Leveraging Artificial Intelligence to Accelerate and Enable Antibody Discovery

Monoclonal antibodies are a powerful, diverse class of therapeutics which can be developed to target theoretically any protein with exquisite specificity. Despite decades of effort toward experimental and computational methods for antibody discovery, existing approaches remain limited by low probabilities of success, insufficient datasets, and limited scope. In this dissertation I present three complementary methods which leverage artificial intelligence to overcome such limitations, providing a novel computational framework to augment the traditional antibody discovery process. First, I present a lightweight method for denoising antibody specificity predictions from single-cell sequencing data by clustering antigen counts into signal and noise components with a negative binomial mixture model. I show that this approach provides improved predictions for in vitro antibody-antigen binding when compared to the standard scoring method, regardless of variance in data size and noise structure across samples. Next, I present MAGE (Monoclonal Antibody GEnerator), a sequence-based protein Large Language Model (LLM) fine-tuned for the task of generating paired variable heavy and light chain antibody sequences against targets of interest. I show that MAGE is capable of generating diverse antibody sequences with experimentally validated binding specificity and neutralization against three viral targets, without need for a starting antibody template. Lastly, I demonstrate that classification of antibody binding specificity is possible from sequence alone using LLM classifiers. I present two separate model architectures for this task, using the SARS-CoV-2 spike receptor binding domain (RBD) as a proof of concept, and explore the interpretability of these models. While each of these projects independently present novel methods for accelerating the discovery process, the synergistic integration of such methods presents a powerful framework for AI-augmented antibody discovery that enables iterative improvement in combination with experimental validation. This lab-in-the-loop environment will drastically decrease the resources necessary for antibody discovery, while also enabling the design of antibodies with novel properties, and against novel targets, expanding the capabilities of existing methods

Unsettling Black Servitude in Jean Rhys’s Wide Sargasso Sea

It would be impossible to tell the story of Jean Rhys’s 1966 novel Wide Sargasso Sea without its Black servant characters, yet these characters have historically figured very little in existing scholarship on the novel. Self-consciously written as a prequel to Charlotte Brontë’s Jane Eyre (1847), Wide Sargasso Sea is populated with servants whose movements, laughter, and behavior both unsettle and compel the cautious scrutiny of the novel’s white narrators. While Christophine—one of the novel’s most prominent servant figures—certainly stands out as a servant to both the narrators and readers of Wide Sargasso Sea, I hope in my paper to complicate readings of the character by considering how she functions in a relational context with the novel’s other figures of Black servitude which, in turn, I argue, enables investigation into the ways in which Wide Sargasso Sea represents relations of servitude in the first years of Emancipation. In this way, paying attention to the array of servant figures surrounding Rhys’s white narrators, I argue, dilates an understanding of Wide Sargasso Sea beyond simply, or merely, a reinterpretation of Jane Eyre from the perspective of its villainized madwoman in the attic; it also reveals the novel to be both a story about what happened in the Caribbean after the British Empire abolished slavery, and a record of imperial and colonial subjects affectively reorienting themselves within a disintegrating hegemonic order

Training Behavior Technicians to Foster Enriched Learning Contexts

While many behavior technicians utilize natural environment teaching (NET) when delivering applied behavior analysis (ABA) therapy services, guidance is limited regarding how naturalistic intervention should be implemented. Naturalistic Developmental Behavioral Interventions (NDBIs) are a class of interventions that are behavior analytic but also incorporate developmental principles (Schreibman et al., 2015). While behavior technicians are trained on some strategies that are components of NDBIs, they are not required to be trained on developmental strategies that enrich the learning context, such as contingent imitation and linguistic mapping (Bravo, et al., 2024; Jimenez-Gomez et al., 2019), modeling (Schreibman et al., 2015), language expansions (Kaiser et al., 2000), or play expansions (Frey & Kaiser, 2011). A non-concurrent multiple baseline design was used to evaluate a cascading logic model that includes researcher training and ongoing Board Certified Behavior Analyst (BCBA)-implemented support on behavior technician (BT) use of NDBI-informed strategies designed to foster enriched learning contexts (ELC) during NET. The intervention was effective in increasing levels of play and language strategies across all three participants, increasing BT engagement across all three participants, and increasing stability in levels of engagement for two of the three child participants. The results of this study demonstrate the potential for effective training methods for recommended practices in NET that center endogenous implementers. ABA therapy centers prioritizing play-based and child-led intervention may need to consider ways to explicitly train their staff in implementing strategies that support an enriched and engaging context, which may extend beyond the bounds of current RBT Task List training requirements

Irradiation- and Bias-Stress-Induced Defects and Gate Leakage in GaN-based HEMTs

During last several decades, GaN-based HEMTs are increasingly popular for use in space-based, high-power, and high-frequency electronics due to their large band gap, high breakdown electric field and high mobility two-dimensional electron gas (2DEG) at the heterointerface. In this work, the irradiation and bias stress response are investigated. The non-monotonic response to different fluence of proton irradiation, caused by evolution of defect concentrations, highlights crucial role of ionization-induced defect passivation and activation, as well as the generation of new defects via displacement damage. Besides, temperature-dependent noise measurements verify that the activation energy for FeGa defects is 0.56 ± 0.05 eV, aligning with theoretical predictions and other spectroscopic observations. This research revises and expands upon prior studies, offering a more physically accurate calibration of the Dutta-Horn model for low-frequency (LF) noise in AlGaN/GaN HEMTs. Also, dehydrogenation of ON−H impurity centers, along with the subsequent rise in the concentration of ON impurity centers in the AlGaN and/or AlN layers, plays a significant role in the threshold-voltage hysteresis and increased gate leakage current detected at cryogenic temperatures in stressed devices. These findings provide valuable insights into the instabilities that influence the reliability and radiation response of GaN-based HEMTs in the application of cryogenic environments

Electrochemically actuated metasurfaces for low power nanophotonic and energy storage devices

In an age of ubiquitous access to information, metamaterials offer a solution to a wide range of information display needs. Notably, metamaterial-based structural color promises vivid coloration across a broad color gamut, promising fade-resistance and a reduced environmental footprint. However, once structural parameters are set using traditional fabrication methods wavefront operations cannot be modified. In recent years, active elements have been incorporated into metasurface geometries to enable broader functionality controlled by an applied stimulus. In particular, electrochemical ion insertion allows for reversible carrier doping, volume expansion, and phase transition within the same system, and is an attractive actuation mechanism for a meta-optic platform. The research presented here aims to elucidate this platform by studying the use of electrochemical ion insertion and associated lattice modification to manipulate dielectric structural color within the visible spectrum. This study begins with amorphous silicon as a lithium-ion host material, due to its outstanding specific capacity and volumetric expansion during alloying. By designing a silicon structural color metasurface and monitoring its optical response in real time during ion insertion, we demonstrated continuous color bleaching and restoration while simultaneously establishing color resilience after irreversible capacity loss and energy storage ability. In contrast to silicon, anatase TiO2 offers ion hosting ability without associated volume expansion effects and reduced losses at visible frequencies, offering another attractive platform for electrochemically actuated structural color. Here, switching times were improved by minimizing diffusion distances and selecting H+ as a dopant for increased diffusivity in the material. The resulting device improved coloration time by an order of magnitude over actuation times for Li-ion insertion based active structural color. This dissertation demonstrates that electrochemical ion insertion is a viable method for dynamic structural color metasurface operation, and shows that improvement in color shifting, switching timescales, and energy storage ability are possible with careful host material, ion, and electromagnetic unit cell design

Single Event Functional Interrupt (Sefi) Characterization of Cots and Radiation Hardened Arm Microcontrollers

This work evaluated the single event functional interrupt (SEFI) response of the commercial-off-the-shelf (COTS) and radiation hardened Cortex-M4 (M4) microcontrollers with the Armv7-M ISA. The microcontrollers were exposed to 200 MeV protons. The COTS M4 was further evaluated under carbon ions and alpha particles to assess if the control bits that depend on the software could have a significant influence on the SEFI cross section for this ISA. The SEU results show that both microcontrollers can experience multiple-cell upsets (MCUs), which could facilitate the accumulation of multiple-bit upsets (MBUs). MBUs could be a concern even for radiation hardened systems with ECC, because ECC crashes the system (SEFI) to correct MBUs

Analyzing the Field Force Volunteer Program at the U.S. Military Academy at West Point

Leadership and Learning in Organizations capstone projectIn recent years, there has been a decline in the number of qualified applicants applying and accepting an offer of admission to the U.S. Military Academy at West Point. This trend aligns with an 8-year decline in U.S. college enrollment, referred to as the enrollment cliff. This project explores how the Field Force, a volunteer group of West Point alumni and affiliates, can be optimally utilized in the admission process to increase the number of qualified applicants applying and accepting admission. With over 700 members, the Field Force program consists of highly committed and dedicated volunteers uniquely positioned to optimize admission efforts. However, the ongoing implementation of the Field Force program faces several challenges that may hinder the program’s effectiveness. Using interviews (N=12) and surveys adapted from the Volunteer Satisfaction Index and Mentoring Competency Assessment, Field Force volunteers were queried (N=381, 63% survey response rate) about their experience, abilities, and promising practices. Descriptive statistics and deductive and inductive coding were used to analyze the responses. Eight primary outcomes involving the volunteers' autonomy, values, competencies, and connections with prospective cadets reflect the findings of this project. Proposed recommendations include formalizing the program's purpose and goals, improving volunteer training, and implementing a volunteer appreciation program. As the number of qualified applicants declines, the commitment to fostering community and supporting prospective cadets will be essential in navigating the complexities of the current college enrollment landscape

Weak Ties and Strong Allies: Improving Alumni Engagement through Critical Social Network Analysis

Leadership and Learning in Organizations capstone projectThe development department at a top tier, small, private research university recruits alumni volunteers to serve as fundraisers for their respective reunion year giving campaigns. The recently admitted and graduating classes have been shifting demographically, but strategies for soliciting alumni engagement remain largely the same. A mixed methods approach was used to conduct descriptive, non-parametric and social network analyses on alumni demographic and giving data from the 2023 reunion campaign, and interviews were employed to assess organizational affinity, group dynamic and social connections. Findings revealed: alumni volunteer committees reflect their graduating cohorts less and less with time, there’s a need for more robust peer connection data to identify more diverse alumni volunteers in more recent cohorts, and staff turnover in the development department negatively impacts both staff and alumni

A Case for Disability Leadership in Southwest Pennsylvania

Leadership and Learning in Organizations capstone projectThis project on disability justice examines the landscape of leadership by persons with disabilities. In primary partnership with Pittsburgh, PA-based FISA Foundation, which partnered with Chicago, IL-based Disability Lead, we investigate the opportunity to expand a disability-focused leadership development program (LDP) to Southwest Pennsylvania (SWPA). A review of extant literature revealed themes of barriers to leadership. As the literature failed to address persons with disabilities as leaders, we introduce a framework for disrupting the social model of disability by illustrating a ceiling of leadership expectations. Examination and coding of over 150 pages of documentation from interviews, focus groups, FISA Foundation meetings, and Disability Lead program curricula exposed four findings. The findings indicate FISA Foundation is well established in SWPA to launch a disability-focused LDP. They must act as a convener to align other advocacy groups towards a common goal, identify additional support within the community to serve as mentors, intentionally design the program to ensure physical accommodation and remove financial barriers, and forge partnerships within the business sector for financial support. The findings suggest that barriers to leadership by persons with disabilities exist at the societal level. To overcome barriers, individuals from the disability community must be deliberately and purposefully positioned as leaders at a societal level, not just within the sector serving individuals with disabilities

The miR-23-27-24 Clusters Drive Lipid-Associated Macrophage Proliferation in Obese Adipose Tissue

Identifying molecular circuits that control adipose tissue macrophage (ATM) function is necessary to understand how ATMs contribute to tissue homeostasis and obesity-induced insulin resistance. In this study, we found that mice with a myeloid-specific knockout of the miR-23-27-24 clusters of miRNAs gained less weight on a high-fat diet but exhibited worsened glucose and insulin tolerance. Analysis of ATMs from these mice revealed selectively reduced numbers and proliferation of a recently reported subset of lipid-associated CD9+Trem2+ ATMs (LAMs). Leveraging the role of miRNAs to control networks of genes, we used RNA sequencing, functional screens, and biochemical assays to identify candidate target transcripts that regulate proliferation-associated signaling. We determined that Eif4ebp2 is a direct target of miR-23, which we found to inhibit protein synthesis and proliferation in macrophages. Altogether, our study demonstrates that control of proliferation of a protective subset of LAMs by noncoding RNAs contributes to protection against diet-induced obesity metabolic dysfunction