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DTSTART;TZID=America/Los_Angeles:20250821T110000
DTEND;TZID=America/Los_Angeles:20250821T110000
DTSTAMP:20260422T150412
CREATED:20250730T070000Z
LAST-MODIFIED:20250925T231624Z
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SUMMARY:HireUC Alumni Career Summit
DESCRIPTION:About the career summit \nThe HireUC Alumni Career Summit\, in partnership with Hire Talent\, is a hiring event organized for University of California (UC) alumni who are looking for early- and mid-level career opportunities. It offers a special chance for alumni to connect with employers from diverse fields and industries.
URL:https://events.ucsc.edu/event/hireuc-alumni-career-summit/
CATEGORIES:Exhibits,Lectures & Presentations
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DTSTART;TZID=America/Los_Angeles:20250821T120000
DTEND;TZID=America/Los_Angeles:20250821T120000
DTSTAMP:20260422T150412
CREATED:20250815T070000Z
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SUMMARY:HireUC Alumni Career Fair
DESCRIPTION: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 to connect with employers from diverse fields and industries. Alumni from all 10 UC campuses are invited. UC alumni can attend the fair for free\, but it’s important to register in advance to secure participation.  \nAbout Hire Talent \n\nSince 2014\, over 100\,000+ attendees to Hire Talent Events\nCreated 1\,000s of new careers\n50% bachelors / 40% masters / 10% doctorate\nAverage experience of attendees: 6 years\n500+ University Partners\n25 Cities\n\nQuestions \n\nJeffrey Nortman jeff@gohiretalent.com\nPatricia Nguyen\, Director of Systemwide UC Santa Cruz Alumni & Diversity Initiatives patricia.nguyen@ucop.edu\n\nEmployers \nIf you work for a company looking to connect with alumni from the University of California graduating from various majors\, degrees and career levels\, please use the Employer Registration tab to get participate as a recruiter.  Employer registration is open to all employers not just UC Alumni.
URL:https://events.ucsc.edu/event/hireuc-alumni-career-fair/
CATEGORIES:Meetings & Conferences,Training
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DTSTART;TZID=America/Los_Angeles:20250821T130000
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DTSTAMP:20260422T150412
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SUMMARY:Briden\, M. (CSE) -  Representation Learning and Generative Forecasting for Noisy and Limited Clinical Data: Applications in Wound Healing and EEG
DESCRIPTION: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 a challenge to widespread adoption. The rarity of medical conditions\, ethical considerations\, and varying acquisition protocols leads to limited and noisy data. The time-intensive process of labeling data\, the high degree of accuracy required in clinical settings\, and the ill-defined nature of certain medical conditions further complicate the application and deployment of machine learning models. Likewise\, high‐stakes medical decisions demand trustworthy and interpretable predictions. However\, prioritizing trust and explainability is rarely a primary objective in most model designs. \nThis thesis addresses three key challenges in machine learning for healthcare. First\, we develop methods for learning under noisy and limited medical data\, focusing on representation learning strategies that improve generalization when datasets are small or contain mislabeled samples. Second\, we explore the prediction of generative outcomes amid label noise and data scarcity\, utilizing parameter-efficient and temporal generative models to forecast disease trajectories. Third\, we advance trustworthy and explainable medical artificial intelligence by designing deep architectures that provide interpretable outputs suitable for clinical decision-making. \nThese challenges are addressed in the context of two complementary medical modalities: wound healing images and electroencephalogram signals. Wound healing tasks focus on predicting healing trajectories while enhancing interpretability through segmentation-based explanations and training large models in light of extreme data noise and scarcity. Electroencephalogram-based tasks emphasize representation learning and explainability for non-invasive mental state classification. These experiments demonstrate the clinical relevance of the proposed approaches and their ability to operate under challenging medical conditions across both imaging and physiological signal domains. \nEvent Host: Michael Briden\, PhD Candidate\, Computer Science & Engineering \nAdvisor: Narges Norouzi
URL:https://events.ucsc.edu/event/briden-m-cse-representation-learning-and-generative-forecasting-for-noisy-and-limited-clinical-data-applications-in-wound-healing-and-eeg/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
GEO:37.0009723;-122.0632371
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DTSTART;TZID=America/Los_Angeles:20250821T180000
DTEND;TZID=America/Los_Angeles:20250821T180000
DTSTAMP:20260422T150412
CREATED:20250626T070000Z
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SUMMARY:Regulatory Affairs and Medical Device Quality and Design – Fall Info Session
DESCRIPTION:Explore medical innovation with Kiran Gulati\nJoin medical device and biotech expert Kiran Gulati for a closer look at UCSC Silicon Valley’s Regulatory Affairs and Medical Device Quality and Design certificates. These programs equip you to navigate global regulations and bring safe\, effective products to market. \nBuild in-demand skills in a regulated field\nLearn FDA negotiation\, risk management\, and quality system standards like ISO 13485 and 14971. Whether you're aiming for RAC certification or advancing your career in biotech\, this session will highlight how these programs prepare you for success in the fast-moving healthcare industry. \nThis fall info session is sponsored by the Regulatory Affairs and Medical Device Programs.
URL:https://events.ucsc.edu/event/regulatory-affairs-and-medical-device-quality-and-design-fall-info-session/
CATEGORIES:Lectures & Presentations,Meetings & Conferences,Training
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