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DTSTART;TZID=America/Los_Angeles:20251201T160000
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DTSTAMP:20260406T011153
CREATED:20251119T172305Z
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SUMMARY:AM Seminar: Denoising: A Powerful Building Block for Imaging\, Inverse Problems and Machine Learning
DESCRIPTION:Presenter: Peyman Milanfar\, Distinguished Scientist\, Google \nDescription: Denoising\, the process of reducing random fluctuations in a signal to emphasize essential patterns\, has been a fundamental problem of interest since the dawn of modern scientific inquiry. Recent denoising techniques\, particularly in imaging\, have achieved remarkable success\, nearing theoretical limits by some measures. Yet\, despite tens of thousands of research papers\, the wide-ranging applications of denoising beyond noise removal have not been fully recognized. This is partly due to the vast and diverse literature\, making a clear overview challenging. This article aims to address this gap. We present a clarifying perspective on denoisers\, their structure and their desired properties. We emphasize the increasing importance of denoising and showcase its evolution into an essential building block for complex tasks in imaging\, inverse problems and machine learning. Despite its long history\, the community continues to uncover unexpected and groundbreaking uses for denoising\, further solidifying its place as a cornerstone of scientific and engineering practice. \nBio: Peyman is a Distinguished Scientist at Google\, where he leads the Computational Imaging team. Prior to this\, he was a Professor of Electrical Engineering at UC Santa Cruz for 15 years\, two of those as Associate Dean for Research. From 2012-2014 he was on leave at Google-x\, where he helped develop the imaging pipeline for Google Glass. Over the last decade\, Peyman’s team at Google has developed several core imaging technologies that are used in many products. Among these are the zoom pipeline for the Pixel phones\, which includes the multi-frame super-resolution (Super Res Zoom) pipeline\, and several generations of state of the art digital upscaling algorithms. Most recently\, his team led the development of Pro Res Zoom\, and Unblur\, features launched in Pixel 10 devices and Google Photos. Peyman received his undergraduate education in electrical engineering and mathematics from the UC Berkeley\, and the MS and PhD degrees in electrical engineering from MIT. He holds more than two dozen patents. He founded MotionDSP\, which was acquired by Cubic Inc. Along with his students and colleagues\, his research work has had deep impact in several areas of computational imaging\, and applications of AI thereto – including the introduction of adaptive kernel regression to imaging; pioneering use of learning for fast\, content-adaptive image upscaling (RAISR); Neural Image quality Assessment (NIMA)\, Regularization by Denoising (RED); and most recently (2024) Inversion by Direct Iteration (InDI). All of these works have been recognized with best paper awards. He’s been a Distinguished Lecturer of the IEEE Signal Processing Society\, and is a Fellow of the IEEE “for contributions to inverse problems and super-resolution in imaging” \nHosted by: Professor Julie Simons\, Applied Mathematics \nZoom link: https://ucsc.zoom.us/j/93681175800?pwd=bgfPLQpTzs5PG4z3Qo2zbvMMScMAwn.1 \nMeeting ID: 936 8117 5800\nPasscode: 609643
URL:https://events.ucsc.edu/event/am-seminar-denoising-a-powerful-building-block-for-imaging-inverse-problems-and-machine-learning/
LOCATION:https://ucsc.zoom.us/j/93681175800?pwd=bgfPLQpTzs5PG4z3Qo2zbvMMScMAwn.1
CATEGORIES:Lectures & Presentations,Seminars
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DTSTART;TZID=America/Los_Angeles:20251203T110000
DTEND;TZID=America/Los_Angeles:20251203T123000
DTSTAMP:20260406T011153
CREATED:20251103T224713Z
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SUMMARY:When Less is More: Applications of Type-Based Underapproximate Reasoning
DESCRIPTION:Presenter: Suresh Jagganathan\, Purdue University\n\n\nAbstract:\nUnlike program verifiers\, symbolic execution and property-based testing tools underapproximate program behavior: they aim to report only real bugs (no false positives)\, at the cost of potentially missing some (false negatives). Recent work has sought to place such tools on a more formal footing\, primarily through the development of incorrectness logics that capture a program’s ‘must’ rather than ‘may’ behavior. This talk explores how to transplant these ideas of underapproximation into an expressive refinement type system. Our development enables us to:\n\n(a) Typecheck the completeness of property-based testing (PBT) generators\, ensuring that a well-typed generator produces all values (i.e.\, fully covers) its output type;\n\n(b) Synthesize effectful generators by extending the type system to model underapproximations of sequences of effects rather than just values; and\n\n(c) Guide symbolic execution in effectful functional programs\, prioritizing execution paths capable of falsifying data structure safety properties.\n\nOur results demonstrate that viewing types through the lens of underapproximation offers a principled foundation for designing\, implementing\, and reasoning about program analyzers and test generators\, significantly improving their reliability and practical utility in the process.\n\n\nBio:\nSuresh Jagannathan is the Samuel D. Conte Professor of Computer Science at Purdue University. His interests span functional programming\, program verification\, distributed and concurrent systems\, and trustworthy machine learning. In recent years\, he has spent time as an Amazon Scholar\, a program manager at the Information Innovoation Office (I2O) at DARPA\, and a visiting researcher at the University of Cambridge. He serves an Associate Editor of ACM TOPLAS\, and has served as both General and PC Chair of POPL (ACM Symposium on Programming Languages).\n\n\nHosted by: Professor Mohsen Lesani\n\n\nLocation: E2-180\n*Refreshments such as coffee and pastries will be provided\n\n\n\nZoom: https://ucsc.zoom.us/j/93445911992?pwd=YkJ2TQtF79h0PcNXbEcpZLbpK0coiY.1&jst=3
URL:https://events.ucsc.edu/event/when-less-is-more-applications-of-type-based-underapproximate-reasoning/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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DTSTART;TZID=America/Los_Angeles:20251203T115000
DTEND;TZID=America/Los_Angeles:20251203T131000
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SUMMARY:Applied Microeconomics and Trade Seminar Series presents: Matt Weinberg
DESCRIPTION:Applied Microeconomics and Trade Seminar\nDate: Wednesday\, December 3\, 2025\nTime: 11:50am – 1:10 p.m.\nLocation: E2-499\n\n \n\nSpeaker: Matt Weinberg \nTitle: Professor of Economics \nAffiliation: Ohio State University\nHost: Jon Robinson\n \nSeminar title: Oligopsony and Collective Bargaining: Evidence from K-12 Teachers \n\nABSTRACT:  Employers facing limited labor market competition may suppress wages below socially optimal levels. Unions can counteract this wage suppression through collective bargaining\, though the may also push wages above the socially optimal level. To assess these forces\, we estimate a structural model of labor supply\, labor demand\, and Nashin-Nash bargaining over wages between teacher unions and school districts in Pennsylvania’s K-12 public school system from 2013 to 2020. Using the estimated parameters\, we compare negotiated equilibrium wages and employment to the pure oligopsony scenario and the social planner scenario. On average\, pure oligopsony reduces wages 16 percent below the social optimum\, while collective bargaining raises wages by 9 percent above the optimum. This average masks substantial district-level heterogeneity driven by variation in bargaining power. Twenty-seven percent of schools have negotiated salaries below the social optimum due to cross-district externalities\, where high salaries at one school lead to hiring reductions\, which increase labor supply in competing districts. 
URL:https://events.ucsc.edu/event/applied-microeconomics-and-trade-seminar-series-presents-matt-weinberg/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Seminars
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DTSTART;TZID=America/Los_Angeles:20251204T114000
DTEND;TZID=America/Los_Angeles:20251204T131500
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SUMMARY:BME 280B Seminar: Gali Bai & David Haussler
DESCRIPTION:Presenter 1: Gali Bai\, BME/PBSE Doctoral Candidate\, Brooks Lab\, UC Santa Cruz \nTitle 1: Dissecting the contribution of chromatin accessibility to RNA transcription and processing with long-read sequencing \nDescription: Although all cells in an organism share the same genomic sequence\, transcriptional programs vary dramatically across cell types. This diversity is governed by epigenetic regulation involving the coordinated activities of chromatin remodelers\, histone modifiers\, and histone chaperones that precisely modulate chromatin accessibility. While previous studies have shown that chromatin accessibility at DNase I–hypersensitive sites such as promoters and enhancers is closely associated with gene expression\, much less is known about how chromatin influences transcription and RNA processing. To study how chromatin regulates RNA processing\, we perturbed yeast chromatin accessibility by deleting two highly conserved chromatin remodelers ISW1 and CHD1. With Oxford Nanopore long-read sequencing\, we profiled nascent RNA\, full-length mRNA\, and chromatin fibers in wild-type and chd1 isw1 double-mutant yeast cells. Loss of ISW1 and CHD1 led to increased chromatin accessibility within intragenic regions\, accompanied by aberrant transcription initiation. Leveraging long-read data\, we associated distinct chromatin states with specific RNA processing events and isoform expression outcomes. Despite a similar level of chromatin perturbations across the genome\, genes with low baseline expression showed extensive transcriptional reprogramming\, whereas highly expressed genes remained largely unaffected. These discrepancies can be partially explained by differences in the enrichment of transcription initiation motifs. In intron-containing genes\, loss of ISW1 and CHD1 reduced splicing efficiency and increased intron retention\, likely due to disrupted RNAPII elongation in the double mutant. Together\, our findings highlight the crucial role of ATP-dependent chromatin remodelers in maintaining nucleosome organization and coordinating co-transcriptional RNA processing. \nPresenter 2: David Haussler\, Distinguished Professor\, UC Santa Cruz \nTitle 2: Brain Organoids \nBio: Haussler received his PhD in computer science from the University of Colorado at Boulder. He is a member of the National Academy of Sciences\, the National Academy of Engineering\, the American Academy of Arts and Sciences and a fellow of AAAS and AAAI. He has won a number of awards\, including the 2015 Dan David Prize\, the 2011 Weldon Memorial Prize from University of Oxford\, the 2009 ASHG Curt Stern Award in Human Genetics\, the 2008 Senior Scientist Accomplishment Award from the International Society for Computational Biology\, the 2005 Dickson Prize for Science from Carnegie Mellon University\, and the 2003 ACM/AAAI Allen Newell Award in Artificial Intelligence. \nHosted by: Professor Josh Stuart\, BME Department
URL:https://events.ucsc.edu/event/bme-280b-seminar-gali-bai-david-haussler/
LOCATION:Physical Sciences Building\, Physical Sciences Building\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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DTSTART;TZID=America/Los_Angeles:20251204T134000
DTEND;TZID=America/Los_Angeles:20251204T150000
DTSTAMP:20260406T011153
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SUMMARY:Behavioral\, Econometrics and Theory Seminar Series Presents: Jacopo Magnani
DESCRIPTION:Economics Behavioral\, Econometrics\, & Theory Seminar\nDate: Thursday\, December 4\, 2025\nTime: 1:40-3:00 p.m.\nLocation: E2-499\n\n \n\nSpeaker: Jacopo Magnani \nTitle:  Associate Professor of Economics \nAffiliation: Norwegian University of Science and Technology\, visiting Caltech\nHost: Kristian Lopez Vargas\n \nSeminar title: Behavioral Limits to Complete Markets\n \nABSTRACT:  Standard economic theory predicts that individuals should prefer complete markets to incomplete markets\, as the former allow state-contingent claims for every possible outcome. Yet real-world markets remain incomplete\, and the demand-side origins of the phenomenon are poorly understood. We develop an experimental framework to examine whether investors may themselves prefer incomplete markets\, and highlight two potential mechanisms: preference instability\, which exposes agents to greater regret or temptation in complete markets\, and complexity costs\, which arise because higher dimensionality increases cognitive effort and errors. In our experiment\, participants consistently reveal a preference for in complete markets\, contradicting the rational benchmark. Comparing homegrown and induced-preference treatments\, we find no evidence that this behavior is driven by preference instability. Instead\, utility losses\, response times\, and subjective ratings indicate that complexity costs drive the preference for incompleteness. Structural estimation confirms that complete markets are several times more complex than incomplete ones\, providing a behavioral foundation for market incompleteness. 
URL:https://events.ucsc.edu/event/behavioral-econometrics-and-theory-seminar-series-presents-jacopo-magnani/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Seminars
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