the niche through production of a glycan-rich secretion to favor secondary colonization by unrelated commensals in the Acetobacter genus. Our results provide a mechanistic framework for understanding the establishment and stability of a multi-species intestinal microbiome.

  PublisherOA PDFDOI

• Stochastic microbiome assembly depends on context

  Proceedings of the National Academy of Sciences · 2022 · 98 citations

  • Computer Science
  • Computational biology
  • Computer Science

  , interactions between bacteria can affect the microbiome assembly process, contributing to a baseline level of microbiome variability even among isogenic organisms that are identically reared, housed, and fed. In germ-free flies fed known combinations of bacterial species, we find that some species colonize more frequently than others even when fed at the same high concentration. We develop an ecological technique that infers the presence of interactions between bacterial species based on their colonization odds in different contexts, requiring only presence/absence data from two-species experiments. We use a progressive sequence of probabilistic models, in which the colonization of each bacterial species is treated as an independent stochastic process, to reproduce the empirical distributions of colonization outcomes across experiments. We find that incorporating context-dependent interactions substantially improves the performance of the models. Stochastic, context-dependent microbiome assembly underlies clinical therapies like fecal microbiota transplantation and probiotic administration and should inform the design of synthetic fecal transplants and dosing regimes.

  PublisherDOI

• Variation and Variability in Drosophila Grooming Behavior

  Frontiers in Behavioral Neuroscience · 2022-01-11 · 13 citations

  articleOpen access

  Behavioral differences can be observed between species or populations (variation) or between individuals in a genetically similar population (variability). Here, we investigate genetic differences as a possible source of variation and variability in Drosophila grooming. Grooming confers survival and social benefits. Grooming features of five Drosophila species exposed to a dust irritant were analyzed. Aspects of grooming behavior, such as anterior to posterior progression, were conserved between and within species. However, significant differences in activity levels, proportion of time spent in different cleaning movements, and grooming syntax were identified between species. All species tested showed individual variability in the order and duration of action sequences. Genetic diversity was not found to correlate with grooming variability within a species: melanogaster flies bred to increase or decrease genetic heterogeneity exhibited similar variability in grooming syntax. Individual flies observed on consecutive days also showed grooming sequence variability. Standardization of sensory input using optogenetics reduced but did not eliminate this variability. In aggregate, these data suggest that sequence variability may be a conserved feature of grooming behavior itself. These results also demonstrate that large genetic differences result in distinguishable grooming phenotypes (variation), but that genetic heterogeneity within a population does not necessarily correspond to an increase in the range of grooming behavior (variability).

  PublisherOA PDFDOI

• MR method for measuring microscopic histologic soft tissue textures

  Magnetic Resonance in Medicine · 2021-02-19 · 3 citations

  article

  PURPOSE: Provide a direct, non-invasive diagnostic measure of microscopic tissue texture in the size scale between tens of microns and the much larger scale measurable by clinical imaging. This paper presents a method and data demonstrating the ability to measure these microscopic pathologic tissue textures (histology) in the presence of subject motion in an MR scanner. This size range is vital to diagnosing a wide range of diseases. THEORY/METHODS: MR micro-Texture (MRµT) resolves these textures by a combination of measuring a targeted set of k-values to characterize texture-as in diffraction analysis of materials, performing a selective internal excitation to isolate a volume of interest (VOI), applying a high k-value phase encode to the excited spins in the VOI, and acquiring each individual k-value data point in a single excitation-providing motion immunity and extended acquisition time for maximizing signal-to-noise ratio. Additional k-value measurements from the same tissue can be made to characterize the tissue texture in the VOI-there is no need for these additional measurements to be spatially coherent as there is no image to be reconstructed. This method was applied to phantoms and tissue specimens including human prostate tissue. RESULTS: Data demonstrating resolution <50 µm, motion immunity, and clearly differentiating between normal and cancerous tissue textures are presented. CONCLUSION: The data reveal textural differences not resolvable by standard MR imaging. As MRµT is a pulse sequence, it is directly translatable to MRI scanners currently in clinical practice to meet the need for further improvement in cancer imaging.

  PublisherDOI

Recent grants

• Friction, Fatigue and Failure: a Multiscale Approach Linking Physics, Fabrication and Geophysical Phenomena

  NSF · $270k · 2006–2011

• Collaborative Research: Statistical Physics of Fault Behavior - Dynamic Friction, Strain Localization, Comminution, Heat Transfer, and Compaction

  NSF · $230k · 2014–2018

Frequent coauthors

• John C. Doyle

  Dublin City University

  33 shared

• Ahmed Elbanna

  University of Illinois System

  26 shared

• Eric W. Jones

  Simon Fraser University

  22 shared

• Chantal Nguyen

  21 shared

• Scott T. Grafton

  Hologic (Germany)

  19 shared

• Danielle S. Bassett

  McGill University

  19 shared

• Max A. Moritz

  19 shared

• Marco Morais

  University of California, Santa Barbara

  18 shared

Labs

• Complex SystemsPI

  This lab focuses on the study of complex systems, including network dynamics, microbiome network dynamics, and sensorimotor integration.