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SUMMARY:Graduate Preparation Program
DESCRIPTION:The Graduate Preparation Program (GPP) is a four-week intensive non-credit course offered in person on the main campus prior to the fall quarter\, which is open to all current and newly admitted international graduate students. It focuses on English for Academic Purposes (EAP)\, academic skills\, and cultural orientation. The program also provides a foundation for transitioning into the Teaching Assistant role. \nThe course offers guided support with: \n\nSeminar-style classroom discussion\nPresentation and oral communication skills\nInformation on U.S. classroom culture; roles and responsibilities of faculty\, Teaching Assistants\, and students\nCritical thinking: using evidence to support ideas\nResearch writing\, citation\, and avoiding plagiarism\nCollaborative and project-based learning\n\nA collaboration between the Graduate Division and Global Engagement\, the Graduate Preparation Program provides a strong foundation for the U.S. classroom environment and university system\, in addition to the opportunity to practice and master the language and academic skills needed for success. \nFor more information and to register\, please visit our webpage.
URL:https://events.ucsc.edu/event/graduate-preparation-program/
CATEGORIES:Conference,Lectures & Presentations
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DTSTART;TZID=America/Los_Angeles:20260817T100000
DTEND;TZID=America/Los_Angeles:20260817T120000
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SUMMARY:Nikolakakis\, M. (ECE) - Learned Gridless Representations of Cone Beam Computed Tomography Scans
DESCRIPTION:Medical image representation has long been dominated by voxel-grid matrices. While\ntheir inherent structure and order work efficiently for various linear transformations and\nprovide a seamless visualization method on monitors\, they fail to preserve the topology\nof the scan and to encode sparse information in a memory-efficient way.   The recent emergence of machine learning-based continuous coordinate-based\nscene representations such as neural radiance fields and Gaussian splatting has provided alternative representation techniques. These approaches overfit the weights of\na model by iterative differentiable rendering and have been shown to be more compact than grid representations. They are then able to perform novel view\nsynthesis from any given camera pose.\nOff-grid representations translate directly to Cone Beam Computed Tomography\nsparse-view acquisitions\, where streaking and quantum noise artifacts are dominant.\nUsing differentiable rendering\, a continuous representation is achieved\, with interpolation providing a path to recover some of the lost signal.\nIn this dissertation\, we apply a variety of methodologies\, including Gaussian splatting\, implicit occupancy fields\, and Neural Attenuation Fields regularized with an\nanatomic prior\, to Cone Beam Computed Tomography reconstruction\, and evaluate\ntheir performance across a range of anatomic datasets. Our models show that learned\ngridless representations achieve substantial memory reduction\, recover signal under\nextreme view sparsity\, and preserve scene topology. \nEvent Host: Manolis Nikolakakis\, Ph.D. Candidate\, Electrical and Computer Engineering  \nAdvisor: Razvan Marinescu \nZoom: https://ucsc.zoom.us/j/5964517596?pwd=c1AwRlJLNk5pVzFBUENibEw3by85Zz09
URL:https://events.ucsc.edu/event/nikolakakis-m-ece-learned-gridless-representations-of-cone-beam-computed-tomography-scans/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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DTSTART;TZID=America/Los_Angeles:20260817T130000
DTEND;TZID=America/Los_Angeles:20260817T150000
DTSTAMP:20260813T194341Z
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SUMMARY:Condon\, C. (BMEB) - Genomic conflict across scales
DESCRIPTION: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 investigate segregation distortion in Arabidopsis hybrids and its potential role in the early evolution of reproductive isolation. Second\, I characterize the population dynamics and functional effects of introners\, mobile elements that generate new introns in the green alga Micromonas pusilla. Finally\, I explore widespread splicing dysfunction in algal mating-type chromosomes and its consequences for transcript diversity. Together\, these studies highlight how departures from genome cooperation can shape inheritance\, genome evolution\, and gene regulation. \nEvent Host: Chris Condon\, Ph.D. Candidate\, Biomolecular Engineering & Bioinformatics  \nAdvisor: Russell Corbett-Detig
URL:https://events.ucsc.edu/event/condon-c-bmeb-genomic-conflict-across-scales/
LOCATION:Biomedical Sciences Building\, 575 McLaughlin Drive
CATEGORIES:Ph.D. Presentations
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DTSTART;TZID=America/Los_Angeles:20260817T180000
DTEND;TZID=America/Los_Angeles:20260817T190000
DTSTAMP:20260730T192605Z
CREATED:20260730T192605Z
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SUMMARY:Build better chips
DESCRIPTION:Join us for an interactive discussion on current industry trends\, emerging skills\, and career opportunities\, and learn how our Silicon Chip Design & Semiconductor Engineering courses are designed to help professionals build expertise\, stay competitive\, and achieve their educational and career goals. \nWhether you’re looking to advance in your current role\, transition into a new field\, or expand your knowledge\, this session is a great place to start. \nYour speaker\nArvind Vidyarthi –  M.S.E.E. is vice president of Silicon Design Engineering at Altera\, where he leads SoC and IP physical design implementation\, methodology\, and automation. Arvind has served since 2022 as chair of the UCSC Silicon Valley Extension Silicon Chip Design & Semiconductor Engineering program\, where he also sits on the VLSI engineering advisory group and mentors the next generation of design engineers. \nKeep learning\nThe Silicon Chip Design & Semiconductor Engineering program presents this information session. Visit our program page for complete program details and a closer look at all upcoming courses. \nClaim your seat today. 
URL:https://events.ucsc.edu/event/build-better-chips-2/
LOCATION:Silicon Valley Campus\, 3175 Bowers Avenue\, Santa Clara\, CA\, 95054\, United States
CATEGORIES:Lectures & Presentations,Meetings & Conferences,Training
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