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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240223T110000
DTEND;TZID=America/Los_Angeles:20240223T130000
DTSTAMP:20260404T021135
CREATED:20231204T223026Z
LAST-MODIFIED:20231205T041426Z
UID:24496-1708686000-1708693200@idre.ucla.edu
SUMMARY:Learning ChatGPT: An Accessible Introduction
DESCRIPTION:Since its launch in November 2022\, ChatGPT has rapidly become one of the most intriguing technological advancements of our time. In the first session of our “Learning ChatGPT” workshop series\, we will explore the significance and functionalities of ChatGPT. The session aims to provide a comprehensive understanding of what ChatGPT is\, its inherent limitations\, the breadth of its applications across diverse tasks\, and offers practical usage tips\, illustrated through concise demonstrations.\nThis workshop\, conducted in person\, is crafted for a broad general audience and does not require any prior technical knowledge or background. It presents a good opportunity for those curious about the advanced AI technologies\, seeking to comprehend and potentially apply ChatGPT in various domains. \nAny questions about this workshop can be emailed to Qiyang Hu (huqy@oarc.ucla.edu). \nRegister via Google \n 
URL:https://idre.ucla.edu/calendar-event/learning-chatgpt-an-accessible-introduction
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240226T130000
DTEND;TZID=America/Los_Angeles:20240226T160000
DTSTAMP:20260404T021135
CREATED:20231204T222303Z
LAST-MODIFIED:20231205T192202Z
UID:24486-1708952400-1708963200@idre.ucla.edu
SUMMARY:Introduction to Linear Regression in R
DESCRIPTION:This workshop teaches the basics of the linear regression model\, the foundation for most other regression models. Topics include understanding the model equation\, continuous and categorical predictors\, interpreting the model estimates\, and diagnostics for assessing model assumptions. The workshop is intended to be interactive\, with examples and exercises in R\, and assumes only introductory exposure to R. \nAny questions about this workshop can be emailed to Kotrina Kajokaite (kkajokaite@oarc.ucla.edu) and Andy Lin (alin@oarc.ucla.edu). \nRegister via Zoom
URL:https://idre.ucla.edu/calendar-event/introduction-to-linear-regression-in-r
LOCATION:Zoom
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240229T130000
DTEND;TZID=America/Los_Angeles:20240229T143000
DTSTAMP:20260404T021135
CREATED:20231204T223030Z
LAST-MODIFIED:20240108T201535Z
UID:24500-1709211600-1709217000@idre.ucla.edu
SUMMARY:Annotate Digital Imagery: Theory\, Applied Practice\, and Tools for Research
DESCRIPTION:Information systems since the advent of the World Wide Web have offered increasingly sophisticated and reliable tools for inquiry and scholarship based upon centuries-old practices of annotation. What are the connections and tensions between visual and verbal media? How do idiosyncratic readerly practices of scribbling in margins of a book translate into W3C standards for networked multimedia scholarly communication\, and what impacts will community standards development have upon the future of knowledge production (or your career)?\nThis workshop will provide a theoretical introduction to the ancient and still evolving social practice of annotation and situate leading ideas in the concrete tools and practices of digital knowledge production. Taking a 3-tiered approach (simple\, intermediate\, complex)\, it will present several handy tools for immediate and long-term application. \nThis workshop is part of the Research Collections and Digital Scholarship series — a collaboration between the Office of Advanced Research Computing (OARC) and the UCLA Digital Library Program. \nAny questions about this workshop can be emailed to Francesca Albrezzi (falbrezzi@ucla.edu) and Christopher Gilman (cjgilman@library.ucla.edu). \nThis is a hybrid workshop (OARC Portal or Zoom). \nRegister via Google
URL:https://idre.ucla.edu/calendar-event/annotate-digital-imagery-theory-applied-practice-and-tools-for-research
LOCATION:Hybrid: OARC Portal\, Math Sciences 5628 and Zoom
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240301T110000
DTEND;TZID=America/Los_Angeles:20240301T130000
DTSTAMP:20260404T021135
CREATED:20231204T223027Z
LAST-MODIFIED:20231205T041221Z
UID:24497-1709290800-1709298000@idre.ucla.edu
SUMMARY:Learning ChatGPT: A Deep Technical Dive
DESCRIPTION:Since its launch in November 2022\, ChatGPT has rapidly become one of the most intriguing technological advancements of our time. In the second session of our “Learning ChatGPT” workshop series\, we are set to undertake a deep technical dive into ChatGPT. This session will encompass an in-depth discussion on the transformer architecture\, explore fine-tuning techniques\, examine the developments of ChatGPT-like Large Language Models (LLMs)\, and present scientific application examples utilizing LLMs.\nThis in-person workshop is specifically tailored for an audience keen on understanding the technical intricacies of ChatGPT. It offers a unique opportunity to delve into the subject matter from a broader and more profound perspective. Participants with a basic understanding of machine learning or deep learning will be better positioned to appreciate the nuances and depths of the topics discussed. \nAny questions about this workshop can be emailed to Qiyang Hu (huqy@oarc.ucla.edu). \nRegister via Google
URL:https://idre.ucla.edu/calendar-event/learning-chatgpt-a-deep-technical-dive
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240301T113000
DTEND;TZID=America/Los_Angeles:20240301T123000
DTSTAMP:20260404T021135
CREATED:20240209T203023Z
LAST-MODIFIED:20240302T002639Z
UID:24712-1709292600-1709296200@idre.ucla.edu
SUMMARY:Computational approaches in clinical epigenomics
DESCRIPTION:Speaker: Fei-Man Hsu\, Ph.D.\nIDRE Fellow\nDepartment of Molecular\, Cell\, and Developmental Biology\nUniversity of California Los Angeles \n  \n  \n  \nTime: 11:30 AM – 12:30 PM (PST)\nDate: March 1\, 2024\nView recording: https://youtu.be/RVfoXBN66HU\n\n\n\n\nAbstract: DNA methylation signatures have high predictive value and could be used to predict health outcomes. Challenges remained in clinical studies such as the large population variations and the biopsy with mixed cell types which all contribute to DNA methylation dynamics. In this presentation I will introduce the computational approaches of clinical epigenomics with our recent research that applied targeted bisulfite sequencing (TBS-seq) to peripheral blood mononuclear cells (PBMCs) from 156 individuals before lung or kidney transplant in two medical centers to study the impact of cytomegalovirus (CMV) to the host epigenome. Cell type composition contributes most DNA methylation changes in PBMCs\, and we resolved the mixed cell type issue with a reference-based cell type deconvolution method. Lastly\, I will direct to a reference-free source-of-origin cell type classifier under development. \nAbout the speaker: Dr. Fei-Man Hsu is a postdoctoral fellow at the Pellegrini lab in the Department of Molecular\, Cell\, and Developmental Biology at UCLA. With a Ph.D. from the University of Tokyo\, Dr. Hsu specializes in bioinformatics. She holds a M.S. degree in Molecular and Cellular Biology\, and a B.S. degree in Life Science from National Taiwan University.
URL:https://idre.ucla.edu/calendar-event/idre-ecr-march-1-2024
CATEGORIES:Conferences and Seminars,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240304T130000
DTEND;TZID=America/Los_Angeles:20240304T160000
DTSTAMP:20260404T021135
CREATED:20231205T042823Z
LAST-MODIFIED:20231205T043336Z
UID:24553-1709557200-1709568000@idre.ucla.edu
SUMMARY:Zero-inflated and Hurdle models for Count Data in R
DESCRIPTION:This workshop introduces zero-inflated poisson\, zero-inflated negative binomial\, and hurdle models for count data\, which are two-part models used when more zeros are found in the data than expected with typical count distributions. We will discuss the formulations of the two parts of each model\, the interpretation of model parameters\, and how to run these models and analyze zero-inflated count data in R. \nFor questions about this workshop\, please contact Siavash Jalal (sjalal@oarc.ucla.edu).  \nRegister via Zoom
URL:https://idre.ucla.edu/calendar-event/zero-inflated-and-hurdle-models-for-count-data-in-r-3
LOCATION:Zoom
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240307T090000
DTEND;TZID=America/Los_Angeles:20240307T163000
DTSTAMP:20260404T021135
CREATED:20240305T063602Z
LAST-MODIFIED:20240305T063602Z
UID:24830-1709802000-1709829000@idre.ucla.edu
SUMMARY:Building a Database of Recorded Music Data for Analysis\, Research\, and Access - Developing the Database of Recorded Jewish Music (DRJM)
DESCRIPTION:Agenda: \n\n\n\n9:00 – 10:30 \nAddressing the Archive: Current State of Jewish Music Archives in the U.S \nTodd Presner\, UCLA: Chair and Opening Remarks \nJudy Pinnolis\, Berklee: An Overview of Academic Issues in Jewish Music Sound Recording Collections \nLorin Sklamberg\, YIVO Institute: Issues and Challenges Digitizing the YIVO Sound Archives \nSharon Benamou\, UCLA: Acquisitions and Cataloging Considerations in the UCLA Judaica Collectio \n\n\n10:30 – 10:45 \nBreak \n\n\n\n10:45 – 11:30 \nIntroducing the Database of Recorded Jewish Music (DRJM) \nMark Kligman\, UCLA: Project Origins\, Overarching Goals and Questions \nJeff Janeczko\, Milken Archive/UCLA: Pilot Study—Visualizing the Milken Archive \nDanielle Stein\, UCLA: Aggregating the Archives—Tableau as Tool for Research and Analysis \n\n\n11:30 – 12:15 \nPanel Response to the DRJM Introduction \nChair: Thomas Hodgson\, UCLA \nRandall Goldberg\, Cal State Fullerton \nMatthew Vest\, UCLA \nFrancesco Spagnolo\, UC Berkeley \nSam Brylawski\, UC Santa Barbara\, Library of Congress \n\n\n12:15 – 1:15 \nLunch (provided for invited participants) \n\n\n\n1:15 – 3:15 \nHands-on Workshop \nParticipants will create their own Tableau worksheets and dashboards using a predetermined subset of data from the DRJM. \nFacilitated by: Anna Bonazzi\, Jordan Galczynski\, and Wei Si Nic Yiu. \n\n\n3:15 – 3:30 \nBreak \n\n\n\n3:30 – 4:30 \nClosing Remarks and Discussion \nModerator: Sam Brylawski\, UC Santa Barbara\, Library of Congress \nMark Kligman\, UCLA \nJeff Janeczko\, Milken Archive/UCLA \nDanielle Stein\, UCLA 
URL:https://idre.ucla.edu/calendar-event/addressing-archive-03-07-2024
CATEGORIES:Classes and Workshops,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240308T110000
DTEND;TZID=America/Los_Angeles:20240308T143000
DTSTAMP:20260404T021135
CREATED:20240216T212407Z
LAST-MODIFIED:20240401T195759Z
UID:24733-1709895600-1709908200@idre.ucla.edu
SUMMARY:Using Topological Data Analysis to characterize fluctuations in brain activity patterns in healthy and patient populations
DESCRIPTION:Link to the recording:  https://youtu.be/CxpGAIjidvQ \n  \n  \nSpeaker: Prof. Manish Sagger\nTashia and John Morgridge Endowed Faculty Scholar in Pediatric Translational Medicine\, Stanford Maternal & Child Health Research Institute\nAssistant Professor\, Department of Psychiatry & Behavioral Sciences\nPrincipal Investigator\, Brain Dynamics Lab\nStanford University School of Medicine  \n  \nAbstract: Understanding the neurobiological underpinnings of psychiatric disorders has long been a challenge. This talk addresses this issue by exploring how noninvasive neuroimaging\, despite its inherent limitations\, can be leveraged to anchor psychiatric disorders into neurobiology. Two main challenges in this endeavor are identified: (a) the inherent noise in noninvasive neuroimaging devices and (b) the limited utilization of biophysical models. To tackle the first challenge\, we propose the application of Topological Data Analysis (TDA)\, specifically Mapper\, as a novel approach. I present some promising results on how Mapper can capture evoked transitions during tasks\, intrinsic transitions during resting states\, changes in the landscape or shape associated with psychiatric disorders\, and various pharmacological interventions and neuromodulation techniques. I will highlight a few methodological advances for Mapper that could enhance its applicability in noninvasive neuroimaging studies. Finally\, the talk concludes by posing open questions to understand the neurobiological basis of psychiatric disorders better and pave the way for innovative therapeutic strategies. \nDemo talk title: A short tutorial on Topological Data Analysis based Mapper approach \nAbstract: In this tutorial\, I will introduce and provide a high-level overview of Topological Data Analysis\, mainly the Mapper approach. The hands-on portion of this tutorial will include a brief introduction to the DyNeuSR package from my lab (more information here – https://braindynamicslab.github.io/dyneusr/). DyNeuSR is a Python visualization library for topological representations of neuroimaging data. Developed with neuroimaging data analysis in mind\, DyNeuSR connects existing implementations of Mapper (e.g. KeplerMapper) with network analysis tools (e.g. NetworkX) and other neuroimaging data visualization libraries (e.g. Nilearn) and provides a high-level interface for interacting with and manipulating shape graph representations of neuroimaging data and relating these representations to neurophysiology. \nAbout the presenter: Manish Saggar is an assistant professor in the Psychiatry & Behavioral Sciences department at Stanford University and currently directs the Brain Dynamics Lab. His lab aims to develop computational methods for anchoring psychiatric diagnosis into biological features (e.g.\, neural circuits and spatiotemporal neurodynamics). Manish received his Ph.D. in Computer Science from the University of Texas at Austin and later received postdoctoral training in Psychiatry from Stanford University.
URL:https://idre.ucla.edu/calendar-event/topological-data-analysis-march-8-2024
CATEGORIES:Classes and Workshops,Conferences and Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240311T130000
DTEND;TZID=America/Los_Angeles:20240311T160000
DTSTAMP:20260404T021135
CREATED:20231205T043212Z
LAST-MODIFIED:20231205T043314Z
UID:24556-1710162000-1710172800@idre.ucla.edu
SUMMARY:Introduction to Mediation Models in Mplus
DESCRIPTION:This workshop will introduce mediation (i.e.\, causal) models using Mplus. Explanations of the syntax and output will be given\, as well as some tips about reporting such analyses. Models with latent variables will not be discussed. \nFor questions about this workshop\, contact Christine Wells (crwells@ucla.edu).  \nRegister via Zoom
URL:https://idre.ucla.edu/calendar-event/introduction-to-mediation-models-in-mplus-3
LOCATION:Zoom
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240315T113000
DTEND;TZID=America/Los_Angeles:20240315T123000
DTSTAMP:20260404T021135
CREATED:20240306T015538Z
LAST-MODIFIED:20240306T015811Z
UID:24837-1710502200-1710505800@idre.ucla.edu
SUMMARY:ACCESS – Advanced computing systems and services for university researchers
DESCRIPTION:RSVP link: https://ucla.zoom.us/meeting/register/tJwrcuiprj8pEtb0HFIN3H1PdxN-B6_IkDps \nThe US National Science Foundation supports an ecosystem of computing facilities housing some of the most advanced supercomputers and high-end visualization and data analysis resources. Its ACCESS program is to help researchers and educators\, with or without supporting grants\, to utilize the nation’s advanced computing systems and services. Its computing facilities provide “free” computing cycles at scale\, storage\, and other services. These resources are available through an application process based on the merit of the research objectives and demonstration of the efficacy and parallel scalability of the software. \nThis presentation aims to explain the capabilities of various computing facilities under the ACCESS program. The discussion will also discuss how a UCLA researcher can transition from local computing systems to take advantage of the “free” advanced computing and data resources.
URL:https://idre.ucla.edu/calendar-event/access-program-march-15-2024
CATEGORIES:Education and Training,Meetings,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240328T113000
DTEND;TZID=America/Los_Angeles:20240328T123000
DTSTAMP:20260404T021135
CREATED:20240308T010052Z
LAST-MODIFIED:20240401T194223Z
UID:24846-1711625400-1711629000@idre.ucla.edu
SUMMARY:Interacting Dynamical System Modeling for Science: Construction\, Generalization\, and Applications
DESCRIPTION:Speaker: Xiao Luo\, Ph.D.\nIDRE Fellow\nDepartment of Computer Science\nUniversity of California Los Angeles   Time: 11:30 AM – 12:30 PM (PST)\nDate: March 28\, 2024 \nLink to the recording: https://youtu.be/0_WwPe-kV-Q\n\n\n\n\nAbstract: Many real-world systems such as disease transmission\, molecular dynamics\, and spring systems can be considered as multi-agent dynamical systems\, where multiple objects interact with each other and exhibit complex behavior along the time. In this talk\, I will discuss my current research on interacting dynamics system modeling for scientific problems\, especially focusing on model construction and model generalization. I will begin by discussing my work on graph ODEs for efficiently capturing continuous high-order correlations. Then\, I will discuss different types of distribution shifts in dynamical system modeling and how to address them to improve the generalization ability. Finally\, I will introduce future research directions in the field of dynamical system modeling. \nAbout the speaker: Dr. Xiao Luo is a postdoctoral researcher at UCLA’s Department of Computer Science. Previously\, he received a B.S. degree in Mathematics from Nanjing University\, Nanjing\, China\, in 2017 and a Ph.D. in the School of Mathematical Sciences from Peking University\, Beijing\, China in 2022. His research interests include machine learning on graphs\, dynamical systems\, statistical models\, and AI for Science.
URL:https://idre.ucla.edu/calendar-event/ecr-march-28-2024
CATEGORIES:Conferences and Seminars,Education and Training,Meetings,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240402T100000
DTEND;TZID=America/Los_Angeles:20240402T100000
DTSTAMP:20260404T021135
CREATED:20240308T222824Z
LAST-MODIFIED:20240411T160002Z
UID:24861-1712052000-1712052000@idre.ucla.edu
SUMMARY:HPC@UCLA: Intro to H2C (Hoffman2 Cluster)
DESCRIPTION:The Hoffman2 Cluster is a powerful computational resource for the UCLA research community. Come and learn what is it and how you can get started using it. \nInstructor: Raffaella D’Auria \nRegister via Zoom
URL:https://idre.ucla.edu/calendar-event/hpcucla-intro-to-h2c-hoffman2-cluster
LOCATION:Zoom
CATEGORIES:Training workshop / Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240416T100000
DTEND;TZID=America/Los_Angeles:20240416T100000
DTSTAMP:20260404T021135
CREATED:20240308T222826Z
LAST-MODIFIED:20240411T155946Z
UID:24862-1713261600-1713261600@idre.ucla.edu
SUMMARY:HPC@UCLA: Working at the UNIX shell & Environmental Modules on H2C
DESCRIPTION:Knowledge of Linux is key to successfully using most HPC resources\, including the Hoffman2 Cluster. This workshop introduces users to basic usage of the command line interface (CLI)\, basic file manipulation and the filesystem hierarchy. Environmental modules and modification of the user environment will also be introduced. \nInstructor: Raffaella D’Auria \nRegister via Zoom
URL:https://idre.ucla.edu/calendar-event/hpcucla-working-at-the-unix-shell-environmental-modules-on-h2c
LOCATION:Zoom
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240418T090000
DTEND;TZID=America/Los_Angeles:20240418T090000
DTSTAMP:20260404T021135
CREATED:20240308T222841Z
LAST-MODIFIED:20240411T155924Z
UID:24868-1713430800-1713430800@idre.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. 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. \nInstructor: Ben Winjum \nRegister via Zoom
URL:https://idre.ucla.edu/calendar-event/data-visualization-with-python-i-plotting-fundamentals-4
LOCATION:Zoom
CATEGORIES:Training workshop / Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240419T103000
DTEND;TZID=America/Los_Angeles:20240419T103000
DTSTAMP:20260404T021135
CREATED:20240308T222842Z
LAST-MODIFIED:20240411T155910Z
UID:24871-1713522600-1713522600@idre.ucla.edu
SUMMARY:Introduction to Network Analysis Tools and Methodologies
DESCRIPTION:Network analysis allows for the modeling of connections between people\, places\, concepts\, and entities in nearly any field of study. We can visualize\, describe\, and even predict these connections by treating them as data through the use of widely available and free tools.\nThis workshop will introduce participants to the field of network analysis\, with an emphasis on its use for data-driven humanities research. Upon completion of the workshop\, participants will be familiar with important concepts and trends in network analysis\, be able to construct a basic network from a spreadsheet\, run common network analytics\, and visualize the results using both their own machines and UCLA high performance computing resources. No prior knowledge of network analysis or programming is required or expected. \nInstructor: Ryan Horne \nRegister via Zoom
URL:https://idre.ucla.edu/calendar-event/introduction-to-network-analysis-tools-and-methodologies
LOCATION:Zoom
CATEGORIES:Training workshop / Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240425T090000
DTEND;TZID=America/Los_Angeles:20240425T090000
DTSTAMP:20260404T021135
CREATED:20240308T222842Z
LAST-MODIFIED:20240411T155852Z
UID:24869-1714035600-1714035600@idre.ucla.edu
SUMMARY:Data Visualization with Python II: Making Interactive Plots and Dashboards
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 second part of this series will explore various ways that Python can be used to make interactive graphics that enhance one’s ability to explore data and conceptualize trends and dependencies. We’ll dive into Python libraries for making interactive widgets\, plots\, and dashboards. These will be covered in interactive exercises so that attendees can gain direct experience in using these libraries. Basic familiarity with Python will be useful. \nInstructor: Ben Winjum \nRegister via Zoom
URL:https://idre.ucla.edu/calendar-event/data-visualization-with-python-ii-making-interactive-plots-and-dashboards-2
LOCATION:Zoom
CATEGORIES:Training workshop / Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240430T100000
DTEND;TZID=America/Los_Angeles:20240430T100000
DTSTAMP:20260404T021135
CREATED:20240308T222826Z
LAST-MODIFIED:20240411T155837Z
UID:24863-1714471200-1714471200@idre.ucla.edu
SUMMARY:HPC@UCLA: Jupyter Notebooks/ JupyterLan on H2C
DESCRIPTION:Jupyter Notebook and JupyterLab are a powerful tool for interactive computing and for proof of concept implementations. Come and learn how to open jupyter sessions on your local browser while harnessing the computing power on the Hoffman2 Cluster. Work in a conda/python environment\, in R\, julia or many other programming languages. \nInstructor: Raffaella D’Auria \nRegister via Zoom
URL:https://idre.ucla.edu/calendar-event/hpcucla-jupyter-notebooks-jupyterlan-on-h2c
LOCATION:Zoom
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240501T113000
DTEND;TZID=America/Los_Angeles:20240501T113000
DTSTAMP:20260404T021135
CREATED:20240308T222821Z
LAST-MODIFIED:20240411T155819Z
UID:24857-1714563000-1714563000@idre.ucla.edu
SUMMARY:Optimizing research with GPUs on Hoffman2
DESCRIPTION:This workshop caters to computing professionals and researchers eager to push the boundaries of high-performance computing using GPUs. Tailored for an audience that ranges from novices to experienced users\, the workshop covers the essentials of GPU computing\, with a special focus on leveraging these powerful processors within Python and R environments as well as other GPU codes. Attendees will dive into CUDA programming for NVIDIA GPUs\, mastering memory management techniques and parallel computing strategies to significantly enhance computational efficiency. \nInstructor: Charles Peterson \nRegister via Zoom
URL:https://idre.ucla.edu/calendar-event/optimizing-research-with-gpus-on-hoffman2
LOCATION:Zoom
CATEGORIES:Training workshop / Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240514T100000
DTEND;TZID=America/Los_Angeles:20240514T100000
DTSTAMP:20260404T021135
CREATED:20240308T222826Z
LAST-MODIFIED:20240411T155749Z
UID:24864-1715680800-1715680800@idre.ucla.edu
SUMMARY:HPC@UCLA: Interactive Computing on H2C
DESCRIPTION:Learn how to perform interactive computing on the Hoffman2 Cluster. From requesting the computational resources needed for your interactive session to loading and starting TUI and GUI applications. \nInstructor: Raffaella D’Auria \nRegister via Zoom
URL:https://idre.ucla.edu/calendar-event/hpcucla-interactive-computing-on-h2c
LOCATION:Zoom
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240517T100000
DTEND;TZID=America/Los_Angeles:20240517T100000
DTSTAMP:20260404T021135
CREATED:20240308T222827Z
LAST-MODIFIED:20240411T155721Z
UID:24866-1715940000-1715940000@idre.ucla.edu
SUMMARY:High Performance Python for Data Analytics (1)
DESCRIPTION:While Python has been the most popular programming language since 2019\, data scientists often critique its slow speed and limited capabilities in handling big data scenarios. In this workshop series\, we’ll tackle how to enhance Python’s performance in data science by diving deep into its workings and leveraging technologies to transform Python into an effective tool for high-performance big data analytics.\nIn our first 2-hour session\, we’ll concentrate on significantly accelerating Python code at the interpreter level. We’ll demystify concepts such as the GIL and JIT and introduce packages like PyPy\, Numba\, Pythran\, and Cython. While there are no strict prerequisites for this lecture\, prior programming experience in Python will be advantageous for a complete understanding of the material. \nInstructor: Qiyang Hu \nRegister via Zoom
URL:https://idre.ucla.edu/calendar-event/high-performance-python-for-data-analytics-1
LOCATION:Zoom
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240520T130000
DTEND;TZID=America/Los_Angeles:20240520T130000
DTSTAMP:20260404T021135
CREATED:20240308T222822Z
LAST-MODIFIED:20240411T155706Z
UID:24858-1716210000-1716210000@idre.ucla.edu
SUMMARY:R Graphics: Introduction to ggplot2
DESCRIPTION:This seminar teaches the “grammar” of graphics that underlies the ggplot2 package\, allowing the user to build eye-catching\, publication-quality graphics layer-by-layer. We will cover the basic elements of the grammar of graphics\, including aesthetics\, geoms\, scales\, and themes\, and we will show you how easy ggplot2 makes it to integrate these elements to make informative and beautiful graphics. The seminar is meant to be interactive with attendees participating in the coding\, so some very basic R coding knowledge is helpful but not required. \nInstructor: Kotrina Kajokaite \nWorkshop materials \nRegister via Zoom
URL:https://idre.ucla.edu/calendar-event/r-graphics-introduction-to-ggplot2-5
LOCATION:Zoom
CATEGORIES:Training workshop / Tutorial
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240523T100000
DTEND;TZID=America/Los_Angeles:20240523T100000
DTSTAMP:20260404T021135
CREATED:20240308T222842Z
LAST-MODIFIED:20240411T155649Z
UID:24870-1716458400-1716458400@idre.ucla.edu
SUMMARY:Cloud Computing Workshops: Build your own HPC cluster on the cloud
DESCRIPTION:Cloud computing service enables users to access various computing resources such as applications\, storage\, databases\, and even machine learning. This workshop will cover how to create your own high-performance computing cluster with a job scheduler on the cloud service\, based on the knowledge of compute instance and storage. By doing this\, the users can run serial (e.g.\, job array) or parallel (e.g.\, MPI) jobs on the cloud more efficiently. \nInstructor: Jerry Huang \nRegister via Zoom
URL:https://idre.ucla.edu/calendar-event/cloud-computing-workshops-build-your-own-hpc-cluster-on-the-cloud
LOCATION:Zoom
CATEGORIES:Training workshop / Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240524T100000
DTEND;TZID=America/Los_Angeles:20240524T100000
DTSTAMP:20260404T021135
CREATED:20240308T222841Z
LAST-MODIFIED:20240411T155625Z
UID:24867-1716544800-1716544800@idre.ucla.edu
SUMMARY:High Performance Python for Data Analytics (2)
DESCRIPTION:While Python has been the most popular programming language since 2019\, data scientists often critique its slow speed and limited capabilities in handling big data scenarios. In this workshop series\, we’ll tackle how to enhance Python’s performance in data science by diving deep into its workings and leveraging technologies to transform Python into an effective tool for high-performance big data analytics.\nIn the second 2-hour session\, our focus will be on techniques for loading and processing extremely large datasets in Python on a single machine\, comparing dataframe implementations from Pandas\, Modin\, Pandarallel\, Dask\, and Vaex\, among others. No specific prerequisites are required to join the lecture\, but familiarity with Python’s numpy and Pandas packages will aid in fully grasping the discussed content. \nInstructor: Qiyang Hu \nRegister via Zoom
URL:https://idre.ucla.edu/calendar-event/high-performance-python-for-data-analytics-2
LOCATION:Zoom
CATEGORIES:Training workshop / Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240528T100000
DTEND;TZID=America/Los_Angeles:20240528T100000
DTSTAMP:20260404T021135
CREATED:20240308T222826Z
LAST-MODIFIED:20240411T155609Z
UID:24865-1716890400-1716890400@idre.ucla.edu
SUMMARY:HPC@UCLA: Batch Job Submission on H2C
DESCRIPTION:Batch computing enables you to execute concurrently or independently a large number of simulations\, practically scaling up your ability to conduct research. Come and learn the basics of how to submit jobs\, how to request resources and how to take advantage of very many CPU and GPU cores on the Hoffman2 Cluster. \nInstructor: Raffaella D’Auria \nRegister via Zoom
URL:https://idre.ucla.edu/calendar-event/hpcucla-batch-job-submission-on-h2c
LOCATION:Zoom
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240531T113000
DTEND;TZID=America/Los_Angeles:20240531T123000
DTSTAMP:20260404T021135
CREATED:20240508T030807Z
LAST-MODIFIED:20240531T214334Z
UID:24988-1717155000-1717158600@idre.ucla.edu
SUMMARY:Challenges to mitigating climate change drivers and associated risks of surpassing lower emission targets
DESCRIPTION:  \n\n\n\nSpeaker: Robert Fofrich\, Ph.D.\nIDRE and UC President’s Postdoctoral Fellow\nInstitute of the Environment and Sustainability\nUniversity of California Los Angeles    \n\nPlace: Virtual (Link to the video recording)\n\n\n\n\n\n\nAbstract: Lower climate change mitigation pathways require large and swift reductions in anthropogenic CO2 emissions worldwide\, a substantial portion arising from fossil energy sources utilized in electricity generation. Thus\, stabilizing global mean temperatures at or below 2 degrees necessitates retiring fossil-burning infrastructure well before their operational lifespans have elapsed\, resulting in stranded assets worldwide. However\, sizable investments in fossil energy infrastructure have continued to rise globally\, posing a threat to international climate change mitigation\, food security\, and financial objectives. Thus\, we will discuss challenges associated with attaining lower climate warming targets and the potential repercussions for global agriculture and human well-being if these targets are exceeded. \nAbout the speaker: Dr. Fofrich was born in East Los Angeles and is an alumnus of West Los Angeles College. Currently\, he is a UC President’s Postdoctoral Fellow at the Institute of the Environment and Sustainability and works under the supervision of Dr. Elsa Ordway and Dr. Thomas Smith within the Department of Ecology and Evolutionary Biology. Before joining UCLA\, Dr. Fofrich joined the Climate Impact lab and was briefly a postdoctoral scholar in the Department of Earth and Planetary Sciences at Rutgers University. Dr. Fofrich received his Ph.D. in 2022 from the Department of Earth System Science at the University of California\, Irvine\, where his research focused on energy and agricultural systems as they relate to climate change mitigation and adaptation. He has also served as a researcher at NASA-JPL and the Center for Environmental Biology in Orange County\, California. His passion for the natural environment and a profound commitment to underserved communities steered his decision to study ways to mitigate anthropogenic environmental damages and protect vulnerable populations from these changes.
URL:https://idre.ucla.edu/calendar-event/robert-fofrich-may-31-2024
CATEGORIES:Conferences and Seminars,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240603T130000
DTEND;TZID=America/Los_Angeles:20240603T130000
DTSTAMP:20260404T021135
CREATED:20240308T222823Z
LAST-MODIFIED:20240411T155538Z
UID:24860-1717419600-1717419600@idre.ucla.edu
SUMMARY:Applies Survey Data Analysis in SPSS
DESCRIPTION:The workshop will introduce the basic concepts and elements necessary to analyze data collected via a complex sampling design. The workshop will use SPSS Complex Samples to conduct descriptive analyses. Examples of subpopulation analyses will be given\, as well as examples of linear and logistic regression models. \nInstructor: Christine Wells \nRegister via Zoom
URL:https://idre.ucla.edu/calendar-event/applies-survey-data-analysis-in-spss
LOCATION:Zoom
CATEGORIES:Training workshop / Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240610T130000
DTEND;TZID=America/Los_Angeles:20240610T160000
DTSTAMP:20260404T021135
CREATED:20240308T222823Z
LAST-MODIFIED:20240411T155228Z
UID:24859-1718024400-1718035200@idre.ucla.edu
SUMMARY:Analysis and Visualization of interactions in R
DESCRIPTION:In regression\, we are often interested in an interaction\, which is the modification or moderation of the effect of an independent variable by another. Understanding interactions involves interpreting the regression coefficients\, estimating and testing simple effects and their differences\, and visualizing the interaction. This workshop will teach you how to do all of these thing in R using base R\, as well as the emmeans and ggplot2 packages. Some prior knowledge of linear regression and experience with R is recommended but not necessary. \nInstructor: Siavash Jalal \nRegister via Zoom \nWorkshop materials
URL:https://idre.ucla.edu/calendar-event/analysis-and-visualization-of-interactions-in-r
LOCATION:Zoom
CATEGORIES:Training workshop / Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240628T113000
DTEND;TZID=America/Los_Angeles:20240628T123000
DTSTAMP:20260404T021135
CREATED:20240620T183709Z
LAST-MODIFIED:20240701T220736Z
UID:25039-1719574200-1719577800@idre.ucla.edu
SUMMARY:TimeAutoDiff : Combining auto-encoder and diffusion model for time series tabular synthesizing
DESCRIPTION:  \n  \n\n\n\nSpeaker: Najoon Suh\, Ph.D \nIDRE Fellow \nDepartment of Statistics and Data Science \nUniversity of California Los Angeles \n  \nLocation: Zoom (Recording link)\n\n\n\n\n  \nAbstract: In the work to be presented\, we leverage the power of latent diffusion models to generate synthetic time series tabular data. Along with the temporal and feature correlations\, the heterogeneous nature of the feature in the table has been one of the main obstacles in time series tabular data modeling. We tackle this problem by combining the ideas of the variational auto-encoder (VAE) and the denoising diffusion probabilistic model (DDPM). Our model\, named “TimeAutoDiff\,” has several key advantages\, including (1) Generality\, the ability to handle the broad spectrum of time series tabular data from single to multi-sequence datasets; (2) Good fidelity and utility guarantees: numerical experiments on six publicly available datasets demonstrating significant improvements over state-of-the-art models in generating time series tabular data\, across four metrics measuring fidelity and utility; (3) Fast sampling speed: entire time series data generation as opposed to the sequential data sampling schemes implemented in the existing diffusion-based models\, eventually leading to significant improvements in sampling speed\, (4) Entity conditional generation: the first implementation of conditional generation of multi-sequence time series tabular data with heterogenous features in the literature\, enabling scenario exploration across multiple scientific and engineering domains.\n\n\nAbout the speaker: Dr. Namjoon Suh is a UCLA adjunct assistant professor. He is an IDRE fellow and is associated with Prof. Dr. Guang Cheng’s lab in the UCLA Statistics and Data Science Department. He obtained his Machine Learning Ph.D. degree at Stewart School of Industrial & Systems Engineering\, Georgia Tech\, in December 2022 and earned an M.Sc. in Statistics at Georgia Tech in 2018. Before Georgia Tech\, he received a B.Sc. degree from Korea University in 2015\, majoring in Industrial Engineering.
URL:https://idre.ucla.edu/calendar-event/ecr-june-28-2024
CATEGORIES:Conferences and Seminars,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240731T080000
DTEND;TZID=America/Los_Angeles:20240801T140000
DTSTAMP:20260404T021135
CREATED:20240702T215957Z
LAST-MODIFIED:20240709T171325Z
UID:25071-1722412800-1722520800@idre.ucla.edu
SUMMARY:Workshop on Machine Learning and Big Data
DESCRIPTION:UCLA-IDRE  is pleased to host a two-day\, in-person\, Big Data workshop (July 31 – August 1\, 2024\, 8 AM-2 PM each day) organized by Pittsburgh Supercomputing Center. \nThis workshop will focus on big data analytics\, machine learning using Spark\, and deep learning using TensorFlow. It is an in-person workshop presented using the Wide Area Classroom (WAC) training platform in OARC Portal (5628 Math Science Building). \nRegistration: \nInterested applicants must first have an ACCESS ID.  If you do not have an ACCESS ID\, please visit this page to create one: \nACCESS USER REGISTRATION \nOnce you have an ACCESS ID\, please send an email (indicating your ACCESS ID and which site you wish to attend) to Tom Maiden at tmaiden@psc.edu by Friday\, July 26\, at Noon Eastern time. \nFurther details will be provided once your registration has been processed. \n  \nTentative Agenda: \nDay – 1:\n \n\n\n\nWednesday\, July 31\, 2024\nAll times given are Pacific\n\n\n08:00 AM\nWelcome\n\n\n08:25 AM\nA Brief History of Big Data\n\n\n09:20 AM\nIntro to Spark\n\n\n10:00 AM\nLunch Break\n\n\n11:00 AM\nMore Spark and Exercises\n\n\n02:00 PM\nIntro to Machine Learning\n\n\n02:00 PM\nAdjourn\n\n\n\nDay – 2: \n\n\n\nThursday\, August 1\, 2024\nAll times given are Pacific\n\n\n08:00 AM\nMachine Learning: Recommender System with Spark\n\n\n10:00 AM\nLunch break\n\n\n11:00 AM\nDeep Learning with TensorFlow\n\n\n02:00 PM\nTying it All Together\n\n\n02:30 PM\nAdjourn\n\n\n\n\n\nNote: Please visit the PSC’s website for details about the agenda. You are also welcome to contact tvsingh@ucla.edu if you have any questions about this workshop at UCLA.
URL:https://idre.ucla.edu/calendar-event/workshop-on-machine-learning-and-big-data
CATEGORIES:Classes and Workshops,Education and Training,Training workshop / Tutorial
ORGANIZER;CN="T V Singh":MAILTO:tvsingh@ucla.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240805T130000
DTEND;TZID=America/Los_Angeles:20240805T160000
DTSTAMP:20260404T021135
CREATED:20240614T185949Z
LAST-MODIFIED:20240614T190156Z
UID:25029-1722862800-1722873600@idre.ucla.edu
SUMMARY:R Markdown Basics
DESCRIPTION:R Markdown files integrate text\, Markdown\, and R code into dynamic documents that weave together plain text\, formatted text\, and the output of the R code. The resulting dynamic reports can be produced in many formats\, including HTML documents\, HTML slideshows\, LaTeX pdf\, Beamer slideshows\, MS Word doc\, books\, scientific articles\, and websites. This seminar covers basic coding and conventions of the 3 frameworks upon which R Markdown depends: Markdown for formatting text\, knitr for R code chunks\, and YAML for rendering the document. The seminar does not assume any previous experience with R Markdown\, but attendees who wish to participate in seminar demonstrations should come with RStudio and R Markdown installed on their computers. \nInstructor: Kotrina Kajokaite \nRegister Now via Zoom
URL:https://idre.ucla.edu/calendar-event/r-markdown-basics-4
LOCATION:Zoom
CATEGORIES:Training workshop / Tutorial
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END:VCALENDAR