Autonomous systems, such as Autonomous Vehicles (AVs) and drones, are increasingly deployed across a wider array of contexts for both civilian and military use. As these systems become more common, they may be targeted by malicious actors seeking to exploit and abuse them, compromising safety-critical operations. Among the ways to protect these systems simulation based […]
A central goal on the path toward general AI is to build systems capable of deliberative reasoning before action. Such systems should inspect what they know, identify what they need, seek or construct useful information, and revise their reasoning through intermediate cognitive states. This dissertation studies this goal through the lens of Inner Monologue (IM), […]
This dissertation investigates how to make modern AI systems safer as they grow more capable. It addresses two central sources of risk: malicious misuse, in which adversarial users coerce models into harmful behavior, and internal misalignment, in which models themselves pursue goals that diverge from human intent through deception, sandbagging, or other covert behaviors. The […]
Electrochemical impedance spectroscopy (EIS) is the workhorse measurement behind lithium-ion battery diagnostics, biosensing, and corrosion science — yet no integrated circuit has ever delivered the complete capability of a benchtop analyzer on a single die. This dissertation presents ISoC, the first universal Impedance Spectroscopy instrument-on-chip. Designed in SkyWater 130 nm CMOS process, ISoC supports all […]
This dissertation investigates how neuromorphic and brain-inspired principles can guide the design of efficient neural language architectures. It addresses two central limitations of modern Transformer-based language models: memory growth with context length and high computational cost from dense matrix multiplication. Through studies of spiking neural networks, linear-recurrent language models, hybrid attention architectures, MatMul-free models, and […]
Recently, a class of non-invasive hardware side-channel attacks has been discovered in field-programmable gate arrays (FPGAs). These attacks extract remnants of prior users’ activity that persist as transistor defect states […]
Ion transfer as the movement of charged species across spaces and interfaces is the basis of signaling in nearly all biological systems. My research is grounded in the idea that […]
The electric grid is essential to modern society, and recent developments such as renewable energy sources (RESs), battery energy storage systems (ESSs), and microgrids (MGs) have necessitated novel computational methods for planning and operations. Machine learning offers a promising lever here, both as an accelerator for and proxy to traditional optimization-based problems. In this thesis, […]
Intracellular symbionts are microorganisms, such as bacteria, that live within host cells. These associations are widespread throughout the invertebrate tree of life, and can perform a diversity of key metabolic, […]
This event celebrates and highlights the work of UCSC graduate students in all academic divisions. Enrolled graduate students will present either a poster, talk, or mixed media presentation. Judges will […]
Centromeres ensure proper chromosome segregation during cell division, yet the organization and regulation of centromeric chromatin within satellite DNA arrays remain incompletely understood. Here, we leverage the complete diploid human […]
Cooperative two-player play produces distinctive social experiences between players: intimacy, trust, cooperation, communitas. Since Huizinga, the frame within which these experiences arise has been called the Magic Circle: a temporarily-set-apart […]
As quantum computing transitions from theory to practice, understanding which algorithms suit near-term devices becomes critical. Current quantum computers are severely constrained by limited qubit counts, short coherence times, and […]
Many genetics pipelines start by aligning sequencing reads to a reference genome. Aligners attempt to find the position in the reference sequence which best matches the read sequence, but this breaks down when the reads come from a sample with variation relative to the reference. A proposed alternative, pangenome graphs, is supposed to fix such […]
Self-reflection holds significant potential for learning, behavior change, and emotional processing, yet designing technologies that effectively support it remains challenging, particularly when reflection involves difficult experiences such as failure. Most current technologies avoid negative experiences altogether, leaving users without support at precisely the moments when reflection could be most valuable. This dissertation investigates how technology […]
The growing complexity of high-performance computing (HPC) systems poses a fundamental challenge for domain scientists, whose primary objective is to obtain scientifically valid results rather than to optimize resource utilization. […]
Modern high-performance GPU kernels increasingly rely on subgroup-level execution, including subgroup-level communication, subgroup operations, and matrix operations. These features are essential for workloads such as matrix multiplication and FlashAttention, but […]
Modern software increasingly relies on distributed systems to provide accessible, scalable, and reliable services. Choreographic programming brings a global perspective to distributed system development: programmers write a single program that […]
Edge computing and distributed AI systems increasingly operate under heterogeneous resources, dynamic workloads, and frequent failures, requiring both adaptivity and fault tolerance for efficient execution. In heterogeneous edge clusters, nodes […]
Real-time monitoring of infectious disease outbreaks calls for statistical models that recover interpretable quantities such as the time-varying reproduction number from noisy count data, track posterior uncertainty, and run on time scales compatible with daily updates. Existing methods address these aims through separate model classes. Discretized Hawkes processes, Poisson autoregressions, and distributed lag models each […]