Tang, M. (STAT) – Bayesian Modeling and Scalable Inference for Count Time Series in Infectious Disease Surveillance
Engineering 2 Engineering 2 1156 High Street, Santa Cruz
Hybrid Event
7 events found.
Week of Events
Monday, June 15, 2026
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Hybrid EventJune 15, 2026Tang, M. (STAT) – Bayesian Modeling and Scalable Inference for Count Time Series in Infectious Disease Surveillance
Hybrid Event
Tang, M. (STAT) – Bayesian Modeling and Scalable Inference for Count Time Series in Infectious Disease Surveillance
Real-time monitoring of infectious disease outbreaks calls for statistical models that recover interpretable quantities such as the time-varying reproduction number from noisy count data, track posterior uncertainty, and run on time scales compatible with daily updates. Existing methods address these aims through separate model classes. Discretized Hawkes processes, Poisson autoregressions, and distributed lag models each […]
Tuesday, June 16, 2026
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Wednesday, June 17, 2026
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Thursday, June 18, 2026
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Virtual EventJune 18, 2026Carrión, H. (CSE) – Deep Learning Algorithms for Medical Image Representation Learning and Understanding
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Virtual EventJune 18, 2026Wang, Z. (CSE) – From Static Alignment to Adaptive Safety: Toward Reliable and Capable AI Systems
Virtual Event
Carrión, H. (CSE) – Deep Learning Algorithms for Medical Image Representation Learning and Understanding
AI-assisted clinical decisions in medicine, and particularly in dermatology, demand fine-grained understanding across diverse skin tones, body sites, and disease types, yet expert-annotated datasets are scarce, demographically imbalanced, and almost devoid of rare presentations. This dissertation develops four deep learning systems for this low-label, low-coverage regime. We introduce HealNet, which learns wound healing stages from […]
Virtual Event
Wang, Z. (CSE) – From Static Alignment to Adaptive Safety: Toward Reliable and Capable AI Systems
Modern AI systems are rapidly moving beyond static text generation toward capable models and agents that reason, use tools, store memories, and update persistent state, yet safety methods still often assume a fixed model whose behavior can be controlled by output-level refusal. This leaves critical gaps in understanding why aligned models fail under adversarial pressure, […]
Friday, June 19, 2026
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Saturday, June 20, 2026
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Sunday, June 21, 2026
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