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DTSTART;TZID=America/Los_Angeles:20260518T100000
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SUMMARY:ECE Seminar: From Plumes to Produce: Leveraging Atmospheric Modeling and Smart Sensing for Food Safety
DESCRIPTION:Presenter: Derek Hollenbeck\, postdoctoral research scholar\, University of California\, Merced  \nDescription: Advances in drone-based environmental sensing\, atmospheric modeling\, and intelligent monitoring systems are creating new opportunities for addressing emerging challenges in food safety and agricultural resilience. This talk explores how methodologies originally developed for methane emission detection and quantification could be translated toward agricultural and food safety applications. The presentation begins with an overview of research experiences in autonomous sensing and environmental monitoring\, including work associated with the inaugural CITRIS Aviation Prize before outlining some key potential areas for food safety with drones. Then\, the talk overviews previous research on the topics related to drone-based environmental monitoring\, Digital Twins\, and Smart Sensing – with a focus on methane emission source quantification\, atmospheric transport modeling of a point source\, and inverse problem methodologies for real-time parameter estimation. Finally\, the talk examines how these concepts may be adapted to food safety research questions\, as well as highlight opportunities for interdisciplinary collaboration alongside emerging priorities from organizations and certification frameworks. \nBio: Derek Hollenbeck is a postdoctoral research scholar at the University of California\, Merced (UCM)\, where he serves as the manager of the Center for Methane Emissions Research and Innovation (CMERI) under the supervision of Dr. YangQuan Chen. He earned his B.Sc. (2016) and Ph.D. (2023) in Mechanical Engineering from UCM\, where he conducted research in the Mechatronics Embedded Systems and Automation (MESA) Lab.\n \nHis work sits at the intersection of fluid mechanics\, controls\, dynamics\, and inverse problems\, with a focus on developing intelligent environmental monitoring systems using small unmanned aerial systems (sUAS). His research integrates machine learning and physics-based modeling to detect\, localize\, and quantify methane emissions in complex environments.\n \nDr. Hollenbeck is the author of Smart Sensing with Digital Twins: Methane Emission Source Determination with sUAS\, which presents a framework for combining digital twins\, inverse modeling\, and autonomous sensing to improve environmental observability. His work emphasizes how data-driven and physics-informed approaches can be fused to optimize sensor placement\, enhance estimation accuracy\, and enable real-time decision-making in single/distributed mobile sensing systems. \nHosted by: Professor Marco Rolandi\, ECE Department \nZoom Link: https://ucsc.zoom.us/j/96727838511?pwd=1Qzl9HTV3G2BxaSEG8GeKOPZVu2NWj.1
URL:https://live-events-ucsc.pantheonsite.io/event/ece-seminar-from-plumes-to-produce-leveraging-atmospheric-modeling-and-smart-sensing-for-food-safety/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Seminars
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DTSTART;TZID=America/Los_Angeles:20260518T104000
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SUMMARY:ECE 290 Seminar: AI for Enhancing Power Grid Resilience Against Extreme Weather Events
DESCRIPTION:Presenter: Masood Parvania\, Roger P. Webb Endowed Professor\, University of Utah \n  \nDescription: Many communities across the world are experiencing more frequent and severe extreme weather disturbances such as wildfires\, heatwaves\, drought\, storms\, rising sea levels\, and flooding\, which not only pose threats to human health\, and the environment but also affect the ability of the power grid to continue powering the communities. This requires upgrading the operation of power grid from passive and manual applications to making complex decisions in real-time to facilitate the automated recovery of the system after major disturbances. This talk will review the application of various AI and ML techniques for detection\, response and mitigation of cyber anomalies and extreme weather events in power distribution systems.\n \n  \nBio: Masood Parvania is the Roger P. Webb Endowed Professor of Electrical and Computer Engineering and the Director of Utah Smart Energy Laboratory (U-Smart) at the University of Utah. Dr. Parvania is the Principal Investigator and Director of the U.S.-Canada Center on Climate-Resilient Western Interconnected Grid (NSF WIRED Global Center)\, co-funded by U.S. National Science Foundation (NSF) and Natural Sciences and Engineering Research Council of Canada (NSERC). He is also the Founder and President of the Energy-AI company\, Grid Elevated\, which specializes on developing and commercializing AI technology for resilient and efficient power grid operation. \n  \nHosted by: Professor Soumya Bose\, ECE Department \nZoom Link: https://ucsc.zoom.us/j/97975378707?pwd=ljcgaCfhMmhZ88Vt5dqQUBVQRjehOx.1
URL:https://live-events-ucsc.pantheonsite.io/event/ece-290-seminar-ai-for-enhancing-power-grid-resilience-against-extreme-weather-events/
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:20260518T132500
DTEND;TZID=America/Los_Angeles:20260518T143000
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SUMMARY:Seminar Series | Is the Farm a Digital Factory?: Labor\, Leafy Greens\, and the Limits of Automation with Summer Sullivan
DESCRIPTION:Host:Madeleine Fairbairn \nSilicon Valley investors\, entrepreneurs\, and engineers are increasingly interested in agriculture as a site to disrupt and improve upon with their technologies. The nearby Salinas Valley – known as the Salad Bowl of the World – might be considered a “ground zero” for these operations of technological introduction\, with some calling it the Silicon Valley of Agriculture. This exit talk showcases my research on the evolving context in which new technologies are transforming social and environmental relations\, especially for already exploited\, racialized workers in the Salinas Valley. I trace the uneven ways in which agricultural automation is unfolding\, but also its profound limits within the region’s delicate\, leafy farming systems. Through interviews\, focus groups\, participant observation\, and historical analysis\, I will show how the materiality of crops such as lettuce continues to organize labor and limit full automation. Contributing to critical analysis of the uneven racial\, class\, and gender dynamics of the “future of work\,” this project centers emergent\, uncertain relationships among farmworkers\, the plants they care for\, and the fragile futures of capitalism. \nIn person and on Zoom \nMeeting ID:  949 5253 7079 \nPasscode: 552886
URL:https://live-events-ucsc.pantheonsite.io/event/seminar-series-is-the-farm-a-digital-factory-labor-leafy-greens-and-the-limits-of-automation-with-summer-sullivan/
LOCATION:Interdisciplinary Sciences Building\, 7487 Red Hill Road\, Santa Cruz\, CA\, 95064
CATEGORIES:Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260518T160000
DTEND;TZID=America/Los_Angeles:20260518T170000
DTSTAMP:20260408T220408Z
CREATED:20260408T220408Z
LAST-MODIFIED:20260408T220408Z
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SUMMARY:Statistics Seminar: Unifying Regression-Based and Design-Based Causal Inference in Time-Series Experiments and Crossover Experiments
DESCRIPTION:Presenter: Peng Ding\, Associate Professor\, UC Berkeley \nDescription: I will present some recent results on unifying regression-based and design-based causal inference in time-series experiments and crossover experiments. Part I: Time-series experiments\, also called switchback experiments or N-of-1 trials\, play increasingly important roles in modern applications in medical and industrial areas. Under the potential outcomes framework\, recent research has studied time-series experiments from the design-based perspective\, relying solely on the randomness in the design to drive the statistical inference. Focusing on simpler statistical methods\, we examine the design-based properties of regression- based methods for estimating treatment effects in time-series experiments. We demonstrate that the treatment effects of interest can be consistently estimated using ordinary least squares with an appropriately specified working model and transformed regressors. Additionally\, we show that asymptotically\, the heteroskedasticity and autocorrelation consistent variance estimators provide conservative estimates of the true\, design-based variances. This part is based on https://arxiv.org/pdf/2510.22864  \nPart II: Crossover designs randomly assign each unit to receive a sequence of treatments. By comparing outcomes within the same unit\, these designs can effectively eliminate between-unit variation and facilitate the identification of both instantaneous effects of current treatments and carryover effects from past treatments. They are widely used in traditional biomedical studies and are increasingly adopted in modern digital platforms. However\, standard analyses of crossover designs often rely on strong parametric models\, making inference vulnerable to model misspecification. We unify the analysis of crossover designs using least squares\, with restrictions on the coefficients and weights on the units. Based on the theory\, we recommend specifying the regression function\, weighting scheme\, and coefficient restrictions to assess identifiability\, construct efficient estimators\, and estimate variances in a unified manner. This part is based on https://arxiv.org/pdf/2511.09215 \nAbout the speaker: Peng Ding is an Associate Professor in the Department of Statistics at UC Berkeley. He obtained his Ph.D. from the Department of Statistics\, Harvard University in May 2015 and worked as a postdoctoral researcher in the Department of Epidemiology\, Harvard T. H. Chan School of Public Health until December 2015. Previously\, he received his B.S. in Mathematics\, B.A. in Economics\, and M.S. in Statistics from Peking University. \nThis seminar is hosted by Professor Allen Kei.
URL:https://live-events-ucsc.pantheonsite.io/event/statistics-seminar-unifying-regression-based-and-design-based-causal-inference/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260518T160000
DTEND;TZID=America/Los_Angeles:20260518T170000
DTSTAMP:20260429T152454Z
CREATED:20260429T152454Z
LAST-MODIFIED:20260429T152454Z
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SUMMARY:AM Seminar: Dissecting Complex Disease Mechanisms with Causal Inference and Deep Learning
DESCRIPTION:Presenter: Dr. David A. Knowles\, New York Genome Center & Columbia University \nDescription: Many human diseases have a substantial genetic component\, which association studies are increasingly capable of characterizing\, empowered by ever-growing sample sizes. These associations have the potential to elucidate complex disease biology and prioritize therapeutic interventions. However\, it is challenging to determine the impacted genes\, pathways and cellular states since most risk variants are noncoding. I will describe strategies we have explored to address this challenge\, particularly in the context of Alzheimer’s disease. We have mapped genetic effects on expression\, splicing and RNA editing in over 10k postmortem brain samples\, enabling interpretation of common variant associations. We developed a Mendelian randomization-based causal network inference method to estimate how genetic effects propagate through the gene network to converge on disease risk. We show that deep learning models of pre- and post- transcriptional regulation can refine functional fine-mapping\, improve the portability of polygenic risk scores across ancestries\, and increase power in novel annotation-aware noncoding rare variant association studies. Finally\, we designed a CRISPR/Cas13-based strategy to perform isoform-specific knockdown\, opening the door for isoform-resolved functional characterization of putative disease-causal transcriptomic changes. \nAbout the speaker: Dr. Knowles studied Natural Sciences and Information Engineering at Cambridge before obtaining an MSc in Bioinformatics and Systems Biology at Imperial College London. During his PhD in the Cambridge University Machine Learning Group under Zoubin Ghahramani he worked on variational inference and Bayesian nonparametric models. He was a postdoc at Stanford developing methods for functional genomics with Daphne Koller (CS)\, Sylvia Plevritis (Computational Systems Biology/Radiology) and Jonathan Pritchard (Genetics/Biology). At Columbia\, he is an Associate Professor of Computer Science\, an Interdisciplinary Appointee in Systems Biology and an Affiliate Member of the Data Science Institute. He is also a Core Faculty Member at the New York Genome Center. His group develops methods to better understand the genetic basis of human disease. \n\n\n\nThis seminar is hosted by Professor Nilah Ioannidis.
URL:https://live-events-ucsc.pantheonsite.io/event/am-seminar-dissecting-complex-disease-mechanisms-with-causal-inference-and-deep-learning/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260519T100000
DTEND;TZID=America/Los_Angeles:20260519T110000
DTSTAMP:20260514T225808Z
CREATED:20260514T195842Z
LAST-MODIFIED:20260514T225808Z
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SUMMARY:ECE Seminar: Multiscale Sensing for Specialty Crop Systems: From Field Monitoring to Food Safety Application
DESCRIPTION:Presenter: Eve Laroche-Pinel\, Postdoctoral Researcher\, California State University\, Fresno \nDescription: Advances in remote sensing\, drone platforms\, and data analytics are enhancing the ability to monitor agricultural systems at fine spatial and temporal scales. This presentation will highlight applied research using multispectral and hyperspectral data from satellites\, drones\, aircraft\, and ground platforms to assess crop water status\, detect disease\, and estimate fruit composition. These efforts are developed in collaboration with growers and industry partners\, with an emphasis on methods that are robust under field conditions and scalable across production systems. Building on this foundation\, the talk will examine how similar sensing approaches could be extended to address food safety challenges in California agriculture\, particularly in systems transitioning toward organic and regenerative practices . By linking environmental variability\, water dynamics\, and landscape features with potential contamination pathways\, sensing technologies may support improved risk assessment and monitoring. \nBio: Eve Laroche-Pinel is a researcher specializing in the application of sensing technologies to agricultural systems\, with a focus on translating data-driven methods into tools that support decision-making in real production environments. Her work sits at the intersection of agricultural engineering\, remote sensing\, and applied machine learning.  \nShe holds a PhD from the National Polytechnic Institute of Toulouse (France)\, completed in partnership with industry\, where she developed an operational service to monitor vineyard water status using satellite imagery. This work fostered a strong emphasis on applied research\, system integration\, and technology transfer to end users.  \nShe is currently a postdoctoral researcher at California State University\, Fresno\, contributing to a research program that uses multispectral and hyperspectral data collected from satellites\, drones\, aircraft\, and ground-based platforms. Her work addresses plant water status\, disease detection\, and crop composition\, combining field measurements\, laboratory analyses\, and predictive modeling. These projects are conducted in collaboration with growers\, industry partners\, and multidisciplinary academic teams\, with the objective of producing methods that are robust under field conditions and scalable across production systems.  \nShe plans to increasingly focus on how sensing technologies could contribute to food safety challenges in specialty crops. By linking environmental variability\, crop condition\, and landscape features with potential contamination pathways\, her future work would aim to support improved risk assessment and monitoring strategies\, particularly in systems transitioning toward organic and regenerative practices.  \nExtension and stakeholder engagement are central to her approach. She works closely with growers and partners to co-develop field trials\, adapt methodologies to operational constraints\, and translate technical outputs into actionable guidance. Her work includes participation in workshops\, training activities\, and collaborative projects that connect research with practice.  \nHer long-term goal is to build integrated research and extension programs that combine drones\, spectral sensing\, and environmental monitoring to support safe\, resilient\, and technology-enabled agriculture. \nHosted by: Professor Marco Rolandi\, ECE Department \nZoom Link: https://ucsc.zoom.us/j/96727838511?pwd=1Qzl9HTV3G2BxaSEG8GeKOPZVu2NWj.1
URL:https://live-events-ucsc.pantheonsite.io/event/ece-seminar-researcher-in-agricultural-sensing-remote-sensing-and-applied-ai/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260520T110000
DTEND;TZID=America/Los_Angeles:20260520T121500
DTSTAMP:20260518T155149Z
CREATED:20260518T155149Z
LAST-MODIFIED:20260518T155149Z
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SUMMARY:CSE Colloquium - Safety Alignment of LMs via Non-cooperative Games
DESCRIPTION:Presenter: Arman Zharmagambetov\, Meta \nAbstract:\nEnsuring the safety of language models (LMs) while maintaining their usefulness remains a critical challenge in AI alignment. Current approaches rely on sequential adversarial training: generating adversarial (harmful) prompts and fine-tuning LMs to defend against them. We introduce a different paradigm: framing safety alignment as a non-zero-sum game between an Attacker LM and a Defender LM trained jointly via online reinforcement learning. Each LM continuously adapts to the other’s evolving strategies\, driving iterative improvement. Our method uses a preference-based reward signal derived from pairwise comparisons instead of point-wise scores\, providing more robust supervision and potentially reducing reward hacking. Our RL recipe\, AdvGame\, shifts the Pareto frontier of safety and utility\, yielding a Defender LM that is simultaneously more helpful and more resilient to adversarial attacks. In addition\, the resulting Attacker LM converges into a strong\, general-purpose red-teaming agent that can be directly deployed to probe arbitrary target models. \nBio:\nArman Zharmagambetov is a research scientist in the Fundamental AI Research (FAIR) team at Meta. His research primarily focuses on machine learning and optimization\, recently exploring their application in enhancing the security and robustness of AI systems. He received his PhD from the University of California – Merced. Afterward\, he completed his postdoctoral research at FAIR\, focusing on Reinforcement Learning\, AI-guided design and Optimization. \nHosted by: Professor Alvaro Cardenas and Professor Sungjin Im \nDate and Time: Wednesday\, May 20\, 2026 from 11:00 am – 12:15 pm \nLocation: Engineering 2\, Room E2-180 (Refreshments such as fruit\, pastries\, coffee\, and tea will be provided.) \nZoom Option: https://ucsc.zoom.us/j/93445911992?pwd=YkJ2TQtF79h0PcNXbEcpZLbpK0coiY.1&jst=3
URL:https://live-events-ucsc.pantheonsite.io/event/cse-colloquium-safety-alignment-of-lms-via-non-cooperative-games/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260520T132000
DTEND;TZID=America/Los_Angeles:20260520T142500
DTSTAMP:20260513T212109Z
CREATED:20260513T211954Z
LAST-MODIFIED:20260513T212109Z
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SUMMARY:BME80G Seminar – Ann Mc Cartney\, "The Why\, What and How of Indigenous Data Sovereignty"
DESCRIPTION:Presenter: Dr. Ann Mc Cartney\n\n\nLocation: Virtual. Please register here: https://ucsc.zoom.us/meeting/register/ciShTZsyRViYxMDjCc_cAQ#/registration \nAbstract: In 2007 the General Assembly of the United Nations adopted the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP) that supports Indigenous Peoples’ inherent rights to self-determination and governance over Indigenous Peoples\, territories and resources. This codification in an international treaty led to the conceptualization of Indigenous Data Sovereignty in 2016. Indigenous Data Sovereignty is defined as the right of Indigenous Peoples to own\, control\, access and possess data that derive from them\, and which pertain to Nation membership\, knowledge systems\, customs or territories and is not an internationally recognized concept. Practically\, Indigenous Data Sovereignty gives decision-making authority to Indigenous Peoples and allows them to decide how best data should be collected\, accessed\, and used for nation-building. For this reason\, Indigenous Data Sovereignty is inextricably linked to Indigenous Data Governance. \nThis lecture will dive into the why\, what\, and how of Indigenous Data Sovereignty. Beginning with dive into the history of genomics research and Indigenous Peoples. Then moving into a more in-depth description of both Indigenous Data Sovereignty and Indigenous Data Governance. The lecture will close with highlighting three real world case-studies of genomics projects operationalising Indigenous Data Sovereignty. \nAbout the speaker: Dr. Mc Cartney is a Full Researcher at the University of California\, Irvine and a Consultant for the Secretariat of the Convention on Biological Diversity\, where she works at the intersection of bioinformatics\, bioethics and policy across human and non-human species. Dr. Mc Cartney completed her PhD in Bioinformatics and Molecular Evolution from Dublin City University. After this she carried out a Genomics Aotearoa Postdoctoral Research Fellowship where she created culturally respectful genomic informatics pipelines for the project that were responsive to the needs and rights of Māori. She then moved Stateside and carried out a second Visiting Postdoctoral Fellowship in the Genome Informatics Section at the NHGRI. During this time\, she also conducted a detail in the NIH Office of Science Policy. Dr. Mc Cartney then transitioned to the University of California\, Santa Cruz’s Genomics Institute as an Assistant Researcher where she worked at the forefront of genomic sequencing technologies to develop more just genomic data infrastructures\, policies and frameworks for engagement. She became an elected member of the Executive Council of the Earth BioGenome Project\, the Vice-chair of the European Reference Genome Atlas\, and the Director of International Partnerships for the Human Pangenome Reference Consortium. She also acted as a “technical expert” for many international science policy initiatives including the DSI Scientific Network\, Native Biodata Consortium and the Informal Advisory Group on DSI for the Convention on Biological Diversity. Additionally\, Dr. Mc Cartney was part of the team to build the first NIH-funded Tribal Data Repository for American Indian and Alaska Natives.
URL:https://live-events-ucsc.pantheonsite.io/event/bme80g-seminar-ann-mc-cartney-the-why-what-and-how-of-indigenous-data-sovereignty/
LOCATION:https://live-events-ucsc.pantheonsite.io/event/bme80g-seminar-ann-mc-cartney-the-why-what-and-how-of-indigenous-data-sovereignty/
CATEGORIES:Lectures & Presentations,Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260521T114000
DTEND;TZID=America/Los_Angeles:20260521T131500
DTSTAMP:20260507T163056Z
CREATED:20260507T163056Z
LAST-MODIFIED:20260507T163056Z
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SUMMARY:BME 280B Seminar: Speaker Dylan Shropshire - "How did Wolbachia become Earth's most pervasive animal symbiont?"
DESCRIPTION:Presenter: Dylan Shropshire\, Assistant Professor in the Department of Biological Sciences\, Lehigh University \nDescription: Maternally transmitted Wolbachia bacteria inhabit roughly half of all arthropod species\, making them likely the most common animal-associated microbe on Earth. Wolbachia alter host reproduction\, persist across deep evolutionary timescales\, and move into new host species in ways that we are only beginning to resolve. Wolbachia‘s biological success now also underpins global biocontrol programs aimed at suppressing arboviral disease\, lending applied urgency to a foundational question: how did a single bacterial lineage come to dominate the animal world? In this seminar\, I will draw on my recent and ongoing work to explore facets of this question\, leveraging Wolbachia‘s evolutionary diversity and wet-lab tools to define the mechanisms driving this microbe’s success across the animal world. Collectively\, this work aims to clarify the determinants of Wolbachia‘s natural prevalence and to sharpen the predictive frameworks underpinning Wolbachia-based biocontrol of vector-borne disease. \nBio: Dylan Shropshire is an Assistant Professor in the Department of Biological Sciences at Lehigh University in Pennsylvania\, where he leads a research group studying mechanisms of Wolbachia-host interactions. He earned his PhD at Vanderbilt University as an NSF Graduate Research Fellow and completed an NSF Postdoctoral Research Fellowship at the University of Montana. He is also a first-generation high school graduate and former Pell Grant recipient\, experiences that motivate his commitment to high-quality mentorship and evidence-based pedagogical practices. His work has been recognized by the Charles E. Kaufman New Investigator Award\, Lehigh’s Pre-Tenure Faculty Award\, and the College of Arts and Sciences Dean’s Award for Teaching Excellence. \nHosted by: Professor Shelbi Russell\, BME Department
URL:https://live-events-ucsc.pantheonsite.io/event/bme-280b-seminar-speaker-dylan-shropshire-how-did-wolbachia-become-earths-most-pervasive-animal-symbiont/
LOCATION:Biomedical Sciences Building\, 575 McLaughlin Drive
CATEGORIES:Lectures & Presentations,Seminars
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GEO:46.1226939;-64.7891251
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END:VEVENT
END:VCALENDAR