Audience: Alumni
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Swaby, A. (ECE) – Improving X-ray Medical Imaging using Amorphous Selenium as a Photoconductive Layer
The presence of coronary artery calcification is a strong predictor for future cardiovascular events where cardiac risk categories are quantified depending on calcification size. Dual-energy chest X-rays provide high contrast […]
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HireUC Alumni Career Fair
The HireUC Alumni Career Fair is a hiring event designed for University of California alumni who are looking for early-and mid-level career opportunities. It offers a special chance for alumni […]
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Osorio, S. (AM) – Image-Based Wound Infection Classification
This thesis investigates the use of deep learning for classifying wound infections from photographic images, using colony-forming unit (CFU) counts as a quantitative labeling standard. Leveraging the visual information in […]
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Briden, M. (CSE) – Representation Learning and Generative Forecasting for Noisy and Limited Clinical Data: Applications in Wound Healing and EEG
The rapid integration of artificial intelligence and machine learning into clinical practice has driven advances in disease classification, segmentation, and clinical decision support. However, the complexities of medical data pose […]
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Vats, V. (CSE) – Learning to Remember: Multi-Agent Self-Refinement toward Persistent Machine Perception
Modern machine perception is powerful yet brittle: failing in response to subtle data adversaries and lacking mechanisms to learn from their errors. We address this challenge by progressing from diagnosing […]
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Moreland, Z. (AM) – Transcriptomic and Computational Analysis of Burn and Excisional Wound Healing
Accurate assessment of wound healing progress is critical for optimizing patient care and preventing complications, yet clinicians currently lack precise tools to determine where a wound stands in the healing […]
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Mawhorter, R. (CSE) – Certified Synthesis for Interactive Media: High Assurance Metroidvania Generation
Program verification has been applied in many contexts (including videogames), but the scale and complexity of the examples that have been analyzed fall short of the ability to analyze many […]
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Managing Your Time and Increasing Your Productivity Webinar
It seems we always have too much to do at work in too little time. Join us as we explore innovative approaches to thinking and operating, while also engaging with […]
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Model Context Protocol: Why It Matters
The Impact of Model Context Protocol Join us for an engaging exploration of the Model Context Protocol—a groundbreaking framework designed to improve communication and context-sharing across AI agents. As AI […]
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Asefi, N. (ECE) – Generative Lagrangian Data Assimilation for Ocean Dynamics under Extreme Sparsity
Reconstructing ocean dynamics from observational data is fundamentally limited by the sparse, irregular, and Lagrangian nature of spatial sampling, particularly in subsurface and remote regions. This sparsity poses significant challenges […]