About

Maurizio Porfiri is an Institute Professor at New York University Tandon School of Engineering, holding tenured appointments in the Departments of Mechanical and Aerospace Engineering and Biomedical Engineering. He serves as the Director of the Center for Urban Science + Progress and the inaugural Director of the Urban Institute. Additionally, he is the Interim Chair of the Civil, Urban, and Environmental Engineering Department. Dr. Porfiri received his M.Sc. and Ph.D. degrees in Engineering Mechanics from Virginia Tech in 2000 and 2006, respectively, and holds a Laurea in Electrical Engineering with honors from Sapienza University of Rome, along with a dual Ph.D. in Theoretical and Applied Mechanics from Sapienza University of Rome and the University of Toulon. Since founding the Dynamical Systems Laboratory in 2006, he has been a faculty member at NYU Tandon, where he has contributed extensively to research on complex systems, with applications spanning mechanics, behavior, public health, and robotics. Recognized as a Fellow of the American Society of Mechanical Engineers and the IEEE, Dr. Porfiri has authored approximately 400 journal publications, including articles in prominent journals such as Nature, Nature Human Behaviour, and Physical Review Letters. His research has been featured in major media outlets, and he has received numerous awards, including the NSF CAREER award, the ASME Gary Anderson Early Achievement Award, and the Research Excellence Award from NYU Tandon. His work focuses on collective behavior, complex systems, network science, and urban science, contributing significantly to the understanding of dynamical systems and their applications in real-world contexts.

Research topics

• Artificial Intelligence
• Computer Science
• Management science
• Paleontology
• Cognitive science
• Natural resource economics
• Biology
• Business
• Environmental economics
• Data science
• Epistemology
• Human–computer interaction
• Environmental planning
• Ecology
• Evolutionary biology
• Engineering
• Psychology
• Mathematics
• Physics
• Mechanics
• Environmental science
• Geology
• Environmental resource management
• Economics

Selected publications

• Predicting the role of inequalities on human mobility patterns

  PNAS Nexus · 2026-01-01

  articleOpen accessSenior author

  Whether in search of better trade opportunities or escaping wars, humans have always been on the move. For almost a century, mathematical models of human mobility have been instrumental in the quantification of commuting patterns and migratory fluxes. Equity is a common premise of most of these mathematical models, such that living conditions and job opportunities are assumed to be equivalent across cities. Growing inequalities in modern urban economy and pressing effects of climate change significantly strain this premise. Here, we propose a mobility model that is aware of inequalities across cities in terms of living conditions and job opportunities. Comparing results with real datasets, we show that the proposed model outperforms the state-of-the-art in predicting migration patterns in South Sudan and commuting fluxes in the United States. This model paves the way to critical research on resilience and sustainability of urban systems.

  PublisherDOI

• Hydrodynamic entanglement in the abyss: Morphological adaptations of groups of E. <i>aspergillum</i>

  PNAS Nexus · 2026-05-18

  articleOpen accessSenior author

  Abstract Euplectella aspergillum is a deep-sea glass sponge that has attracted the interest of the scientific community for almost 150 years, for its surprising adaptations to the asperities of the abyss. The state-of-the-art on this organism focuses on specimens in isolation, but field observations question this premise. Footage from the abyss shows instances in which E. aspergillum live in bouquets comprising several organisms. Through high performance computing of the flow physics of E. aspergillum, we discover a complex hydrodynamic entanglement that favors downstream organisms at no cost to upstream ones. Such an interaction benefits the nutrition, reproduction, and resilience of the bouquet – the first instance of a hydrodynamic advantage that emerges due to purely passive interactions in a group.

  PublisherDOI

• Emergent patterns of crime distributions across major U.S. cities

  Cities · 2026-05-15

  articleSenior authorCorresponding
  PublisherDOI

• Bio-inspired density control of multi-agent swarms via leader-follower plasticity

  Automatica · 2026-03-13

  articleOpen accessSenior author

  The design of control systems for the spatial self-organization of mobile agents is an open challenge across several engineering domains, including swarm robotics and synthetic biology. Here, we propose a bio-inspired leader-follower solution, which is aware of energy constraints of mobile agents and is apt to deal with large swarms. Akin to many natural systems, control objectives are formulated for the entire collective, and leaders and followers are allowed to plastically switch their role in time. We frame a density control problem, modeling the agents’ population via a system of nonlinear partial differential equations. This approach allows for a compact description that inherently avoids the curse of dimensionality and improves analytical tractability. We derive analytical guarantees for the existence of desired steady-state solutions and their global stability for one-dimensional and higher-dimensional problems. We numerically validate our control methodology, offering support to the effectiveness, robustness, and versatility of our proposed bio-inspired control strategy.

  PublisherDOI

• Evaluating OCR performance for assistive technology: effects of walking speed, camera placement, and camera type

  Disability and Rehabilitation Assistive Technology · 2026-05-19

  article

  PURPOSE: Optical character recognition (OCR), a process that converts printed or handwritten text into machine-readable form, is widely used in assistive technology for people with blindness and low vision. Yet most evaluations rely on static datasets that do not reflect the challenges of mobile use. This study evaluated how OCR performance changes under static and walking conditions relevant to real-world navigation. METHODS: Static tests varied distance from 1-7 metres and viewing angle from 0°-75°. Dynamic tests examined the impact of motion by varying walking speed from 0.8 m/s to 1.8 m/s and compared head-mounted, shoulder-mounted, and handheld positions. We evaluated a smartphone and smart glasses, including the phone's main and ultra-wide cameras, across four OCR engines: Google Vision, PaddleOCR 3.0, EasyOCR, and Tesseract. Dynamic tests used PaddleOCR 3.0. Accuracy was computed at the character level using the Levenshtein ratio against manually defined ground truth. RESULTS: Recognition accuracy declined with increased walking speed and wider viewing angles. Google Vision achieved the highest overall accuracy, with PaddleOCR close behind as the strongest open-source alternative. Across devices, the phone's main camera achieved the highest accuracy, and a shoulder-mounted placement yielded the highest average among body positions; however, differences among shoulder, head, and hand were not statistically significant. CONCLUSION: OCR performance depends on the recognition engine, camera hardware, field of view, device placement, and user motion. OCR systems for navigation should be evaluated under dynamic, mobility-relevant conditions rather than static images alone and designed to balance coverage, recognition accuracy, and practical deployment.

  PublisherDOI

• Inference of the size of nonlinear network systems from perceptible dynamics

  Chaos An Interdisciplinary Journal of Nonlinear Science · 2026-02-01

  articleSenior author

  Network dynamical systems are ubiquitous in science and engineering. The most basic property of a network dynamical system is its size, which, for scalar dynamics, corresponds to the number of nodes. For linear network systems, recent studies have developed reliable tools for inferring the size of the system from perceptible dynamics (measurements of one or some of the network nodes) across multiple experiments. Here, we extend these tools to nonlinear network systems by putting forward a model-agnostic approach that combines clustering techniques, the use of detection matrices, and spectral analysis. The theoretical premise of the algorithm is that, under mild assumptions, the variation between the dynamics of some nodes across multiple measurements can be used to bound the variation between the dynamics of all nodes across the same measurements. By applying clustering techniques on perceptible dynamics, we identify nearby measurements, about which the variational dynamics are approximately linear and the use of the detection matrix is valid. From the spectrum of the detection matrix, we infer its rank, which corresponds to the size of the nonlinear network system. We demonstrate our approach via numerical experiments on different nonlinear network systems, including different types of hypergraphs. Whether nonlinearity comes from individual dynamics of the nodes or the interactions among them, it is rarely a feature that one can dismiss. Our work paves the way to infer the size of a nonlinear network system when governing equations are unknown and only limited data are accessible.

  PublisherDOI

• Dynamic stabilization of a mechanical oscillator in the absence of any stable feature

  Nature Communications · 2026-03-10

  articleOpen accessSenior author

  How and why base vibration can stabilize an inverted pendulum has puzzled the scientific community for decades, until the work on dynamic stabilization by Pyotr Kapitza pointed at the alternation between unstable and stable modes as a pathway to stability. We report the discovery of a mechanical oscillator that switches between two unstable modes, has an unstable average, and, yet, can be dynamically stabilized. Our system is governed by a modified Meissner's model - a one-degree-of-freedom oscillator where both stiffness and damping are modulated through a square wave to switch between positive and negative values. We theoretically prove the existence of compact antiresonance windows and provide experimental evidence through a cantilever beam oscillator subject to magnetic and aerodynamic forcing. The prospect of dynamic stabilization in the absence of any stable feature has vast implications from network dynamical systems, to structural mechanics and robotics.

  PublisherOA PDFDOI

• Permanent Relocation Into and Out of Areas Exposed to Natural Hazards: a Multidisciplinary Review of the Literature

  2025-03-27 · 2 citations

  reviewOpen access

  This article examines the long-term impacts of natural hazards caused by patterns of relocation into and out of hazard-exposed communities. We address two main questions: (1) what factors influence permanent relocation decisions in hazard-exposed communities? (2) What are the effects of relocation on the socio-economic and demographic characteristics of these communities? To answer these questions, we review studies on theoretical frameworks, empirical analyses, and simulation-based models. Relocation outcomes result from a complex interplay of household characteristics (e.g., wealth, risk perception, place attachment), community characteristics (e.g., economic opportunities, essential services), and government interventions (e.g., collective risk-reduction measures). The reviewed studies report mixed findings on demographic and socio-economic changes associated with permanent relocation. Large-scale analyses suggest that natural hazards have limited effects on pre-existing population trends, while more granular studies show that specific hazards—such as coastal flooding and sea level rise—can alter local dynamics. Effects on communities socio-economic characteristics also vary. Some communities experience post-hazard gentrification, while others face deepened vulnerabilities, with declining property values trapping residents in high-risk areas. We further review simulation-based models that examine hazard-related relocation and the socio-economic changes it can produce. These models often focus on specific aspects, such as individual decision-making, housing markets, or recovery patterns, without integrating all relevant factors. Finally, we identify key research gaps, including the need for more long-term studies on socio-economic changes in hazard-exposed communities, and greater focus on chronic, low-intensity hazards like tidal flooding.

  PublisherDOI

• Leader–Follower Density Control of Spatial Dynamics in Large-Scale Multiagent Systems

  IEEE Transactions on Automatic Control · 2025-04-30 · 7 citations

  article

  We address the problem of controlling the density of a large ensemble of follower agents by acting on a group of leader agents that interact with them. Using coupled partial integro-differential equations to describe leader and follower density dynamics, we establish feasibility conditions and develop two control architectures ensuring global stability. The first employs feed-forward control on the followers' and a feedback on the leaders' density. The second implements a dual feedback loop through a reference-governor that adapts the leaders' density based on both populations' measurements. Our methods, initially developed in a one-dimensional setting, are extended to multi-dimensional cases, and validated through numerical simulations for representative control applications, both for groups of infinite and finite size.

  PublisherDOI

• A machine learning approach to predict wrist posture in telerehabilitation with haptic devices

  Mechatronics · 2025-11-08

  articleSenior author
  PublisherDOI

Recent grants

• Robotics may help unravel the biological determinants of substance use disorders: studies in zebrafish

  NIH · $173k · 2017–2019

• NIH Grant R21AA021523

  NIH · $175k · 2016

• How and Why Fish School: An Information-theoretic Analysis of Coordinated Swimming

  NSF · $484k · 2019–2024

• EAGER: Reliable Data from Heterogeneous Groups of Citizen Scientists

  NSF · $100k · 2016–2019

• NIH Grant R21AA02152301A1

  NIH · $232k · 2015

Frequent coauthors

• Salvatore Grimaldi

  Università degli Studi della Tuscia

  123 shared

• Flavia Tauro

  Università degli Studi della Tuscia

  106 shared

• Sean D. Peterson

  University of Waterloo

  87 shared

• Alessandro Rizzo

  Polytechnic University of Turin

  85 shared

• Nicole Abaid

  Virginia Tech

  79 shared

• Matteo Aureli

  University of Nevada, Reno

  78 shared

• Youngsu Cha

  Korea University

  75 shared

• Sachit Butail

  Northern Illinois University

  63 shared

Education

• Ph.D., Engineering Mechanics

  Virginia Polytechnic Institute and State University

  2006

• Ph.D.

  Sapienza University of Rome

  2005

Awards & honors

• Fellow of the American Society of Mechanical Engineers (ASME…
• Fellow of the Institute of Electrical and Electronic Enginee…
• ASME C.D. Mote, Jr. Early Career Award (2015)
• Invitee of Japan-America Frontiers of Engineering Symposium,…
• Jacobs Excellence in Education Award (2014)