Speculative ecoacoustic composition systems: listening to insects through music

August2025School of Humanities, Arts, and Social SciencesOngoing insect decline is of critical concern for all species, since insect diversity and resilience are critical to ecosystem function. If we are to rely on anthropocentric rationale alone, this should be ample evidence to pay more attention to insects. However, humans in many western societies have become disconnected from insects, exacerbated by a socialized narrative of fear, avoidance, and exclusion. Parallel to our deteriorating relations with insects there has been a decline in our practices of listening to our environments. This research considers how listening to insects might change the way we perceive and value them – which in turn informs how we interact with and affect them. Composer David Dunn has posited that the production and reception of music can facilitate a connection with beyond-humans through the ‘fabric of mind’ that connects living beings through sound. In this dissertation, I present methods for listening to insects through percussion, electronic, and spatialized music. My focus is on ants and their associates, whose complex societies have tremendous ecological impacts globally. Ants sonically communicate through the architectures in and on which they live, yet there has been very little scientific research on the topic. I posit that we can listen to ants’ mindedness through their aural architectures: the material infrastructure through which they communicate, and by which their sonic agency and social cohesion is realized. Building on Dunn’s artistic works, I present methods for the realization of speculative ecoacoustic composition systems that interact with the sound of insects and our shared environments through recording, playback, and processing. I experiment with composition methods for electronic music, percussion and spatial sound to challenge conceptions of what we can hear, how we listen, and our relations to insects. Percussion and the sounds of our environments are both pushed aside and often labeled “noise” or “experimental” in traditional Western music institutions, yet they are at the same time familiar and embodied, and prompt expansion of what we listen to. My research experiments in bringing these sounds to a broader public through the development and implementation of formats such as performance, public sound installation, in-situ experiences in the field, and web-based media. Through these formats, the work intends to prompt auralization in listeners – composer Pauline Oliveros’ concept of ‘hearing or sounding in the mind,’ through an awareness of cryptic insect sounds in our environments. Building on historical precedents of active listening that empowered social change, and Donna Haraway’s concept of committed sympoietic relationships with beyond-human, I posit that listening through music to insects can foster sonic sympoiesis where we live, sustained by auralization of insect sound in the mind. It is through this affective listening and auralization that we can shift our relations with and challenge our assumptions about insects.Ph

Plasticity in molecular crystal cyclotetramethylene tetranitramine (β-hmx)

May2025School of EngineeringMolecular crystal cyclotetramethylene tetranitramine (β-HMX) is the active ingredient in widely used plastic bonded explosives. Plasticity is believed to be essential for its reaction initiation and detonation. To explore the energetic cost associated with the relative gliding of crystal planes, we calculate γ-surfaces for the most active glide planes in β-HMX, the (101) plane and the (011) plane, with pressure up to 15 GPa. Stable stacking faults are observed on both glide planes, suggesting dislocation disassociation into partials takes place. Furthermore, the γ-surface of the (101) plane indicates twinning on the (101) plane. With increasing pressure, the values of γ-surfaces increase drastically, however, the topography of γ-surfaces remains the same. Homogeneous dislocation nucleation was found to be a relevant mechanism of plastic deformation in β-HMX. In this work, we conduct atomistic simulations to investigate the conditions under which dislocations nucleate homogeneously in the (101) and (011) planes at pressures up to 20 GPa. Critical resolved shear stresses (CRSS) for dislocation nucleation are reported. The competition between the homogeneous nucleation and other mechanisms of plastic deformation shows that homogeneous nucleation is less likely to happen at pressures above 5 GPa, while at pressures below this threshold, homogeneous nucleation competes with shear localization. Further, molecular dynamics simulations are performed to evaluate the dislocation velocity vs. resolved shear stress relation at pressures up to 20 GPa in several slip systems, which helps defining the strain rate sensitivity of the crystal. Based on this data and data from the literature, we establish a mechanism-based constitutive model for β-HMX crystals. The model captures the thermally activated and dislocation drag regimes for dislocation motion and, more importantly, the model is strongly pressure-dependent, and rate sensitive. An isotropic version of the model based of Reuss averaging is also presented. This model has the potential to be broadly applicable in the continuum modeling of HMX. Further we study conditions under which plastic deformation in HMX becomes non-crystallographic, particularly in situations such as pore collapse under shock loading, which is considered to be a key mechanism of detonation. We observe fluidization once the applied pressure and rate are above specific thresholds, and associate this transition with the concomitant fulfillment of two conditions, one dependent on the maximum shear stress and the other dependent on the deformation rate.Ph

An adaptive and flexible framework for convergent manufacturing with robot manipulators

December 2024School of EngineeringRobots have become indispensable in industrial manufacturing, with easy reconfigurability,high repeatability, and the ability to operate in harsh environments. They play a crucial role in factory production lines, executing pre-programmed motions in tasks such as packaging, welding, and assembly. Despite their ability to perform repetitive tasks with speed and precision, robots still face limitations in handling certain payloads (e.g., flexible or bulky objects) or complex tasks which require significant setup, calibration, or programming efforts (e.g., multi-robot coordination). A significant challenge to the universal deployment of industrial robotics in advanced manufacturing is integration and lack of robust planning. Currently, robot motion involves manually teaching waypoints and actions through a teach pendant or pre-program motions through commercial offline software packages. Further, the prevailing practice often involves running robots in the open-loop mode without optimization or feedback, overlooking the potential for improved performance and shorter cycle times with sensor-guided operation. To address these challenges, this thesis proposes an innovative and systematic approach to enhance industrial robotic performance and efficiency by focusing on robot interoperability, coordination, and robustness. This is achieved by integrating various sensors across representative manufacturing processes. This thesis explores the standardization of highlevel robot control, robust motion planning and tracking algorithm, and a combination of sensors with feedback to optimize the overall flexibility and performance of the robotic system. The integration of multiple robots and sensors into a unified framework is essential for convergent manufacturing, enhancing both performance and robustness. Several milestones have been achieved in this thesis work, including successful robotic manufacturing projects involving a mock assembly line, dual arm spraying, metal additive manufacturing, and fabric handling. The ultimate goal of this work is to demonstrate a convergent manufacturing system, comprised of multiple robots and sensors that can achieve new or improved capabilities.Ph

Investigating the molecular mechanisms of bacterial adaptations to pressure

May2025School of ScienceAll organisms must carefully regulate stress response pathways and the rate at which they grow and divide, and hence their size. The vast majority of microbes on Earth live in the deep biosphere, which is comprised of areas with high hydrostatic or lithostatic pressure. The molecular mechanisms underlying the adaptations of these organisms to survive in these extreme environments remain elusive. Despite this, there is great biological significance in understanding how cell growth/division and stress response pathway regulation are altered in these organisms, especially given the role of pressure in food sterilization. In this work, we investigated a pressure-adapted strain of E. coli from the perspective of both stress response and cell size, two essential properties of life. First, we determined that even pressure-adapted organisms are stressed by pressure but distinctly compared to non-adapted organisms. In particular, we demonstrated that the upregulation of the molecular chaperone, GroEL, was favored over that of the DnaK chaperone in response to pressure shock in the pressure-adapted strain, whereas the opposite was true for the non-adapted strain. We interpret this differential regulation as a consequence of the distinct functions of these two proteins. Our results also suggest that the alternative sigma factor RpoE and its anti-sigma factors may work in concert as pressure sensors. Second, we showed that the small cell size phenotype of the pressure-adapted strain is the result of the slow growth of the strain rather than an increase in the accumulation of cell division machinery. Slow growth may result from mutations in GlnA, which is implicated in the activation of the nitrogen starvation response, as well as in the RpoB subunit of RNA Polymerase. We also performed the first ever live cell imaging of FtsZ under pressure, demonstrating that the division ring formed by FtsZ is disrupted under pressure in vivo. Taken together, our results expand upon our understanding of how microbes can adapt to live in high pressure environments and survive pressure shocks.Ph

A unified architecture and control framework for safe and collaborative human-robot manipulation of deformable objects

May2025School of EngineeringDeformable object manipulation (DOM) is pervasive in daily life and in industrial settings. Tasks such as cable routing, tent manufacturing, pouring granular material from bags, and laying up composite sheets all involve objects with high internal degrees of freedom, making them notoriously difficult to model and control. This dissertation focuses on enabling multiple mobile robots, in collaboration with human operators, to perform DOM in various scenarios—ranging from 1D ropes and cables to 2D fabric and composite sheets—while ensuring safety, efficiency, and ease of use. A central challenge in DOM is obtaining accurate state estimates from sensors that are frequently subject to occlusions and limited feedback. To address this, we employ position-based dynamics for real-time simulation of object motion, contact, and friction, providing critical data such as predicted object shape, stress, and proximity to obstacles. This simulation underlies a suite of controllers. First, we incorporate control barrier functions to ensure the robots adapt their motion and maintain safe distances from obstacles and prevent overstretching of the deformable objects. Second, we develop an efficient global planning pipeline to manipulate deformable linear objects in cluttered environments, approximating them as serially connected rigid links. Third, we introduce a local control framework for 2D composite layup, where robots transport and position large fabric sheets collaboratively with a human operator. The same simulation reports tensions and contact forces to avoid overstress and prevent unsticking of the material from curved surfaces. We validate the developed architecture and algorithms in simulation and with physical robots under different modes of shared autonomy: human teleoperation, human-robot collaborative manipulation, and fully autonomous control with human guidance. Demonstrations include robotic rope and stiff rod navigation through obstacles, multi-robot formation in tent manufacturing, and real-time composite layup assistance. The system features a unifying touchscreen user interface that simplifies multi-robot programming and visualization, promoting seamless scalability across tasks and facilitating broader industrial adoption. Ultimately, this work advances DOM toward a robust, user-friendly framework, paving the way for safe and versatile human–robot collaboration on a wide range of deformable objects.Ph

Homophily and influence in online interactions

May2025School of ScienceWith the volume of social interactions that occur online every day and the increasing relevance online social spaces have in information dissemination, it is important to understand how interactions between people and other actors online affect how people adopt opinions and consume information. Some of these behaviors, like homophily, echo chamber formation, and misinformation can result in different populations of social media users consuming entirely non-overlapping sets of information about events occurring around them. These behaviors can drive the polarization of people online and increase misunderstanding between groups of ideologically divided people. This thesis aims to examine these behaviors in social networks, particularly how people are influenced online, how this influence is being used online, how to detect these groups of individuals, and how to test / validate these methods. To identify and quantify these behaviors, this thesis performs two main analyses on social networks and human behavior. We first analyze social behaviors directly, by both developing social experiments, tested on human participants, to test human opinion dynamics directly and by analyzing human opinion dynamics in large Twitter datasets. In this Twitter dataset, we analyze millions of tweets, retweets and replies to examine information diffusion before the 2016 and 2020 U.S. presidential elections, identify the influencers that propagate information, and examine how these influencers and their interactions changed between the two periods. In this work we find that people online are susceptible to both the influence of unknown / anonymous users online as well as opinions / messages being propagated by bots or LLM agents. We also find that the information diffusion between influencers and users of Twitter have polarized further between the 2016 and 2020 elections, and that the set of influential accounts has begun to shy away from established media type accounts and shift to strong political personalities and unaffiliated lesser known people online. In second set of works, we both develop methods for detecting clusters of users in social networks and for generating networks that are adequate benchmarks for testing such methods. We build on existing Modularity community detection methods and extend them to handle issues that occur in large / heterogeneous networks. We then identify and explore the creation of synthetic benchmark networks, defining properties necessary to generate networks with heterogeneous inter-community connectivity, creating hierarchical community structure and better representing behaviors present in many real world social networks.Ph

Application of cold spray to manufacturing of solid-state batteries

May2025School of EngineeringAs current liquid electrolyte lithium-ion batteries reach their theoretical limit, exploration of solid-state batteries (SSBs) as an energy dense and safe alternative continues to expand. Due to many decades of research the stage is being approached where the main hurdle is how to manufacture high performance batteries at scale. Tantalum doped Lithium Lanthanum Zirconium oxide (LLZTO) is a solid electrolyte material of much interest, due to its high ionic conductivity and stability with lithium metal, which faces manufacturing challenges to its high sintering temperature. It is also commonly mixed with lithium cobalt oxide (LCO), a much-used cathode material, to increase ionic transport. In this study cold spray (CS), a kinetic spraying technique with a low process temperature capable of producing dense films, is investigated for its ability to create dense films of LLZTO and LCO. Single layer dense films of LLZTO with a thickness of around 12 µm were produced on an aluminium substrate. Attempts to produce a thicker film by depositing further layers of LLZTO were unsuccessful and caused large surface perturbations which allowed aluminium to come to the surface. LCO was likewise successfully deposited on aluminium and was able to form a 1µm thick film on Alumina. Both films experienced changes in crystallographic structure during deposition, and LLZTO displayed an increase in lattice strain which could affect electrochemical performance. Despite the immaturity of using this technique with solid state batteries, this study shows that with further development, cold spray could become a viable option to produce SSBs at large scale.M

Absorptive performance of layered metasurfaces using microslit panels

December 2024School of ArchitectureThis work examines the effectiveness of layered metasurface arrangements, prioritizing space efficiency to create a broadband sound absorber. Innovative metasurfaces, including microslit panels with concentrated and coiled cavities, provide frequency-dependent absorptive properties. While these metasurfaces are independently known as efficient sound absorbers, single-layer microslit panel absorbers with a single cavity, in general, lack a wide effective bandwidth. In this work, theoretical models guide the effective creation of metastructures to achieve broadband absorption. These systems are then assembled and measured using an impedance tube to validate their acoustic performance. This paper discusses the formulation of the theoretical model, experimental validation of the model for layered absorbers, and the design specifications that can be met using various metasurface combinations.M

Geometry-based and physics-informed 3d face & eye reconstruction for facial behavior analysis

December 2024School of EngineeringFacial behavior analysis and recognition plays an important role in human-centered AI, boosting the technology development in the areas of human emotion recognition, attention detection and autonomous driving. This research performs 3D facial analysis, focusing on accurate 3D face and eye reconstruction, facial action recognition, and eye gaze estimation.The developments of deep learning models, combined with large benchmark datasets and representative 3D facial models, greatly improved the accuracy of 3D face and eye reconstruction. Despite this progress, existing methods in both areas still suffer from several significant limitations: a) lack of detailed shape modeling for accurately recovering subtle 3D facial motions and eyeball movement; b) over-dependence on a large amount of training data and labels; c) poor generalization across subjects and under different illuminations, distances and large head poses; and d) failure to effectively exploit physically plausible facial dynamics in videos. We introduce methods to address these limitations. For accurate 3D face reconstruction, we combine 3D facial models with Facial Action Unit (FAU) encoding system, where each AU represents a specific local facial motion driven by specific muscle activation.We first present a personalized 3D FAU blendshape learning framework together with a 3D face reconstruction model for recovering AU-interpretable 3D facial details. We also innovatively incorporate general knowledge of AU correlations into the learning process to reduce the amount of expression labels used in training. Our method not only produces a more personalized and detailed 3D face model but also yields improved facial action recognition. For 3D eye reconstruction, we create a deformable eye shape basis for representing detailed 3D eye structure. Different from existing approaches, we incorporate the 3D eye shape basis into a learning-based eye gaze estimation framework, inducing a geometry-based weak supervision in training the deep model. Our model is superior to others in terms of recovering 3D eye shape, eye rotation and gaze simultaneously from an image and is less dependent on full training labels while still maintaining the gaze accuracy. To further address the generalization and to exploit the facial dynamics for both facial actions and eye movement, we propose dynamic 3D face action and eye gaze tracking methods from monocular videos. The intuitive idea is based on the facial anatomy that all the facial motion components are activated by certain muscle contractions, so the reconstructed 3D motion should match with the physical laws of motion (Newton’s second law). Different from our frame-based method, we design different physically plausible models for facial action units and eyeball movement. For facial action units, we design a physics-informed model by constraining the reconstructed sequence to satisfy the underlying physics laws. For dynamic gaze tracking, we propose a physics-informed gaze tracking system by subjecting the eyeball movements to certain physical constrains and biomechanical laws. Furthermore, we propose to leverage human interactions and hand-eye coordination to reduce 3D eye gaze annotation using weakly supervised eye gaze tracking models. Our methods are evaluated against state-of-the-art methods both quantitatively and qualitatively, including 3D face reconstruction accuracy, facial action unit detection accuracy, and gaze estimation accuracy, both within and across datasets.Ph

Analytic and numerical investigations of lattice-based statistical mechanical models

December 2024School of ScienceWe study the canonical ensembles of two lattice models which work with vorticity. In a 2D setting vorticity can be treated as a scalar quantity. Certain functions of vorticity, most notably its first moment, are conserved. By choosing a set of conserved quantities appropriate to the problem being studied, and an inverse temperature which allows one to specify whether a high energy or low energy regime is of interest, one can construct a statistical ensemble. An ensemble encodes certain long-term behaviors of the system, but does not require solving the underlying differential equations which govern the dynamics. The first system is studied is based off the Helmholtz-Onsager point vortex gas, and studies the low positive temperature/low energy regime in a multiply-connected domain. In this regime vorticity particles have high probability to be near the domain walls, as the system energy has a self-interaction term for each vortex which is negative in this neighborhood. This behavior was observed in the canonical ensemble. Due to the simplicity of the point vortex dynamics, the results were supplemented with a microcanonical analysis based on simulating the system and analytically solving a mean field equation which gives its long-term density average. The second system studied is the Kac-Berlin spherical model, which conserves the second moment of the site strengths. The low negative temperature/high energy regime of the spherical model has been used to depict wave systems which undergo inverse energy cascade. We approach the model with new analytical techniques and find evidence for a phase transition, as well as an equation for the expectation of energy after the phase transition. These predictions are then examined and verified with numerical simulations on several lattices which encode a particular instance of the spherical model.Ph