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Capturing Obscura: Toward a Participatory Framework for (Re)making of Space of Liminality
No full textCapturing Obscura intends to identify and activate the space of liminality—a residual space resulting from top-down capital planning production—through a participatory methodology that supports the continuous (re)making of the urban landscape. Liminality is adopted here for its ability to address both time and space—its transitional, temporal, and ephemeral qualities reflect a relationship with time, while its informality and lack of prescribed function underscore its spatial ambiguity.
Cambridge, MA is selected as the site for its accessibility and potential for fieldwork. The project identifies liminal spaces through ethnographic observation and develops a guidebook of toolkits that activate liminal space as an inclusive public space, supporting community participation and engagement throughout the design process.
The crux of the thesis is to explore a reciprocal design methodology by examining the space of liminality and inviting communities to engage in the design process for a cohesive and vibrant urban landscape experience.Department of Landscape Architectur
Challenging Current Hip Reconstruction Practices in Patients with Cerebral Palsy
No full textIn April 2006, an international working group revised Bax’s widely used modern definition of Cerebral Palsy (CP), characterizing it as: “A group of permanent disorders of the development of movement and posture, causing activity limitation, that are attributed to non-progressive disturbances that occurred in the developing fetal or infant brain. The motor disorders of CP are often accompanied by disturbances of sensation, perception, cognition, communication and behavior, by epilepsy, and by secondary musculoskeletal problems”. CP remains the most common cause of chronic childhood disability, with a prevalence of 2-2.5 per 1000 live births in developed countries. This thesis will address two intertwined and critical aspects of CP, aligned with its contemporary holistic definition.
First, due to the non-progressive but permanent nature of the primary brain lesion in CP, many acquired clinical manifestations such as musculoskeletal pathology progress over time in the setting of growth and spasticity. Hip displacement, second only to Achilles contracture in prevalence, effects approximately 35% of all children with CP, and is positively correlated with the severity of functional impairment as defined by the Gross Motor Function Classification System (GMFCS). This is a five-level ordinal rating scale based on the assessment of self-initiated movement with emphasis on function with regard to sitting and walking. Incidence of hip displacement in non-ambulatory patients (GMFCS IV and V) ranges from 60% up to 90%. The adverse natural history of CP hip displacement necessitates surgery in the majority of children, which aims to obtain a pain-free, mobile, and concentrically reduced hip with symmetric range of motion, prior to the onset of painful arthritis. Hip reconstruction surgery typically involves soft tissue releases, femoral varus derotation osteotomy (VDRO), pelvic osteotomy (PO), or a combination thereof. In the literature, clear surgical indications for performing an additional acetabuloplasty after VDRO are elusive, and in practice the decision remains driven by surgeons’ experience and training. While combining VDRO and PO generally lowers resubluxation rates, some patients can safely undergo VDRO alone, thus avoiding additional surgical risk and morbidity. The first part of this thesis evaluates the effect of intraoperative hip arthrography – successfully used in Developmental Dysplasia of the Hip - as a tool for acetabuloplasty decision-making in neuromuscular hip reconstruction.
Second, the revised CP definition emphasizes a holistic approach; shifting from the historical musculoskeletal focus towards incorporating comorbidities that influence patients’ health-related quality of life (HRQoL). Hip reconstruction surgery and spinal fusion aim to alleviate pain, ease caregiving, and improve HRQoL, yet their effect has been debated due to surgical complexity, postoperative risk of morbidity and patient mortality. Today, orthopedic surgeons recognize that HRQoL improvements are more meaningful to patients and caregivers than radiographic outcomes, underscoring the importance of HRQoL outcome measures. The Caregiver Priorities and Child Health Index of Life with Disabilities (CPCHILD) questionnaire, validated for assessing HRQoL and caregiver burden in GMFCS levels IV and V CP patients, is increasingly used to evaluate the impact of hip and spine surgery. However, before becoming a gold standard, effective outcome instruments must also demonstrate responsiveness - the tools’ ability to detect change and remain constant across diverse cohorts. The second part of thesis assesses the responsiveness of the CPCHILD questionnaire in children with severe non-ambulatory CP undergoing hip reconstruction surgery and spinal fusion.Graduate Educatio
The Transformative Power of Paradigms: How Shifting the Human-Nature Relationship Impacts Social-Ecological Systems
No full textThe current global social-ecological system (SES) is extractive, polluting and prioritizes economic growth. Due to systems dynamics, reinforcing feedback loops have emerged within this SES that drive runaway growth and environmental degradation. One proposed solution is the Circular Economy (CE) which aims to decouple economic growth from environmental harm. However, it remains unclear if CE will truly achieve sustainability—defined as a system’s ability to provide for human well-being within planetary boundaries—or whether it merely adjusts the rules and parameters of a system without addressing the deeper paradigms that underpin it. As the world’s oldest continuing culture, Aboriginal communities have provided for human health and well- being within planetary boundaries for over 65,000 years, persisting under remarkably diverse and harsh conditions. What can be learned across these three different constructs and cultures, so that we may redesign our current system to one where sustainability and regeneration, instead of degradation and collapse, is inevitable? This research used systems modelling to explore how the human-nature paradigm underpinning an SES impacts on the system, its components, structures, and sustainability outcomes. I hypothesized that (1) an SES underpinned by an ecocentric human-nature paradigm would show greater sustainability than an SES underpinned by an anthropocentric human-nature paradigm. I also hypothesized that (2) SESs sharing a similar anthropocentric human-nature paradigm would exhibit similar system structures, components and sustainability outcomes, and (3) an SES with an ecocentric human-nature paradigm would present a different system structure and components, compared to one with an anthropocentric human-nature paradigm, supporting the proposition that paradigms represent a deep system leverage point. To undertake this analysis, I identified three different SESs: Business as Usual (BAU), CE, and Aboriginal. Upon confirming that each system had the appropriate human-nature paradigm for analysis, I completed a thorough literature review and identified the components and structures of each system. I then mapped each system as a Causal Loop Diagram (CLD) in Kumu to assess the visual system structure and feedback loops. Finally, I evaluated their sustainability using multiple sustainability frameworks including thin and thick, and strong and weak sustainability. The results showed that BAU and CE, which both had anthropocentric human- nature relationship paradigms, had similar system structures and components that resulted in low sustainability outcomes. Alternatively, the Aboriginal system with an ecocentric paradigm, revealed a significantly different structure and components which resulted in high levels of sustainability. This supports the idea that to shift systems to result in sustainability, we must address the human-nature relationship that underpins them. This analysis shows the value of systems thinking and the role that paradigms play in creating sustainable outcomes. Further work is needed to build, test and refine these models, and quantitatively test the qualitative ideas proposed throughout this work. Finally, as revealed by systems modelling, we urgently need a new human-nature paradigm for our global system that will result in a truly sustainable future that achieves societal well-being within planetary boundaries.Extension Studie
Isogenic sets of T. vaginalis harboring different combinations of trichomonasviruses reveal insights into host–virus interactions
No full textTrichomonasviruses are a genus of double stranded RNA (dsRNA) viruses that persist in the obligate human protozoan parasite T. vaginalis (Tvag). Tvag is the causative agent of trichomoniasis, the most common nonviral sexually transmitted infection (STI) worldwide. These viruses, commonly known as TVV1, TVV2, TVV3, TVV4, and TVV5, have been implicated in increasing the severity of trichomoniasis by eliciting greater pelvic inflammation. Unlike many familiar eukaryotic viruses, trichomonasviruses are not thought to have an extracellular lifecycle and instead are believed to be transmitted vertically as the parasite divides. The presence of trichomonasviruses is not thought to be detrimental to the health of the parasite, but rigorous investigation into the effects of trichomonasviruses on their host has to date been challenging. Because uninfected parasites are not thought to be able to be infected with trichomonasviruses, previous studies into the effects of trichomonasviruses on their host have largely relied on comparing virus-positive isolates to virus-negative isolates. However, gene expression differences between these isolates have confounded studies. In 2022, Narayanasamy et al. reported that a cytidine nucleoside analog, 2’-C-methylcytidine (2CMC) was effective in clearing Tvag isolates of infection with TVV1, TVV2, and TVV3. In this study, we extended the results of Narayanasamy et al. to demonstrate that 2CMC is effective against in reducing viral RNA abundance of representative strains of all five TVV species. In doing so, we identified differences in species-specific differences in 2CMC susceptibility and harness those susceptibility differences to generate isogenic sets of Tvag clones derived from the same parent isolate that harbored different combinations of trichomonasviruses. Using these newly generated isogenic sets, we investigated effects of viral infection on Tvag growth, survival, and adherence to human cells. While we saw no apparent difference in the growth rate of virus-positive and virus-negative Tvag clones in ideal conditions, our results suggested that virus-positive Tvag clones have an increased ability to survive in harsh conditions and a decreased ability to adhere to human cells. To understand the mechanism underlying these results, we performed differential gene expression analysis using three isogenic Tvag sets and revealed a number of differentially expressed genes between cured and uncured Tvag clones, including the putative transcription factor TvMyb4, which was consistently upregulated across Tvag clones harboring trichomonasviruses. We provide evidence suggesting involvement of TvMyb4 in the persistence of trichomonasviruses and in the survival differences between virus-positive and virus-negative clones. Together, the results presented in this work reveal new insights about differences between trichomonasvirus species and the relationship between trichomonasviruses and their host, providing valuable information about both an important human pathogen and a valuable model system for viral persistence.Medical Science
The Sumida Transcripts: Imagination Projected
No full textThe thesis transcribes a methodology to design with artifacts of cultural landscapes. This methodological experiment unfolds in three episodes—deconstruction, reconstruction, and projection. It begins with Picture Book Sumida River A Glance of Both Shores, a series of Hokusai’s woodblock prints along the Sumida River. Mass-produced in the early 19th century, the prints reflected and cultivated the public imagination of the river. Upon them, the thesis executes a series of acts to produce interventions in the contemporary landscapes. The serial actions allow the project to oscillate between reality and images. The resulting street painting interventions aim to pivot the external perception of the river, which became obscured during modern urbanization, with optical harmony and dissonance. In doing so, the thesis contributes to the discourse around design methodology, representation, and public imagination.Department of Landscape Architectur
Assessing Corporate Growth and Bankruptcy Risk Using Public Data Proxies
No full textThis thesis applies natural language processing (NLP) to job listing data as a novel predictive and explanatory tool for evaluating bankruptcy risk and corporate growth. Unlike models based on traditional financial ratios, which are limited by the sparsity of data for small and private companies, job postings provide abundant, real-time information relevant for nearly all corporations and enhance published corporate evaluation methods.
In this report, we demonstrate that the textual context within job listing data offers a meaningful signal for both predictive and descriptive purposes. Our analysis is applied to a corpus of approximately 51.8 million job listings generated from 6764 unique corporations over the roughly decade-long period from 2010 to 2020.
For bankruptcy prediction, our research presents models with robust predictive performances (accuracy 0.8652; specificity 0.8653; sensitivity 0.8042; ROC-AUC 0.9162) that mirrors or exceeds the predictive capabilities of reference baseline models from literature. We then discuss the potential of topic models as both a predictive and descriptive tool for the overall economy as a whole; though our work indicates limited performance of the topics as a predictive feature. Instead, their descriptive potential lies with the ability to track desired employment and thematic distribution across fields such as remote work-- concentrated in tech and management--or entry-level positions--concentrated in retail or delivery. Finally, we also present models evaluating corporate growth, where our predictions reflect the theoretical economic behaviors of debt-based and cyclical investment in the corporate bond and commodity-driven sectors.Computer Scienc
The New Surface: Street as a Contested Field Condition
No full textAutonomous vehicle (AV) technologies are fundamentally altering the operational logic of streets, disrupting established urban patterns. This thesis examines the spatial consequences of automation on the street as a complex field condition—where movement systems, regulations, and urban form intersect and compete. Through critical examination of historical urban visions proposed in response to transportation revolutions—from the automobile’s emergence to the proliferation of highway infrastructures—the research reveals patterns of adaptation to changing mobility systems. Building on this historical analysis, the thesis explores how AVs will prescribe new spatial logics and politics on streets. Rather than accepting this impending mobility shift as technological inevitability to which cities merely react, the thesis reframes it as a contingent process that can transform in response to urban design desires. The work concludes with speculative urban scenarios that project AVs’ continued influence, suggesting design interventions that reimagine streets as contested urban conditions—where boundaries between infrastructure, public space, and technology are continuously renegotiated.Department of Urban Planning and Desig
Uncertainty and Risk Quantification in High-Dimensional Statistics: Methods for Non-Traditional Settings
No full textHigh-dimensional data are increasingly common across fields such as genomics, economics, and neuroscience, often challenging conventional statistical methods. This dissertation develops new tools for uncertainty quantification in high-dimensional settings where standard assumptions—like sparsity or data homogeneity—may not apply. The first part focuses on high-dimensional causal inference without sparsity. We analyze cross-fitted estimators and derive the asymptotic distribution of the cross-fitted augmented inverse probability weighting (AIPW) estimator under a proportional asymptotics regime. Our results highlight how cross-fitting and regularization impact estimation risk, enabling more accurate inference even in dense, high-dimensional designs. The second part addresses predictive inference under distributional heterogeneity. Classical conformal methods assume identically distributed data, an assumption violated in many real-world applications. We propose conformal algorithms for multi-environment settings, offering valid prediction intervals under minimal assumptions. These methods apply to both regression and classification, support general loss functions, and can incorporate auxiliary information to reduce interval size without compromising coverage. Together, these results advance uncertainty quantification in modern, complex data environments.Statistic
Data-Driven Methods for Modeling Emissions and Atmospheric Composition
No full textThis dissertation investigates how large remote sensing datasets of atmospheric composition can be combined with traditional chemical transport models to advance understanding of pollutant budgets. Chemical transport models can simulate past and future pollutant burdens by representing atmospheric transport, reactive processes, and pollutant sources and sinks, but are subject to error in any of these components. Recent advances in chemical data assimilation and machine learning offer novel methods to combine the strengths of chemical transport models with information encoded in large measurement libraries from satellites and other instruments. I further develop and apply these methods in two core areas: fine particulate matter concentrations (focusing in East Asia) and pollutant emissions quantification (focusing on methane). Specific topics addressed in my dissertation include the following:
Quantifying surface fine particulate matter in East Asia using machine learning (Chapters 1 and 2). Inhalation of outdoor fine particulate matter (PM2.5) is a major public health burden. Surface instruments allow PM2.5 monitoring but cannot cover all areas, so satellite-based aerosol optical depth (AOD) measurements can be used in combination with machine learning to estimate gap-free surface PM2.5. Here I developed and applied a machine learning model to produce daily, high resolution maps of PM2.5 in East Asia.
Pendergrass et al. (2022) Atmos. Meas. Tech., Pendergrass et al. (2025) Atmos. Env.
Interpreting fine particulate matter trends in South Korea, 2011-2022 (Chapter 3). Despite steady reductions in precursor emissions, winter PM2.5 in South Korea has shown fluctuating trends. Here I apply results from Chapters 1 and 2 along with surface data and remote sensing products to analyze the drivers of PM2.5 concentrations. Results suggest a growing role for secondary PM2.5 production due in part to rising oxidant concentrations, sulfate reductions in favor of nitrate, and changing nighttime PM2.5 formation pathways.
Pendergrass et al. submitted to Geophys. Res. Lett.
Developing a chemical data assimilation platform and applying it to global methane emissions (Chapters 4 and 5). Satellite observations of pollutant concentrations do not offer direct information on pollutant sources. Bayesian optimization can fuse observational data with emissions inventories and constrain emissions based on both. Here I develop an open-source chemical data assimilation toolkit called CHEEREIO which uses the localized ensemble transform Kalman filter (LETKF) algorithm and the GEOS-Chem chemical transport model to optimize emissions and concentrations. I then apply CHEEREIO to methane, with a focus on explaining causes of the 2020-2022 methane surge. I attribute the surge to emissions from the tropics and use a satellite inundation product to suggest that wetlands play a key role.
Pendergrass et al. (2023) Geosci. Mod. Dev., Pendergrass et al. submitted to Atmos. Chem. Phys.Engineering and Applied Sciences - Engineering Science
Long-Term Single-Cell Imaging of Live Microbes by Correlative Fluorescence and Raman Microscopy & Time-Resolved Stark Effect Spectroscopy of Protein Crystals
No full textUnderstanding the behavior of a microbe requires not only an understanding of molecular mechanisms, e.g. DNA replication, transcription, and translation, but also knowledge of the cell’s chemical composition over time. There are powerful tools for probing the mechanisms of core cell-biological processes. However, the existing tools to measure cell composition have significant limitations. Information-rich methods, such as mass spectrometry, are lethal, while fluorescence methods provide good time resolution and work on live cells, but are limited in what they can measure. Prior work has demonstrated that spontaneous Raman spectroscopy can be a powerful tool to measure cellular composition. However, low throughput has limited its potential for discovery. Here, I describe my contributions to correlated epifluorescence and laser scanning Raman microscopy to enable the collection of single-cell spectra from many single cells in long-term time-lapse experiments, with imaging every 15 minutes. I then establish that this single-cell Raman imaging (scRaman) system can be used without substantial phototoxic effects to image the yeast Saccharomyces cerevisiae. To benchmark the ability to track biologically important changes in cellular composition, I study S. cerevisiae under conditions of nitrogen starvation and repletion. I demonstrate the ability of this system to resolve the dynamics of compositional changes at a single-cell level, mapping the observed dynamics to known biological mechanisms. I describe the analysis pipeline required for this work and the advances in combined Raman and microscope control software to achieve these experiments. Finally, I describe a separate project in which I developed an analytical framework for interpreting time-resolved Stark effect spectroscopy data obtained from single protein crystals.Engineering and Applied Sciences - Applied Physic