One of the central challenges in quantum computing is finding or approximating the ground-state energy of a local Hamiltonian, a quantum analogue of classical constraint satisfaction problems (CSPs). Among these, […]
Miniaturized spectrometers have the potential to replace bulky and expensive benchtop models. We have previously demonstrated a multimode interference (MMI) waveguide-based spectrometer that achieves high performance while minimizing its footprint. In this talk, the integration of the MMI spectrometer into an optofluidic device is proposed. This integration opens up applications such as the detection of […]
Organoids are three-dimensional tissue cultures that model real organs and serve as valuable tools for studying development, disease, and treatment response. Traditional methods, which rely on manual handling and incubators, limit consistency and real-time monitoring. To address these issues, we developed a modular microfluidic platform that integrates automated feeding, live fluorescence imaging, and environmental control […]
Most optimization problems face the challenge of computing an optimum solution requiring superpolynomial time. In particular, they are classified as NP-hard problems that have no polynomial-time algorithm to date. Instead, computer scientists turn to find an approximate solution and create numerous elegant algorithms. However, in the modern era, computational environments have changed drastically, and we […]
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 1970’s. We have also utilized simulation in our prior work, where we formalized and proved a folklore claim that the state-based and operation-based approaches to […]
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 Gaussian-process-based “recipe’’ for constructing high-order linear operators such as interpolation, reconstruction, and derivative approximations. Building on this recipe, we derive a kernel-agnostic convergence theory for […]
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 improve circuit efficiency, they also erase the correspondence between gate-level netlists and their originating HDL source lines. The loss of traceability makes post-synthesis debugging, timing […]
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 data flows. The processor-memory speed gap, combined with these complexities, can lead to unexpected performance inefficiencies in these applications, preventing them from achieving optimal performance. […]
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 to learn complex strategies without explicit human instruction, which can lead to better solutions that human designers overlook in domains ranging from robotics to scientific […]
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 a covert channel for the attacker for various types of transient and speculative attacks. Transient based execution attacks emanate when the secret information is leaked […]
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 harmful instructions. These risks, alongside emerging privacy regulations, motivate the need for LLM unlearning, methods that remove the influence of specific data while preserving overall […]
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 high-performance AI, we have established foundational work in linearizing attention and maximizing hardware utilization through architectures such as RWKV and MatMul-Free networks. Addressing the remaining […]
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 introduces a QKD protocol based on entanglement swapping that significantly enhances error tolerance and key generation rates. The protocol encodes six-bit classical symbols into six-qubit […]
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 ribosome counts, while Ribo-Seq offers positional information in the genome but destroys long-range structure and transcript expression information. Because of these limitations, many fundamental questions […]
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 those of adult tumors(Gröbner et al., 2018; X. Ma et al., 2018). Within the osteosarcoma (OS) landscape, despite being the most common bone tumor of […]
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 cohesion. The digital archive where our mediated memories are stored does not merely store information but actively inscribes it, often privileging narratives aligned with commercial […]
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 them effectively is difficult because they differ in performance-critical features like SIMT width, cache capacity, and memory bandwidth, demanding different optimization strategies. Tunable kernels address […]
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 generative representations that align with professional editing workflows, enabling users to manipulate foreground objects while preserving the rest of the scene. A central focus is […]