Nikolakakis, M. (ECE) – Learned Gridless Representations of Cone Beam Computed Tomography Scans
Engineering 2 Engineering 2 1156 High Street, Santa Cruz
Hybrid Event
7 events found.
Condon, C. (BMEB) – Genomic conflict across scales
Biomedical Sciences Building 575 McLaughlin DriveWeek of Events
Monday, August 17, 2026
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Hybrid EventAugust 17, 2026Nikolakakis, M. (ECE) – Learned Gridless Representations of Cone Beam Computed Tomography Scans
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August 17, 2026Condon, C. (BMEB) – Genomic conflict across scales
Hybrid Event
Nikolakakis, M. (ECE) – Learned Gridless Representations of Cone Beam Computed Tomography Scans
Medical image representation has long been dominated by voxel-grid matrices. While their inherent structure and order work efficiently for various linear transformations and provide a seamless visualization method on monitors, they fail to preserve the topology of the scan and to encode sparse information in a memory-efficient way. The recent emergence of machine learning-based continuous coordinate-based […]
Condon, C. (BMEB) – Genomic conflict across scales
Genomes are often viewed as cooperative systems in which genes work together to support organismal function. Yet genetic elements can also act in ways that favor their own transmission or persistence, creating conflict within the genome. In this talk, I examine the evolutionary and functional consequences of such genomic conflict across three systems. First, I […]
Tuesday, August 18, 2026
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Virtual EventAugust 18, 2026Gutie, J. (SciCAM) – SORh: Hyperbolic Relaxation Methods For Elliptic Problems In Computational Fluid Dynamics
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Hybrid EventAugust 18, 2026Lupin-Jimenez, L. (AM) – Data-Driven Deep Learning for Turbulent Phenomena: Regional Ocean Prediction and Assimilation, Spectral Bias in Diffusion Models, and Equation Discovery
Virtual Event
Gutie, J. (SciCAM) – SORh: Hyperbolic Relaxation Methods For Elliptic Problems In Computational Fluid Dynamics
This thesis explores iterative methods for solving elliptic partial differential equations (PDEs), which are used in computational fluid dynamics (CFD) to model a wide range of physical phenomena. The primary application of interest here is self-gravity, modeled by Poisson’s equation. Although many numerical approaches exist, including direct matrix inversion, FFT-based methods, and classical iterative methods […]
Hybrid Event
Lupin-Jimenez, L. (AM) – Data-Driven Deep Learning for Turbulent Phenomena: Regional Ocean Prediction and Assimilation, Spectral Bias in Diffusion Models, and Equation Discovery
Deep learning models trained on simulation and reanalysis data can now emulate turbulent geophysical flows at a small fraction of the computational cost of numerical solvers. Their scientific utility depends on physical consistency, which for the systems studied here rests in large part on spectral fidelity, the accurate reconstruction of variance across spatial scales. This […]
Wednesday, August 19, 2026
No events on this day.
Thursday, August 20, 2026
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Hybrid EventAugust 20, 2026Penunuri, G. (BMEB) – Genomic, Proteomic, and Computational Approaches to the Study of Host-Microbe Systems
Hybrid Event
Penunuri, G. (BMEB) – Genomic, Proteomic, and Computational Approaches to the Study of Host-Microbe Systems
Host-microbe systems are core to some of biology’s most consequential interactions, from the pathogens that drive infectious disease to symbionts affecting agricultural pest control and vector-borne disease transmission. Yet unlike the model organisms that have driven most of modern molecular biology, the microbes at the center of these interactions are rarely genetically tractable: many cannot […]
Friday, August 21, 2026
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Hybrid EventAugust 21, 2026Nava, A. (AM) – Machine-Learning Methods for Prediction of Biological Systems
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Virtual EventAugust 21, 2026Huang, X. (CSE) – Scalable and Verifiable Reasoning for Medical Foundation Models
Hybrid Event
Nava, A. (AM) – Machine-Learning Methods for Prediction of Biological Systems
Advances in microscopy have enabled the collection of high-quality single-cell datasets, providing new opportunities to identify the mechanisms underlying complex biological processes. In this work, we develop machine-learning frameworks using single-cell temporal data with the goal of predicting and providing insights into these mechanisms. We produce frameworks for two biological systems, bacterial spore germination, the […]
Virtual Event
Huang, X. (CSE) – Scalable and Verifiable Reasoning for Medical Foundation Models
This PhD research focuses on developing reliable medical foundation models capable of reasoning across textual, visual, and interactive clinical information. The work investigates three complementary directions: improving medical reasoning through test-time scaling, training multimodal medical models with verifiable rewards, and synthesizing high-quality visual question-answering data from biomedical literature using generator-verifier frameworks. Building on these efforts, […]
Saturday, August 22, 2026
No events on this day.
Sunday, August 23, 2026
No events on this day.