Transcriptomic profiling has been transformative in pediatric oncology. Pediatric cancers arise from disrupted developmental programs. Their impaired transcriptional states reflect cell lineage infidelity, aberrant differentiation, and immune-microenvironment interactions distinct from […]
Today, both individual and collective memories are increasingly mediated by digital platforms. Both are fundamentally enmeshed in platform ecosystems that orient around commercial imperatives very much at odds with community […]
Title: Understanding the advising praxes central to student success at a four-year Hispanic-Serving Research Institution Presenter: Dr. Lydia Iyeczohua Zendejas Location: Via Zoom (link provided via RSVP) Abstract: Higher education scholars increasingly recognize academic advising as a critical strategy for supporting the persistence of systemically marginalized students. Since the 1990s, UC Santa Cruz has undergone […]
GPUs are the workhorses of modern AI, widely deployed and developed by many vendors including Apple, Qualcomm, Intel, AMD, and NVIDIA. While these GPUs all offer high compute potential, programming […]
We present a comprehensive numerical investigation examining how vertical asymmetry in compressible convection affects overshooting and the transport of large-scale magnetic fields from convective to stably stratified regions. Using three-dimensional direct numerical simulations, we systematically vary the superadiabaticity and stratification of a convective layer to control the vertical asymmetry of the flow and analyze its […]
Diffusion-based text-to-image models can generate impressive images, but they largely treat an image as a single, flat output, which makes precise editing of individual elements difficult. This proposal studies layered […]
Vision encoders have demonstrated significant performance gains in visual generation and multimodal reasoning. These improvements are primarily attributed to the scaling of data, model capacity, and compute. However, this progress […]
The Huerta Center is proud to present a brown bag presentation by Graduate Student Research Awardee Valeria Alonso Blanco. She will present on a qualitative study that explores how undocumented Latinx transfer students navigate institutional support, belonging, and barriers at a four-year Hispanic Serving Institution (HSI). Findings reveal gaps between institutional commitments and student […]
Diffusion-based generative models offer a principled framework for probabilistic forecasting, but we show they suffer from a fundamental spectral collapse when applied to turbulent flows. A Fourier-space analysis of the […]
Anonymous communication systems hide who is talking to whom, not just what is said. However, existing systems are either vulnerable to traffic analysis attacks–attacks where adversaries observe and correlate the network traffic of users–or are forced to rely on unrealistic and unenforceable assumptions about how users behave. Worse, existing theory lacks tools to rigorously model […]
Machine unlearning addresses the “right to be forgotten” under GDPR and enables privacy, copyright, and safety compliance in large language models. Training-based unlearning can remove targeted behavior on benchmarks, but […]
Game balance is a term widely used among players, researchers, and designers of games. It is a concept that feels vitally important to how we make and play games – […]
Modern edge computing increasingly relies on heterogeneous System-on-Chip (SoC) architectures. These chips tightly integrate general-purpose CPUs with various specialized accelerators, including GPUs, FPGAs, and AI accelerators, all under a shared […]
Children’s lives are now inextricably linked with AI-driven digital systems that shape learning, social interaction, and development. This has elevated child online safety to a central concern for families, policymakers, […]
Artificial neural networks can now learn to play games, control robots, generate language, and solve complicated reasoning tasks, yet we still lack a clear understanding of how to directly guide […]
End-to-end neural generation models have largely displaced the modular architectures that once gave dialogue system designers explicit control over what is said and how it is said. While these models produce fluent text, they collapse content planning, sentence planning, and surface realization into a single undifferentiated decoding step, sacrificing the controllable structure that earlier systems […]
Alzheimer’s disease (AD) is a progressive neurodegenerative disorder and a leading cause of dementia. Neuroimaging and clinical biomarkers can reveal early disease changes, but building reliable machine learning models is […]
Current generative vision models struggle with image customization that requires multi-step reasoning or real-world knowledge. This proposal introduces generalized image customization, enabling systems to execute complex, inferential modifications rather than just simple edits. The research focuses on the foundational framework required for this generalization, specifically high-quality training data, scalable evaluation benchmarks, self-improving training paradigms that […]
As multimodal artificial intelligence systems become increasingly embedded in everyday technology, there is a growing need to design human-centered AI agents that support and amplify human capabilities rather than replace them. This dissertation investigates how to build human-centered multimodal AI agents, framing human-centeredness as an agent-level objective that requires both accessible, assistive interaction and reliable, […]
Advanced driver-assistance systems (ADAS) are commonly organized as modular pipelines that transform raw sensor measurements into low-level actuation commands through perception, planning, and control. While learning-based methods have achieved state-of-the-art performance in perception and environment modeling, the planning layer remains a key bottleneck for reliable autonomy. Highway driving in particular requires long-horizon reasoning and socially […]