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DTSTART;TZID=America/Los_Angeles:20261022T110000
DTEND;TZID=America/Los_Angeles:20261022T120000
DTSTAMP:20260921T183011Z
CREATED:20260921T183011Z
LAST-MODIFIED:20260921T183011Z
UID:10003817-1792666800-1792670400@workshops.ucla.edu
SUMMARY:Introduction to Digital Accessibility Testing
DESCRIPTION:This session introduces the fundamentals of digital accessibility and why it matters at UCLA. Participants will learn what accessibility means in a digital context\, gain insight into disability culture\, and see a live screen reader demonstration. The training will also cover practical tips for creating accessible documents\, websites\, and media\, including proper use of heading structure\, writing effective alt-text\, and creating descriptive hyperlinks.
URL:https://workshops.ucla.edu/workshop/introduction-to-digital-accessibility-testing-8/
LOCATION:Zoom
CATEGORIES:Training workshop / Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261022T150000
DTEND;TZID=America/Los_Angeles:20261022T160000
DTSTAMP:20260919T001427Z
CREATED:20260919T001427Z
LAST-MODIFIED:20260919T001427Z
UID:10003809-1792681200-1792684800@workshops.ucla.edu
SUMMARY:Research Your Ballot
DESCRIPTION:BYOB—bring your own ballot!—and learn how to research the issues at stake in this November’s election. We’ll discuss how to avoid misinformation and practice strategies for finding the information you need to make an informed voting decision.
URL:https://workshops.ucla.edu/workshop/research-your-ballot/
LOCATION:Charles E. Young Research Library\, Presentation Room 11348
CATEGORIES:Live,Training workshop / Tutorial
ORGANIZER;CN="UCLA Library":MAILTO:yrl-circ@library.ucla.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261027T083000
DTEND;TZID=America/Los_Angeles:20261027T153000
DTSTAMP:20260919T001704Z
CREATED:20260919T001704Z
LAST-MODIFIED:20260919T001704Z
UID:10003810-1793089800-1793115000@workshops.ucla.edu
SUMMARY:AWS Research Day at UCLA
DESCRIPTION:The Office of Advanced Research Computing is pleased to share this upcoming opportunity with UCLA researchers. You are invited to the AWS Research Day for UCLA — a one-day\, in-person event designed to help UCLA researchers discover how cloud-powered AI and data platforms can accelerate your work. \nWhat to Expect\nLearn how Amazon Web Services (AWS) can transform the way you conduct research — from analyzing data through natural language queries to automating repetitive workflows and conducting comprehensive research analysis\, all within secure\, shared workspaces built for collaboration. \nThe day will feature real-world use cases\, live demos\, and hands-on workshops led by cloud experts and experienced researchers. Through interactive sessions\, you’ll be introduced to essential AWS services and AI-powered research tools you can start using right away. \nWhether you’re new to the cloud or looking to optimize your existing cloud-based work\, you’ll walk away with practical knowledge and skills to take full advantage of cloud computing for your research. \nMeet the Speakers\nYou’ll hear from leaders and researchers from UCLA and Amazon Web Services:\n•    Davida Johnson — Executive Director\, Office of Advanced Research Computing\, UCLA\n•    Paul Tung — Manager\, High Performance Computing Platform\, UCLA Health\n•    Rami Abdallah — Manager\, Bruin Cloud & DevOps Strategy\, UCLA\n•    Jiaqi Ma — Professor\, Civil & Environmental Engineering Department\, UCLA\n•    Scott Friedman\, Ph.D. — Leader for Research Computing Solutions\, Amazon Web Services\n•    Claudiu Farcas\, Ph.D. — Principal Solutions Architect\, Amazon Web Services \nWho Should Attend\nThis event is designed for faculty\, scientists\, IT professionals\, researchers and support staff including graduate students at UCLA. No prior experience with AWS is required.
URL:https://workshops.ucla.edu/workshop/aws-research-day-at-ucla/
LOCATION:UCLA University Club | 480 Charles E Young Drive East\, Los Angeles
CATEGORIES:Training workshop / Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261028T103000
DTEND;TZID=America/Los_Angeles:20261028T113000
DTSTAMP:20260921T183012Z
CREATED:20260921T183012Z
LAST-MODIFIED:20260921T183012Z
UID:10003818-1793183400-1793187000@workshops.ucla.edu
SUMMARY:Siteimprove Accessibility Software Part 2
DESCRIPTION:In this more advanced session participants will learn about the issues dashboard and how to both interpret results and prioritize issues. This session will also cover how to best use the Siteimprove backend features to improve the accessibility of your website.
URL:https://workshops.ucla.edu/workshop/siteimprove-accessibility-software-part-2/
LOCATION:Zoom
CATEGORIES:Training workshop / Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261029T100000
DTEND;TZID=America/Los_Angeles:20261029T120000
DTSTAMP:20260921T183012Z
CREATED:20260921T183012Z
LAST-MODIFIED:20260921T183012Z
UID:10003819-1793268000-1793275200@workshops.ucla.edu
SUMMARY:Getting Started with the Hoffman2 Cluster
DESCRIPTION:New to the Hoffman2 Cluster? This session gets you from zero to logged-in. Learn how to request an account\, connect via SSH or remote desktop\, find your way around\, and move files to and from the cluster. No HPC experience required — just the foundational skills to start computing on the cluster with confidence.
URL:https://workshops.ucla.edu/workshop/getting-started-with-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:20261029T130000
DTEND;TZID=America/Los_Angeles:20261029T150000
DTSTAMP:20260921T183012Z
CREATED:20260921T183012Z
LAST-MODIFIED:20260921T183012Z
UID:10003820-1793278800-1793286000@workshops.ucla.edu
SUMMARY:Data Visualization with Python I: Plotting Fundamentals
DESCRIPTION:Python is a very popular language for computational and data science\, and it has many powerful capabilities for visualizing data in the pursuit of understanding and conveying underlying patterns. The first part of this series will showcase various ways that Python can be used for creating graphics\, following which we’ll dive into some common Python libraries for data viz: Matplotlib\, Pandas\, and Seaborn. Along the way we’ll cover how these libraries fit together — Matplotlib’s underlying figure-and-axes model\, Pandas’ convenient one-line plotting for quick exploration\, and Seaborn’s higher-level interface for statistical graphics — as well as the practical details that make a figure publication-ready. We will go through several interactive exercises so that attendees can gain direct experience in using these libraries and will be prepared to learn more on their own after the workshop. Basic familiarity with Python will be useful.
URL:https://workshops.ucla.edu/workshop/data-visualization-with-python-i-plotting-fundamentals-6/
LOCATION:Zoom
CATEGORIES:Training workshop / Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261102T120000
DTEND;TZID=America/Los_Angeles:20261102T130000
DTSTAMP:20260921T183013Z
CREATED:20260921T183013Z
LAST-MODIFIED:20260921T183013Z
UID:10003821-1793620800-1793624400@workshops.ucla.edu
SUMMARY:Getting Started with ArcGIS Online at UCLA: Creating\, Editing\, and Sharing Spatial Data and Stories
DESCRIPTION:This recorded workshop series introduces learners to the fundamentals of ArcGIS Online as a browser-based GIS platform for creating\, editing\, and sharing spatial data. Designed for beginners or those transitioning from desktop GIS systems\, this series focuses on essential skills and workflows for building maps\, managing GIS data\, and publishing interactive projects. \nNew videos in the series will cover:\n– Joining tables to spatial features using shared attributes\n– Performing spatial joins based on location and spatial relationships\n– Aggregating point data into neighborhoods\, census areas\, or other polygons\n– Finding nearby features and analyzing proximity\n– Creating buffers and other derived spatial features\n– Representing origins\, destinations\, and connections as nodes and edges\n– Creating flow and movement maps from relational data
URL:https://workshops.ucla.edu/workshop/getting-started-with-arcgis-online-at-ucla-creating-editing-and-sharing-spatial-data-and-stories/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261102T130000
DTEND;TZID=America/Los_Angeles:20261102T160000
DTSTAMP:20260921T183014Z
CREATED:20260921T183014Z
LAST-MODIFIED:20260921T183014Z
UID:10003822-1793624400-1793635200@workshops.ucla.edu
SUMMARY:Introduction to Survival Analysis in R
DESCRIPTION:Survival analysis models time-to-event outcomes.  This workshop introduces usage of the survival package in R for some of the most commonly used survival methods.  Topics include data setup\, Kaplan-Meier estimates and curves\, log-rank tests\, fitting the Cox proportional hazards model\, assessing the proportional hazards assumption\, and modeling time-varying covariates.  Experience in both survival analysis and R will be helpful but not necessarily required to follow the workshop material.
URL:https://workshops.ucla.edu/workshop/introduction-to-survival-analysis-in-r-4/
LOCATION:Zoom
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261105T100000
DTEND;TZID=America/Los_Angeles:20261105T110000
DTSTAMP:20260921T183014Z
CREATED:20260921T183014Z
LAST-MODIFIED:20260921T183014Z
UID:10003823-1793872800-1793876400@workshops.ucla.edu
SUMMARY:Introduction to Document Accessibility (Google docs\, Word\, PDF)
DESCRIPTION:This session provides an introduction to creating accessible documents in Google Docs\, Microsoft Word\, and PDFs. Participants will learn the fundamentals of digital accessibility\, including how to use proper heading structure\, write effective alt-text for images\, create descriptive links\, and ensure sufficient color contrast. The training will also demonstrate how to use built-in and automated accessibility checkers to identify and correct common issues.
URL:https://workshops.ucla.edu/workshop/introduction-to-document-accessibility-google-docs-word-pdf-7/
LOCATION:Zoom
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261105T100000
DTEND;TZID=America/Los_Angeles:20261105T120000
DTSTAMP:20260921T183014Z
CREATED:20260921T183014Z
LAST-MODIFIED:20260921T183014Z
UID:10003824-1793872800-1793880000@workshops.ucla.edu
SUMMARY:Interactive Computing on the Hoffman2 Cluster
DESCRIPTION:This hands-on session covers everything you need to work interactively on the Hoffman2 Cluster: navigating the filesystem\, loading software with Environment Modules\, and requesting compute resources through the job scheduler to launch TUI and GUI applications. We’ll then apply those same skills to a widely used case — running Jupyter Notebook or JupyterLab on the cluster\, tunneling in securely\, and working in Python/conda\, R\, Julia\, or another language of your choice. Ideal for researchers who want to explore tools\, test code\, or prototype analyses in real time.
URL:https://workshops.ucla.edu/workshop/interactive-computing-on-the-hoffman2-cluster/
LOCATION:OARC Portal\, Math Sciences 5628\, 5628 Math Science Building\, UCLA
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261105T130000
DTEND;TZID=America/Los_Angeles:20261105T150000
DTSTAMP:20260921T183015Z
CREATED:20260921T183015Z
LAST-MODIFIED:20260921T183015Z
UID:10003825-1793883600-1793890800@workshops.ucla.edu
SUMMARY:Data Visualization with Python II: Making Interactive Plots and Dashboards
DESCRIPTION:A static figure answers the question you chose in advance\, while an interactive one lets readers explore the data and ask their own: zooming into a region\, filtering to a subgroup\, or hovering to see underlying values. The second part of this series moves from static graphics to interactive visualization\, introducing common Python libraries for the task: Plotly and Altair for building interactive charts\, and Streamlit for assembling those charts into dashboards that others can use. We’ll also briefly survey where these tools reach their limits and what to use instead: Dash for production dashboards that need more control over layout and callbacks\, and the HoloViews\, Panel\, and Datashader ecosystem for datasets too large to render point by point. Finally\, we’ll touch on how to share the results\, from self-contained HTML files that need no server to applications deployed on shared infrastructure. We will go through several interactive exercises so that attendees can gain direct experience in using these libraries and will be prepared to learn more on their own after the workshop. Part I is useful background but not required; basic familiarity with Python and Pandas will be useful.
URL:https://workshops.ucla.edu/workshop/data-visualization-with-python-ii-making-interactive-plots-and-dashboards-4/
LOCATION:Zoom
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261109T090000
DTEND;TZID=America/Los_Angeles:20261112T120000
DTSTAMP:20261020T232330Z
CREATED:20260918T185132Z
LAST-MODIFIED:20261020T232330Z
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:20261020T232332Z
CREATED:20260924T193845Z
LAST-MODIFIED:20261020T232332Z
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:20261020T232333Z
CREATED:20260924T193845Z
LAST-MODIFIED:20261020T232333Z
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: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
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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
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END:VCALENDAR