About

Raissa M. D'Souza is a Professor and Associate Dean for Research in the Department of Computer Science at UC Davis. Her research focuses on network science, complex systems, statistical physics, and applied mathematics. She employs tools from statistical physics and applied mathematics to develop mathematical models that explore the interplay between the structure and function of networks. Her work particularly emphasizes the abrupt onset of large-scale connectivity in networks, network synchronization behaviors, and models of cascading failure. The principles derived from her research provide insights into the behaviors of real-world networks such as infrastructure and social networks, and she investigates small interventions to control the self-organizing and collective behaviors of these systems. D'Souza collaborates broadly with faculty within the college and across disciplines including physics, statistics, political science, and the Primate Center.

Selected publications

• What does the tree of life look like as it grows? Evolution and the multifractality of time

  Journal of Theoretical Biology · 2025-04-11 · 1 citations

  articleOpen accessSenior author

  • We develop a mathematical model of the dynamic tree of life from three principles of phylogeny: nestedness, duality, and randomness. • The resulting structure resembles a Cantor dust, with each branch a distinct fractal, making the whole system multifractal. • Since branch lengths represent time, the length of a time interval depends on the observer's form, so that time is also multifractal. By unifying three foundational principles of modern biology, we develop a mathematical framework to analyze the growing tree of life. Contrary to the static case, where the analogy between phylogenetic trees and the tree that grows in soil is drawn, our framework shows that the living tree of life is analogous to a Cantor dust where each branch is a distinct fractal curve. The system as a whole is therefore multifractal in the sense that it consists of many unique fractals. The three foundational principles for the mathematical framework are that phylogeny is nested, phylogeny is dualistic (i.e., transitive between singularities and populations), and phylogeny is stochastic. Integrating these three principles, we model the dynamic (i.e., living ) tree of life as a random iterated function system that generates unique convexly related sequences of branching random variables (visualized in Animation 1 ). The multifractal nature of this dynamic tree of life implies that, for any two living entities, the time interval from their last common ancestor to the present moment is a distinct fractal curve for each. Thus, the length of a time interval along each distinct branch is unique, so that time is also multifractal and not an ultrametric on the tree of life.

  PublisherDOI

• Coupled catastrophes in systems with bidirectional feedback

  Chaos An Interdisciplinary Journal of Nonlinear Science · 2025-11-01

  article

  Catastrophes are present across many disciplines, ranging from the extinction of populations in ecosystems to the collapse of prices in financial systems. Here, we focus on how interactions between systems influence these catastrophes. Specifically, we study two bidirectionally coupled sub-systems-each of which possesses an S-shaped bifurcation curve with saddle-node bifurcations-and explore how interactions between them can lead to simultaneous bifurcations. There are four types of such coupled catastrophes: synchronization, anti-synchronization, consensus, and anti-consensus. Which of these behaviors manifests depends both on the intrinsic dynamics of the subsystems and ways in which they are coupled. In general, there are three possible coupling classes: cooperation, competition, and predation. We develop an analytic/graphical methodology to determine and visualize the locus of the coupled catastrophes in parameter space, and we show which classes of couplings support different types of coupled catastrophes. Finally, we discuss several potential applications areas from distinct domains.

  PublisherDOI

• Network and Phase Symmetries Reveal That Amplitude Dynamics Stabilize Decoupled Oscillator Clusters

  Entropy · 2025-05-07

  articleOpen accessSenior author

  Oscillator networks display intricate synchronization patterns. Determining their stability typically requires incorporating the symmetries of the network coupling. Going beyond analyses that appeal only to a network's automorphism group, we explore synchronization patterns that emerge from the phase-shift invariance of the dynamical equations and symmetries in the nodes. We show that these nonstructural symmetries simplify stability calculations. We analyze a ring-network of phase-amplitude oscillators that exhibits a "decoupled" state in which physically-coupled nodes appear to act independently due to emergent cancellations in the equations of dynamical evolution. We establish that this state can be linearly stable for a ring of phase-amplitude oscillators, but not for a ring of phase-only oscillators that otherwise require explicit long-range, nonpairwise, or nonphase coupling. In short, amplitude-phase interactions are key to stable synchronization at a distance.

  PublisherOA PDFDOI

• Multiscale Field Theory for Network Flows

  Physical Review X · 2025-05-07 · 1 citations

  articleOpen accessSenior author

  Network flows are pervasive, including the movement of people, transportation of goods, transmission of energy, and dissemination of information; they occur on a range of empirical interconnected systems, from designed infrastructure to naturally evolved networks. Despite the broad spectrum of applications, because of their domain-specific nature and the inherent analytic complexity, a comprehensive theory of network flows is lacking. We introduce a unifying treatment for network flows that considers the fundamental properties of packet symmetries, conservation laws, and routing strategies. For example, electrons in power grids possess interchangeability symmetry, unlike packages sent by postal mail, which are distinguishable. Likewise, packets can be conserved, such as cars in road networks, or dissipated, such as Internet packets that time out. We introduce a hierarchy of analytical field-theoretic approaches to capture the different scales of complexity required. Mean-field analysis uncovers the nature of the transition through which flow becomes unsustainable upon unchecked growth of demand. Mesoscopic field theory accurately accounts for complicated network structures, packet symmetries, and conservation laws and yet is capable of admitting closed-form solutions. Finally, the full-scale field theory allows us to study routing strategies ranging from random diffusion to shortest path. Our theoretical results indicate that flow bottlenecks tend to be near sources for interchangeable packets and near sinks for distinguishable ones, and that dissipation hinders the maximum sustainable throughput for interchangeable packets but can enhance throughput for distinguishable packets. Finally, we showcase the flexibility of our multiscale theory by applying it in two distinct domains of road networks and the neuronal network. Our work paves the way for a more unifying and comprehensive theory of network flows.

  PublisherOA PDFDOI

• Unified framework for hybrid percolation transitions based on microscopic dynamics

  Chaos Solitons & Fractals · 2024-05-21 · 8 citations

  article
  PublisherDOI

• What you have, not who you know: food-enhanced social capital and changes in social behavioural relationships in a non-human primate

  Royal Society Open Science · 2024-01-01 · 3 citations

  articleOpen access

  Social network position in non-human primates has far-reaching fitness consequences. Critically, social networks are both heterogeneous and dynamic, meaning an individual's current network position is likely to change due to both intrinsic and extrinsic factors. However, our understanding of the drivers of changes in social network position is largely confined to opportunistic studies. Experimental research on the consequences of in situ, controlled network perturbations is limited. Here we conducted a food-based experiment in rhesus macaques to assess whether allowing an individual the ability to provide high-quality food to her group changed her social behavioural relationships. We considered both her social network position across five behavioural networks, as well as her dominance and kin interactions. We found that gaining control over a preferential food resource had far-reaching social consequences. There was an increase in both submission and aggression centrality and changes in the socio-demographic characteristics of her agonistic interaction partners. Further, we found that her grooming balance shifted in her favour as she received more grooming than she gave. Together, these results provide a novel, preliminary insight into how in situ , experimental manipulations can modify social network position and point to broader network-level shifts in both social capital and social power.

  PublisherDOI

• Author response for "What you have, not who you know: food-enhanced social capital and changes in social behavioural relationships in a non-human primate"

  2023-12-06

  peer-review
  PublisherDOI

• Consensus Formation Among Mobile Agents in Networks of Heterogeneous Interaction Venues

  arXiv (Cornell University) · 2023-10-13 · 1 citations

  preprintOpen accessSenior author

  Exploring the collective behavior of interacting entities is of great interest and importance. Rather than focusing on static and uniform connections, we examine the co-evolution of diverse mobile agents experiencing varying interactions across both space and time. Analogous to the social dynamics of intrinsically diverse individuals who navigate between and interact within various physical or digital locations, agents in our model traverse a complex network of heterogeneous environments and engage with everyone they encounter. The precise nature of agents internal dynamics and the various interactions that nodes induce are left unspecified and can be tailored to suit the requirements of individual applications. We derive effective dynamical equations for agent states which are instrumental in investigating thresholds of consensus, devising effective attack strategies to hinder coherence, and designing optimal network structures with inherent node variations in mind. We demonstrate that agent cohesion can be promoted by increasing agent density, introducing network heterogeneity, and intelligently designing the network structure, aligning node degrees with the corresponding interaction strengths they facilitate. Our findings are applied to two distinct scenarios: the synchronization of brain activities between interacting individuals, as observed in recent collective MRI scans, and the emergence of consensus in a cusp catastrophe model of opinion dynamics.

  PublisherOA PDFDOI

• R notebook of code used for analyses from What you have, not who you know: food-enhanced social capital and changes in social behavioural relationships in a non-human primate

  Figshare · 2023-01-01

  datasetOpen access

  Social network position in non-human primates has far-reaching fitness consequences. Critically, social networks are both heterogeneous and dynamic, meaning an individual's current network position is likely to change due to both intrinsic and extrinsic factors. However, our understanding of the drivers of changes in social network position is largely confined to opportunistic studies. Experimental research on the consequences of <i>in situ,</i> controlled network perturbations is limited. Here we conducted a food-based experiment in rhesus macaques to assess whether allowing an individual the ability to provide high-quality food to her group changed her social behavioural relationships. We considered both her social network position across five behavioural networks, as well as her dominance and kin interactions. We found that gaining control over a preferential food resource had far-reaching social consequences. There was an increase in both submission and aggression centrality and changes in the socio-demographic characteristics of her agonistic interaction partners. Further, we found that her grooming balance shifted in her favour as she received more grooming than she gave. Together, these results provide a novel, preliminary insight into how <i>in situ</i>, experimental manipulations can modify social network position and point to broader network-level shifts in both social capital and social power.

  PublisherDOI

• Controlling complex networks with complex nodes

  Nature Reviews Physics · 2023-03-24 · 119 citations

  review1st authorCorresponding
  PublisherDOI

Awards & honors

• Raissa D’Souza Receives Two Honors from the Network Science…
• Patrice Koehl and Raissa D'Souza Win 2017 College of Enginee…