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Reliable Grasping with Tactile Sensing
No full textFor robots to seamlessly integrate into everyday life and interact with various objects in unstructured environments like homes, they must exhibit extreme reliability. However, robots today often struggle to recover from errors, and understanding the root causes of these failures remains challenging. This thesis addresses robotic reliability in grasping and manipulation through the application of tactile sensing. Specifically, I have designed a highly instrumented robot hand, developed a stochastic friction model for grasp slip prediction, and employed tactile sensing to create physics-machine learning hybrid models. These models aim to predict the stability of anticipated grasping tasks and determine extrinsic contact locations. Our findings reveal that by modeling friction as a stochastic variable, we can quantify uncertainties in grasping and manipulation more accurately. For stability prediction, our hierarchical physics-machine learning hybrid approach proves effective in addressing performance, data size requirements, interpretability, and generalizability. Overall, reliability is crucial for robots to effectively assist humans in various settings, including hospitals, elderly care facilities, and disaster sites. This thesis offers a comprehensive framework for understanding the role of tactile sensing in enhancing reliability prediction in robotic grasping and manipulation.Engineering and Applied Sciences - Engineering Science
Institutional Books 1.0: A 242B Token Dataset from Harvard Library's Collections, Refined for Accuracy and Usability
No full textLarge language models (LLMs) use data to learn about the world in order to produce meaningful correlations and predictions. As such, the nature, scale, quality, and diversity of the datasets used to train these models, or to support their work at inference time, have a direct impact on their quality. The rapid development and adoption of LLMs of varying quality has brought into focus the scarcity of publicly available, high-quality training data and revealed an urgent need to ground the stewardship of these datasets in sustainable practices with clear provenance chains. To that end, this technical report introduces Institutional Books 1.0, a large collection of public domain books originally digitized through Harvard Library's participation in the Google Books project, beginning in 2006. Working with Harvard Library, we extracted, analyzed, and processed these volumes into an extensively-documented dataset of historic texts. This analysis covers the entirety of Harvard Library's collection scanned as part of that project, originally spanning 1,075,899 volumes written in over 250 different languages for a total of approximately 250 billion tokens. As part of this initial release, the OCR-extracted text (original and post-processed) as well as the metadata (bibliographic, source, and generated) of the 983,004 volumes, or 242B tokens, identified as being in the public domain have been made available. This report describes this project's goals and methods as well as the results of the analyses we performed, all in service of making this historical collection more accessible and easier for humans and machines alike to filter, read and use.Author's Origina
Barbarian: A Semi-Autobiographical Memoir
No full textTake a glance at Kate Irwin’s background and budding résumé, and her life seems
just about as charmed as they come. She graduated number one in her Texas public high
school class at sixteen years old. She then took a gap year, during which she lived and
worked in New York City as a successful teen model. Now, at eighteen, she’s finishing
up her first year at Harvard, where she’s trying to find her place in the college newspaper.
But, as we all know, appearances can be deceiving.
The reality is that Kate’s world is crumbling.
Kate is facing expulsion from Harvard after two semesters of academic probation;
her short-lived modeling career was an unintended outcome of a depression-related
eating disorder that began around puberty; and, she’s struggling with severe alcohol
addiction and PTSD from a childhood rampant with a trifecta of abuse: physical, verbal,
and sexual.
Barbarian: A Semi-Autobiographical Memoir follows Kate from the crushing
blow of her expulsion, which will require her to take a year off from her studies; during
that time, her only option is to go home, a place to which she’d sworn she’d never return.
When Kate gets home, she finds her six-year-old niece—who is also named Katherine
Irwin, due to an embarrassing family situation—is living in her old childhood bedroom,
going to her old elementary school, and following in Kate Sr.’s footsteps. Much to our
protagonist’s horror, Little Katie may be living the same nightmare she herself lived a
decade earlier.Extension Studie
From Tweets to Votes: An Assessment of Twitter’s Role in Donald Trump’s 2016 Election
No full textThis study examines how Donald Trump’s Twitter strategy contributed to his victory in the 2016 U.S. presidential election. Although Trump’s Twitter activity did not directly secure him the winning votes, it played an indirect role by capturing the attention of traditional media outlets, which then amplified his political messages to a broader audience and ignited voter action. By frequently tagging media networks, journalists, and other traditional media professionals, Trump received substantially more coverage than his opponent, Hillary Clinton, the 2016 Democrat nominee, whose Twitter strategy was primarily targeting prominent politicians and elected officials. This heightened exposure proved critical to Trump’s electoral success.
To support this conclusion, a survey, which generated n=132 responses, was administered. The results indicate that both partisan and independent voters rely more on traditional media for political decision-making than on Twitter content. Moreover, compared to partisans, independent voters are notably less susceptible to being influenced by Twitter in shaping their political views.Extension Studie
The Pivotal Role of Digital Public Infrastructure in Shaping the Global Economy
No full textThis thesis explores the pivotal role of India’s Digital Public Infrastructure (DPI)
in advancing effective governance and sustainable development, with a particular
emphasis on its applicability and influence across the Global South. Anchored in
platforms such as Aadhaar (digital identity), Unified Payments Interface (UPI),
DigiLocker, and the Data Empowerment and Protection Architecture (DEPA), India’s
DPI ecosystem represents a public-sector-led, scalable, and modular approach to
delivering digital services. The central research question investigates whether DPI, as
developed and implemented in India, can serve not only as a transformative governance
tool domestically but also as a form of soft power and digital diplomacy abroad,
especially in low- and middle-income countries.
The thesis adopts a multiple case study methodology, combining descriptive and
interpretive analysis of India and Brazil as principal cases, supplemented by emerging
evidence from Ethiopia, Sri Lanka, and the Philippines—countries currently engaged
with India’s DPI model. A secondary data-driven economic model was constructed to
examine the correlation between DPI deployment and progress across selected
Sustainable Development Goals (SDGs), specifically SDG 1 (No Poverty), SDG 8
(Decent Work and Economic Growth), and SDG 9 (Industry, Innovation, and
Infrastructure). Key performance indicators (KPIs) such as poverty headcount ratio,
financial inclusion metrics, broadband penetration, and digital transaction volumes were
tracked over the 2015–2023 period.
Findings indicate a plausible association between DPI rollouts and measurable
improvements in service delivery, fiscal efficiency, and digital inclusion, particularly
among underserved populations. While the study acknowledges that DPI is one among
several contributing factors, the evidence supports its role as an enabler of inclusive
growth and governance reform. Moreover, India’s strategy of exporting DPI components
via open-source frameworks, modular technology, and bilateral cooperation suggests the
emergence of a new model of South–South digital cooperation rooted in co-development
and digital sovereignty.
The thesis concludes by offering policy recommendations for India to integrate AI
into DPI, leverage its mineral resources for tech-industrial development, and
institutionalize multilateral DPI governance standards. In doing so, India can consolidate
its position as both a domestic innovator and a normative leader in shaping a more
equitable digital future for the Global South.Extension Studie
Transient Pattern Formation in Biological Systems
No full textThis dissertation investigates transient pattern formation in biological systems through a combination of theoretical modeling, stochastic analysis, and simulation. Biological processes are often driven by local interactions and feedback mechanisms that give rise to complex, time-dependent patterns. Given the inherent heterogeneity and noise in living systems, traditional deterministic models are often insufficient to capture the full spectrum of behaviors observed in nature. Here, I develop and analyze different models that are robust to microscopic details while capturing essential dynamical features.
One focus of this dissertation is the study of reaction-diffusion phenomena in immune cell signaling. I investigate how neutrophils generate self-regulating, transient chemical waves that coordinate a rapid yet contained response to injury or infection. The models show that the interplay between activators and locally produced inhibitors can naturally limit the spatial extent of these signaling waves, providing a mechanistic basis for preventing overreaction in immune responses.
Further, I examine the role of mechanical stress in flow-driven pattern formation within porous media. By representing these media as dynamic networks in which individual conduits adapt through erosion and deposition, I identify critical thresholds that lead to distinct phase behaviors, such as channelization and homogenization. This work not only elucidates the feedback between fluid flow and structural evolution but also offers a simple approach to analyze complex networks.
By applying a similar strategy to biological networks, I explore the emergence of optimized biological flow networks. By integrating local mechanical sensing into growth dynamics, I derive conditions under which vascular systems naturally converge toward configurations predicted by Murray’s law—a hallmark of energy-efficient design observed in blood vessels, leaf venation, and even in the foraging networks of slime molds.
Finally, I extend the classical mutation models, exemplified by the Luria–Delbruck experiment, to regimes where the effective mutation rate is significantly higher through modern gene-editing techniques. By formulating discrete stochastic models, I reveal novel phase transitions in DNA break-and-repair dynamics and demonstrate how randomness in molecular events influences cell fate and population heterogeneity.Engineering and Applied Sciences - Applied Physic
From Strassbourg To Hadamar: Nazi Psychiatry and Patient Biographies in Annexed Alsace (1941-1944)
No full textAuthor's Origina
Techniques for High-Throughput Directed Enzyme Evolution
No full textEnzymes are versatile biological catalysts that play crucial roles in numerous industrial processes, including the production of biofuels, pharmaceuticals, and fine chemicals. However, natural enzymes often face limitations in stability and efficiency under industrial conditions, necessitating their evolution for enhanced performance. High-throughput directed evolution schemes typically involve four key steps: mutagenesis library construction, library screening or selection, variant sequencing, and variant characterization. In this thesis, we present a series of techniques relevant to enhancing the efficiency and effectiveness of high-throughput directed evolution.
In Chapter 2, we introduce a platform that utilizes nCas9 and mutagenic polymerase to achieve autonomous gene diversification. This platform, combined with a customized lab-on-chip device, enables continuous screening and thus facilitates controlled continuous evolution.
Chapter 3 discusses the development of Random Saturation Mutagenesis (RSM) libraries. This method allows for the generation of chemically diverse libraries with minimal bias, broadening the exploration of the enzyme fitness landscape. We demonstrate the design, construction, and superiority of these libraries over traditional error-prone PCR techniques in terms of diversity and efficiency.
In Chapter 4, we address the challenge of maintaining functional conditions in complex droplet environments by developing a hydrogel-bead based method for high-throughput screening of IVTT-expressed enzymes in each droplet.
And finally in Chapter 5, we present an economical method for sequencing mutagenesis libraries at full gene length using Illumina sequencers, significantly reducing costs for validating mutations in large libraries.Engineering and Applied Sciences - Engineering Science
Sustainable Packaging Trends in the Consumer Packaged Goods Market
No full textThis paper explores sustainable packaging trends in the consumer packaged goods (CPG) market, highlighting the environmental challenges posed by plastic waste, resource scarcity, and recycling inefficiencies. It delves into innovative solutions such as biodegradable materials, technological integration with AI and blockchain, and circular economy models, emphasizing their potential to reduce the environmental footprint of packaging. The study also provides actionable recommendations for enhancing sustainability and fostering consumer engagement through transparent communication and storytelling.The increasing global awareness of environmental challenges, including plastic pollution and resource scarcity, has amplified the demand for sustainable packaging in the consumer packaged goods (CPG) sector. This paper examines sustainable packaging trends and their application within the CPG industry, which significantly contributes to environmental issues due to high usage of non-recyclable and single-use materials. The analysis explores advancements in material innovation, such as biodegradable and compostable packaging, technological integration, including AI and blockchain for supply chain transparency, and circular economy models like reusable packaging. The study highlights the environmental, regulatory, and consumer pressures driving these innovations and provides actionable recommendations for enhancing sustainability, including dematerialization, smart packaging, and stakeholder collaboration. By adopting these strategies, the CPG sector can reduce its ecological footprint, align with consumer preferences, and contribute to global sustainability goals, serving as a benchmark for other industries.Author's Origina