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X-WR-CALNAME:Workshops @ UCLA
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X-WR-CALDESC:Events for Workshops @ UCLA
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261109T090000
DTEND;TZID=America/Los_Angeles:20261112T120000
DTSTAMP:20261109T140609Z
CREATED:20260918T185132Z
LAST-MODIFIED:20261109T140609Z
UID:10003808-1794214800-1794484800@workshops.ucla.edu
SUMMARY:W19: AI Agents
DESCRIPTION:This 3-day workshop (3 hours per day) introduces participants to the foundations and practical implementation of AI agents using large language models (LLMs) and LangChain. The course covers how LLMs reason\, how retrieval-augmented generation (RAG) works\, and how to extend models with tool use to automate tasks \n 
URL:https://workshops.ucla.edu/workshop/w19-ai-agents/
LOCATION:529 Boyer Hall\, 611 Charles E Young Dr E\,\, Los Angeles\, CA\, 90095\, United States
CATEGORIES:Interactive Workshop,Workshops
ATTACH;FMTTYPE=image/png:https://workshops.ucla.edu/wp-content/uploads/2026/09/1dNLbh0n_400x400-oxpkPa.png
ORGANIZER;CN="QCB Collaboratory":MAILTO:collaboratory@ucla.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261109T130000
DTEND;TZID=America/Los_Angeles:20261109T160000
DTSTAMP:20260921T183027Z
CREATED:20260921T183027Z
LAST-MODIFIED:20260921T183027Z
UID:10003826-1794229200-1794240000@workshops.ucla.edu
SUMMARY:Introduction to directed acyclic graphs (DAGs) for causal inference in R
DESCRIPTION:Directed Acyclic Graphs (DAGs) have emerged as an important tool in causal modeling to understand the relationships among variables. DAGs can inform what variables should be included or excluded in a statistical model intended to minimize bias in the estimation of a causal effect. This workshop discusses the basics of DAGs used for causal inference and outlines simple rules one can follow to know which variables to include in a causal statistical model. The R package daggity will be discussed to visualize DAGs.
URL:https://workshops.ucla.edu/workshop/introduction-to-directed-acyclic-graphs-dags-for-causal-inference-in-r-2/
LOCATION:Zoom
CATEGORIES:Training workshop / Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261110T120000
DTEND;TZID=America/Los_Angeles:20261110T130000
DTSTAMP:20260908T192500Z
CREATED:20260908T192500Z
LAST-MODIFIED:20260908T192500Z
UID:10003795-1794312000-1794315600@workshops.ucla.edu
SUMMARY:Using the National Research Platform (NRP) for AI-enabled Research & Education
DESCRIPTION:Are your computing problems too big for your laptop? Do you want to work on research using computing and data beyond your institution? Come learn about how you can run a list of tasks on the national Open Science Pool and deliver data across communities on the Open Science Data Federation. We will talk about common problems solved by these services\, how to get started on them\, and see some hands-on examples. \nSpeaker: \nDaniel Diaz Ph.D.\nComputational Research Scientist\, National Research Platform
URL:https://workshops.ucla.edu/workshop/using-the-national-research-platform-nrp-for-ai-enabled-research-education/
LOCATION:Zoom
CATEGORIES:Training workshop / Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261112T100000
DTEND;TZID=America/Los_Angeles:20261112T120000
DTSTAMP:20260921T183624Z
CREATED:20260921T183028Z
LAST-MODIFIED:20260921T183624Z
UID:10003828-1794477600-1794484800@workshops.ucla.edu
SUMMARY:Batch Job Submission with Slurm & Optimizing and Managing Your Workflows on the Hoffman2 Cluster
DESCRIPTION:Batch computing is how you turn a single analysis into hundreds or thousands\, scaling your research well beyond what you could run by hand. This workshop covers writing and submitting batch scripts\, requesting the CPU and GPU resources your jobs need\, monitoring job status\, and managing output — the core skillset for running larger or automated workloads on the Hoffman2 Cluster. Because job scripts are one of the areas most affected by the cluster’s move to a new scheduler\, we’ll spend dedicated time on what needs to change to take a script from Grid Engine to Slurm.
URL:https://workshops.ucla.edu/workshop/batch-job-submission-on-the-hoffman2-cluster/
LOCATION:OARC Portal\, Math Sciences 5628\, 5628 Math Science Building\, UCLA
CATEGORIES:Training workshop / Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261112T110000
DTEND;TZID=America/Los_Angeles:20261112T120000
DTSTAMP:20260921T183027Z
CREATED:20260921T183027Z
LAST-MODIFIED:20260921T183027Z
UID:10003827-1794481200-1794484800@workshops.ucla.edu
SUMMARY:Introduction to Video\, Audio\, and Youtube Accessibility
DESCRIPTION:In this session participants will learn about video and audio accessibility best practices. \nBy the end of this training you should be able to:\n-Create an WCAG 2.1 AA caption file\n-Identify closed and open captions\n-Test the player controls of an embedded video\n-Add an audio description to a Youtube video\n-Create an accessible transcript
URL:https://workshops.ucla.edu/workshop/introduction-to-video-audio-and-youtube-accessibility/
LOCATION:Zoom
CATEGORIES:Training workshop / Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261113T110000
DTEND;TZID=America/Los_Angeles:20261113T120000
DTSTAMP:20260921T183028Z
CREATED:20260921T183028Z
LAST-MODIFIED:20260921T183028Z
UID:10003829-1794567600-1794571200@workshops.ucla.edu
SUMMARY:A Satellite Analysis Reveals Why Structures Burn While Neighbors Survive Disaster
DESCRIPTION:In this workshop you will learn how to develop image processing workflows in AWS using generative AI services.
URL:https://workshops.ucla.edu/workshop/a-satellite-analysis-reveals-why-structures-burn-while-neighbors-survive-disaster/
LOCATION:Zoom
CATEGORIES:Training workshop / Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261116T130000
DTEND;TZID=America/Los_Angeles:20261116T160000
DTSTAMP:20260921T183029Z
CREATED:20260921T183029Z
LAST-MODIFIED:20260921T183029Z
UID:10003830-1794834000-1794844800@workshops.ucla.edu
SUMMARY:Generalized Linear Regression Models in R
DESCRIPTION:This workshop introduces the generalized linear regression model\, which extends the linear regression model to accommodate outcomes with different distributions. The workshop briefly reviews linear regression concepts as necessary\, and then discusses logistic regression for binary outcomes and Poisson and negative binomial models for count outcomes. Examples of running each of these models in R are provided. Some exposure to both linear regression and R would be helpful but are not required.
URL:https://workshops.ucla.edu/workshop/generalized-linear-regression-models-in-r-2/
LOCATION:Zoom
CATEGORIES:Training workshop / Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261119T100000
DTEND;TZID=America/Los_Angeles:20261119T120000
DTSTAMP:20260921T183030Z
CREATED:20260921T183030Z
LAST-MODIFIED:20260921T183030Z
UID:10003832-1795082400-1795089600@workshops.ucla.edu
SUMMARY:Computing on the National Research Platform
DESCRIPTION:The National Research Platform (NRP) gives researchers access to a distributed\, Kubernetes-based cyberinfrastructure spanning dozens of institutions\, including a large pool of GPUs and high-throughput storage. For researchers coming from traditional HPC batch schedulers\, the model can be unfamiliar: the unit of work is a containerized workload rather than a script submitted to a queue. \nIn this interactive workshop\, participants will learn how to run tasks on the platform. We start with the conceptual model — namespaces\, Pods\, containers\, and how scheduling differs from a queue — then move directly to practice. Participants will launch an interactive Pod for development\, submit a batch Job\, and request a specific GPU type\, learning how resource requests and limits affect placement. We cover attaching a persistent volume so results survive the Pod\, and close with reading logs\, diagnosing common failure modes\, and norms for sharing a multi-institution resource. \nPrerequisites: participants should arrive with NRP account access and kubectl already installed. Setup instructions will be circulated in advance\, and help will be available before the start. Users unfamiliar with containerization are recommended to attend the “Containerization for Reproducible Scientific Computing” workshop.
URL:https://workshops.ucla.edu/workshop/computing-on-the-national-research-platform/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261119T110000
DTEND;TZID=America/Los_Angeles:20261119T120000
DTSTAMP:20260921T183029Z
CREATED:20260921T183029Z
LAST-MODIFIED:20260921T183029Z
UID:10003831-1795086000-1795089600@workshops.ucla.edu
SUMMARY:Introduction to Digital Accessibility Testing
DESCRIPTION:Audience: UCLA web editors\, content creators\, IT staff\, and program managers Tools Covered: WAVE Chrome plug-in\, Siteimprove Accessibility\, manual keyboard testing \nBy the end of this training\, participants will:\n-Understand the basics of digital accessibility and UCLA’s WCAG 2.1 AA compliance requirements\n-Learn how to use WAVE for page-by-page testing\n-Learn how to use Siteimprove for whole-site accessibility scanning and monitoring\n-Practice manual testing with tab navigation to identify barriers that automated tools miss.\n-Know how to prioritize and remediate common accessibility issues
URL:https://workshops.ucla.edu/workshop/introduction-to-digital-accessibility-testing-9/
LOCATION:Zoom
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261130T120000
DTEND;TZID=America/Los_Angeles:20261130T130000
DTSTAMP:20261109T140610Z
CREATED:20260924T193845Z
LAST-MODIFIED:20261109T140610Z
UID:10003836-1796040000-1796043600@workshops.ucla.edu
SUMMARY:QCBio Distinguished Speaker 2026 (part I): Dr. Qing Nie\, Department of Mathematics\, Department of Systems Biology\, University of California\, Irvine
DESCRIPTION:From Models to AI: Learning the Spatiotemporal Organization of Cells (Parts I) \nModern biology faces a fundamental observability barrier: we can measure a biological tissue deeply or watch it evolve\, but we cannot do both simultaneously. The complete spatiotemporal trajectory of a biological tissue—from cell states and cell–cell interactions to spatial reorganization and future function—is therefore intrinsically unobservable. Generative modeling and virtual analysis offer new opportunities to elucidate the spatiotemporal organization of cells. In this two-part talk\, I will first present modeling approaches from a top-down perspective\, using known information about cell–cell communication molecules\, cell-fate genes\, and their regulators to uncover principles and critical features of multicellular organization. To address the limitations of such models\, which depend strongly on prior knowledge of predetermined regulators\, I will then focus on a bottom-up perspective that learns the spatiotemporal organization of cells from the rich information contained in single-cell sequencing\, spatial transcriptomics\, and multi-omics data. These emerging data enable the screening and discovery of unprecedented molecular details underlying multicellular organization. By integrating mathematical models with computational inference\, we can uncover spatiotemporal properties of cells and their interactions that are otherwise difficult to observe. Finally\, I will present our initial efforts to combine AI with the computational tools and mathematical models we have developed toward learning and predicting the spatiotemporal organization of single cells.
URL:https://workshops.ucla.edu/workshop/qcbio-distinguished-speaker-2026-part-i-dr-qing-nie-department-of-mathematics-department-of-systems-biology-university-of-california-irvine/
LOCATION:Boyer Hall 159
CATEGORIES:QCBio Seminar Series,Research Seminars,Special Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261201T130000
DTEND;TZID=America/Los_Angeles:20261201T140000
DTSTAMP:20261109T140610Z
CREATED:20260924T193845Z
LAST-MODIFIED:20261109T140610Z
UID:10003837-1796130000-1796133600@workshops.ucla.edu
SUMMARY:QCBio Distinguished Speaker 2026 (part II): Dr. Qing Nie\, Department of Mathematics\, Department of Systems Biology\, University of California\, Irvine
DESCRIPTION:From Models to AI: Learning the Spatiotemporal Organization of Cells (Part II) \nModern biology faces a fundamental observability barrier: we can measure a biological tissue deeply or watch it evolve\, but we cannot do both simultaneously. The complete spatiotemporal trajectory of a biological tissue—from cell states and cell–cell interactions to spatial reorganization and future function—is therefore intrinsically unobservable. Generative modeling and virtual analysis offer new opportunities to elucidate the spatiotemporal organization of cells. In this two-part talk\, I will first present modeling approaches from a top-down perspective\, using known information about cell–cell communication molecules\, cell-fate genes\, and their regulators to uncover principles and critical features of multicellular organization. To address the limitations of such models\, which depend strongly on prior knowledge of predetermined regulators\, I will then focus on a bottom-up perspective that learns the spatiotemporal organization of cells from the rich information contained in single-cell sequencing\, spatial transcriptomics\, and multi-omics data. These emerging data enable the screening and discovery of unprecedented molecular details underlying multicellular organization. By integrating mathematical models with computational inference\, we can uncover spatiotemporal properties of cells and their interactions that are otherwise difficult to observe. Finally\, I will present our initial efforts to combine AI with the computational tools and mathematical models we have developed toward learning and predicting the spatiotemporal organization of single cells.
URL:https://workshops.ucla.edu/workshop/qcbio-distinguished-speaker-2026-part-ii-dr-qing-nie-department-of-mathematics-department-of-systems-biology-university-of-california-irvine/
LOCATION:Boyer Hall 159
CATEGORIES:QCBio Seminar Series,Research Seminars,Special Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261203T100000
DTEND;TZID=America/Los_Angeles:20261203T110000
DTSTAMP:20261102T234402Z
CREATED:20261102T234302Z
LAST-MODIFIED:20261102T234402Z
UID:10003838-1796292000-1796295600@workshops.ucla.edu
SUMMARY:UC OSPO All-Campus Virtual Meetup: Ten years of browser nano extensions + Show and Tell
DESCRIPTION:Join the UC OSPO Network for an all-campus virtual meetup\, open to the UC community. Neal Fultz\, statistical consultant for UCLA Social Sciences\, looks back on ten years of writing browser extensions. The extensions are nano: each is under 100 lines of code\, and the talk shows an entire program. They work in Firefox and Chrome-based browsers. A Show and Tell follows. \nRegistration is required. \nHosted by Tim Dennis and Leigh Phan of the UCLA Library Data Science Center.
URL:https://workshops.ucla.edu/workshop/uc-ospo-all-campus-virtual-meetup-ten-years-of-browser-nano-extensions-show-and-tell/
LOCATION:Zoom
CATEGORIES:Live,Research talk
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261208T120000
DTEND;TZID=America/Los_Angeles:20261208T130000
DTSTAMP:20260908T192711Z
CREATED:20260908T192711Z
LAST-MODIFIED:20260908T192711Z
UID:10003796-1796731200-1796734800@workshops.ucla.edu
SUMMARY:From One to Many: compute and data beyond your local context
DESCRIPTION:Are your computing problems too big for your laptop? Do you want to work on research using computing and data beyond your institution? Come learn about how you can run a list of tasks on the national Open Science Pool and deliver data across communities on the Open Science Data Federation. We will talk about common problems solved by these services\, how to get started on them\, and see some hands-on examples. \nSpeaker: \nChristina Koch\nLead Research Computing Facilitator\, Center for High Throughput Computing
URL:https://workshops.ucla.edu/workshop/from-one-to-many-compute-and-data-beyond-your-local-context/
LOCATION:Zoom
CATEGORIES:Training workshop / Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261211T110000
DTEND;TZID=America/Los_Angeles:20261211T123000
DTSTAMP:20260921T183030Z
CREATED:20260921T183030Z
LAST-MODIFIED:20260921T183030Z
UID:10003833-1796986800-1796992200@workshops.ucla.edu
SUMMARY:Learn prompt engineering and Retrieval Augmented Generation using LLMs
DESCRIPTION:In this workshop you will how to use LLMs and RAG in concert with prompt engineering to build purpose-driven AI productivity tools
URL:https://workshops.ucla.edu/workshop/learn-prompt-engineering-and-retrieval-augmented-generation-using-llms/
LOCATION:Zoom
END:VEVENT
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