Audience: Alumni
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Leavitt, J. (BMEB) – Evolutionary Dynamics, Functional Adaptations in Stress Response, and Direct Detection of tRNA modifications in Archaea
Transfer RNA (tRNA) modifications are essential for structural integrity, decoding fidelity, and stress adaptation, yet their dynamics across phylogenetically distinct archaeal species and their functional roles during stress remain incompletely […]
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Bhatia, N. (CSE) – Building Adaptive Intelligence into Wireless Sensing
WiFi-based indoor positioning is a widely researched area focused on determining the location of devices. Accurate indoor positioning has numerous applications, including asset tracking and indoor navigation. Despite advances, their […]
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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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Lei, K. (CMPM) – Designing for Meaningful Large-Scale Online Communication, Connection, and Collective Insight
Digital technologies have made large-scale online interaction a central part of how people communicate, connect, and work together. Yet scaling often comes at the cost of depth, and interactions can […]
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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 […]