Simulation is a coinductive proof technique to assert the behavioral equivalence of computing systems that has seen fruitful application in distributed systems, concurrent process calculi, and programming languages, since the […]
In this work, we develop numerical methods for conservation laws that explore statistical, structure-preserving, and machine-learning-based approaches, each built on top of traditional numerical solvers. First, we develop a general […]
Hardware design flows have become increasingly complex as modern chips integrate billions of transistors and rely on aggressive synthesis optimizations to meet performance, area, and power targets. While these transformations […]
Modern applications, such as data center workloads, have become increasingly complex. These applications primarily operate on massive datasets, which involve large memory footprints, irregular access patterns, and complex control and […]
Reinforcement Learning (RL) is a machine learning paradigm that trains a decision maker, or policy, by learning from interaction with an environment. The power of RL lies in its ability […]
Transient execution attacks are serious security threats in modern-day processors. Out-of-order execution compels the processor to access data that should not be otherwise perceived. Leakage of that secret information creates […]
The growing integration of Large Language Models (LLMs) into real-world applications has heightened concerns about their trustworthiness, as models may reveal private information, reproduce copyrighted content, propagate biases, or generate […]
While Large Language Models exhibit remarkable capabilities, their reliance on the standard Transformer architecture imposes prohibitive computational costs and quadratic memory complexity. To bridge the gap between biological efficiency and […]
Quantum Key Distribution (QKD) provides information-theoretic security for cryptographic key establishment, but existing protocols exhibit limited noise tolerance, restricting their applicability in practical quantum channels with finite resources. This work […]
Translation is a central and highly regulated step of gene expression, yet there are few quantitative, high-throughput tools to study translation. Existing methods such as sucrose gradients provide only bulk […]
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 […]
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 […]
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 […]
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 […]