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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220324T100000
DTEND;TZID=America/Los_Angeles:20220324T130000
DTSTAMP:20260406T070525
CREATED:20220311T003918Z
LAST-MODIFIED:20220401T211542Z
UID:22861-1648116000-1648126800@idre.ucla.edu
SUMMARY:Open Science Workshop
DESCRIPTION:IDRE ECR Group is excited to announce Open Science workshop with the following details: \nTitle: Open Science \nDate and Time: Thursday\, March 24\, 2022 @10 AM (PST) \nVideo recordings: Part-1. Part-2 \nAbstract: As the culture and context of academic research evolve with the times\, there is a growing realization of the need and power in adopting open science practices\, methodologies\, technology\, and academic environments which support these changes. Transparency\, data/code/blueprint-sharing\, and modular shared computational infrastructure\, increase the number and quality of research tool sets within reach of nearly any academic entity\, therefore bringing more intellect and effort to bear on burning scientific questions that modern civilization faces as a whole. The workshop will highlight several aspects of open science\, including open hardware\, shared data and code-ecosystem in computationally-empowering cloud environments\, geographically-distributed aggregate-cpu computational infrastructure\, and data resources for precision health research in medical sciences. \nTentative agenda: Thursday\, March 24\, 2022 at 10 AM (PST) \n\n\n\nTime (PST)\nPresentation title (speaker)\n\n\n10:30 AM – 10:40 AM\nWelcome and Introduction\n\n\n10:40 AM – 11:15 AM\nOpen science computing framework – SW/Cloud-environment/Datasets (Julius Buescke/PANGEO)\n\n\n11:15 AM – 11: 25 AM\nBreak\n\n\n11:25 AM – 12:00 PM\nData resources for precision health research (Clara M Lajonchere)\n\n\n12:00 PM – 12:35 PM\nOpen Infrastructure (Frank Wuerthwein/OSG)\n\n\n\n 
URL:https://idre.ucla.edu/calendar-event/open-science-workshop
CATEGORIES:Classes and Workshops,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220322T110000
DTEND;TZID=America/Los_Angeles:20220322T120000
DTSTAMP:20260406T070525
CREATED:20220308T171615Z
LAST-MODIFIED:20220901T205335Z
UID:22784-1647946800-1647950400@idre.ucla.edu
SUMMARY:Hoffman2 Happy Hour: What is the Hoffman2 Cluster and what it can do for you\, how to get an account + Q&A
DESCRIPTION:The Hoffman2 Happy Hours are designed to showcase one cluster related topic in a short presentation (no more than 20 minutes and generally much less) or lightning talk format\, to be followed by 30 to 40 minutes of discussion and user support (office hour style). Each Hoffman2 Happy Hour meeting is 50 minutes long. Bring your computational questions (they do not have to be strictly related to the topic of the week) or just your curiosity. Examples and hands-on components related to the topic of the week will be part of each meeting. \nAny questions about this workshop can be emailed to dauria@oarc.ucla.edu. \nRegister here: https://ucla.zoom.us/meeting/register/tJYod–upzouHNz90smcsyt93yqe8LneDhD4
URL:https://idre.ucla.edu/calendar-event/hoffman2-happy-hour-what-is-the-hoffman2-cluster-and-what-it-can-do-for-you-how-to-get-an-account-qa
LOCATION:Zoom
CATEGORIES:Classes and Workshops,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220308T130000
DTEND;TZID=America/Los_Angeles:20220308T160000
DTSTAMP:20260406T070525
CREATED:20211214T204913Z
LAST-MODIFIED:20220901T205307Z
UID:22550-1646744400-1646755200@idre.ucla.edu
SUMMARY:Introduction to Mediation Models with the PROCESS macro in SPSS
DESCRIPTION:Registration: https://ucla.zoom.us/meeting/register/tJIlcuCpqzwoGt3dCRZ50lDgXWadWKeYfc2r \nThis workshop will introduce the PROCESS Macro in SPSS (written by Andrew Hayes).  Basic models will be demonstrated.  Explanations of the syntax and output will be given\, as well as some tips about reporting such analyses. \n 
URL:https://idre.ucla.edu/calendar-event/introduction-to-mediation-models-with-the-process-macro-in-spss
LOCATION:Zoom
CATEGORIES:Classes and Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220301T130000
DTEND;TZID=America/Los_Angeles:20220301T160000
DTSTAMP:20260406T070525
CREATED:20211214T204435Z
LAST-MODIFIED:20220901T205231Z
UID:22545-1646139600-1646150400@idre.ucla.edu
SUMMARY:Introduction to Generalized Linear Regression Models in R
DESCRIPTION:Registration: https://ucla.zoom.us/meeting/register/tJUud-6uqTwiGtNZEtt6vy5VApsl6AE8BJVM \nIn this workshop we discuss generalized linear models and why and when we need to use them. We will discuss several generalized linear modes such as logistic\, Poisson\, and negative binomial and how we run them in R. The seminar briefly reviews regression concepts as necessary\, but it is assumed that participants have basic understanding of linear regression models (see the Introduction to Regression in R workshop). It also assumed that participants have basic familiarity with R (see the Introduction to R seminar for a tutorial).
URL:https://idre.ucla.edu/calendar-event/introduction-to-generalized-linear-regression-models-in-r
LOCATION:Zoom
CATEGORIES:Classes and Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220225T140000
DTEND;TZID=America/Los_Angeles:20220225T153000
DTSTAMP:20260406T070525
CREATED:20211214T204343Z
LAST-MODIFIED:20220901T205155Z
UID:22543-1645797600-1645803000@idre.ucla.edu
SUMMARY:Scientific Visualization with Paraview
DESCRIPTION:Paraview is an open-source cross-platform program for interactive scientific visualization. Paraview can run as a stand-alone visualization tool\, as well as in a client-server fashion for remote visualization. In this tutorial\, we will explore the visualization pipeline and basic features in Paraview. We will show how to prepare data files from scratch. We will demonstrate how to use Paraview’s remote visualization capability\, in which the Paraview graphical user interface is run on the user’s computer while the data sets reside on a remote HPC cluster\, using Hoffman2 Cluster as an example. \nRegistration: https://ucla.zoom.us/meeting/register/tJErc–vrz0pGdOZeogIJm-pLrJOIqaDR3M1
URL:https://idre.ucla.edu/calendar-event/scientific-visualization-with-paraview
LOCATION:Zoom
CATEGORIES:Classes and Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220225T113000
DTEND;TZID=America/Los_Angeles:20220225T123000
DTSTAMP:20260406T070525
CREATED:20220210T193439Z
LAST-MODIFIED:20220226T092741Z
UID:22725-1645788600-1645792200@idre.ucla.edu
SUMMARY:Creating a Comprehensive Lexical Resource for English Using Bayesian Deep Learning and Missing Data Methodology
DESCRIPTION:  \n \n  \nSpeaker: Bryor Snefjella\, Ph.D.\nIDRE Scholar\,\nPsychology Department\,\nUniversity of California Los Angeles \nVideo Recording: https://youtu.be/RTpW1-FtBGs \n  \nAbstract: Inquiry in the language sciences makes extensive use of open-source data sets. For example\, data sets of hand-annotations of words for properties such as their connotation and familiarity. Other common types of open-source resources include behavioural or neuroimageing recordings of responses to linguistic stimuli in controlled experiments\, or measurements taken from massive respositories of digitized natural language use. A challenge in the language sciences is extensive missing data in extant open-source data sets. Most data sets contain information on orders of magnitude fewer words than an average speaker knows\, and the words they do contain are non-randomly sampled and non-overlapping. A commonly proposed remedy to this missing data is to replace hand-annotation with machine learning. This is the approach taken by the English Lexicon Imputation Project\, the first comprehensive resource of word-level annotations created in cognitive science. In this talk I present the resource\, the Bayesian deep neural network used to create it\, and how missing data methodology was key to overcoming the limitations of prior literature on computational linguistic resource generation. The talk should be of interest to computational social scientists\, language scientists\, and those interested in deep-learning and missing data methods. \nAbout speaker: Bryor Snefjella is a postdoctoral researcher in the Psychology Department\, Cognitive Area\, mentored by Idan Blank\, Keith Holyoak\, and Hongjing Lu. Before moving to UCLA\, Bryor received a PhD in Cognitive Science of Language in McMaster University in Canada. His research on language use patterns in social media has received international media attention. Check him out on his personal website\, Twitter\, Linkedin\, and Research Gate.
URL:https://idre.ucla.edu/calendar-event/bryor-snefjella-feb25-22
CATEGORIES:Conferences and Seminars,Meetings
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220225T100000
DTEND;TZID=America/Los_Angeles:20220225T120000
DTSTAMP:20260406T070525
CREATED:20211214T204231Z
LAST-MODIFIED:20220901T205128Z
UID:22541-1645783200-1645790400@idre.ucla.edu
SUMMARY:Learning Generative Adversarial Networks
DESCRIPTION:Workshop will be conducted in Zoom in PST time. Please Register here in advance for this lecture. \n\nThis workshope will the introduction to Generative Adversarial Networks (GANs). We will illustrate the fundamental GAN techniques on how to use DCGANs to generate do images using PyTorch. The knowledge of topics covered in the previous sessions is assumed. Working experience of Python\, Jupyter Notebooks and linear algebra will be helpful. \nTo register: https://ucla.zoom.us/meeting/register/tJcqc-6orjgtGdJQju538rp_SyhqQsUPdduI \nAfter registering\, you will receive a confirmation email containing information about joining the meeting. \nIf you have any further questions regarding the workshop\, please contact instructor Qiyang Hu.
URL:https://idre.ucla.edu/calendar-event/learning-generative-adversarial-networks
LOCATION:Zoom
CATEGORIES:Classes and Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220223T100000
DTEND;TZID=America/Los_Angeles:20220223T120000
DTSTAMP:20260406T070525
CREATED:20220222T212201Z
LAST-MODIFIED:20220901T205017Z
UID:22745-1645610400-1645617600@idre.ucla.edu
SUMMARY:Running Applications on the Hoffman2 Cluster\, Part III
DESCRIPTION:The Hoffman2 Cluster is a powerful computational resource for the UCLA research community. This workshop is part of a three-seminar series designed to introduce users to the Hoffman2 Cluster environment and to clarify the process of porting applications or using applications already available on the cluster. It also addresses how to port your workflow to Hoffman2 and how to submit batch and run interactive applications. While the three seminars are designed as a series\, each of the seminars stands on its own and does not require attendance to the preceding one. \nPart III addresses how to submit specific workflow classes such as array jobs and to monitor resource utilization. It looks into how to request GPU and run a variety of applications on them including machine learning. A questionnaire will be distributed beforehand to tailor the class as much as possible to the needs of the attendees. \nRegister here: https://ucla.zoom.us/meeting/register/tJEvdu6upjMpHdDV4Byhjcz8FaCR7B8A6OH3.
URL:https://idre.ucla.edu/calendar-event/running-applications-on-the-hoffman2-cluster-part-iii
LOCATION:Zoom
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220222T130000
DTEND;TZID=America/Los_Angeles:20220222T160000
DTSTAMP:20260406T070525
CREATED:20211214T204119Z
LAST-MODIFIED:20220901T204850Z
UID:22539-1645534800-1645545600@idre.ucla.edu
SUMMARY:Stata Data Management
DESCRIPTION:Registration: https://ucla.zoom.us/meeting/register/tJIpf–rrj4vE9DWH23IkyLvjjrk-md-hwYe \nThis workshop covers Stata commands and methods for common data management tasks\, such as identifying data errors\, identifying duplicated data\, specifying missing values\, working with string variables\, labeling variables\, creating new variables\, merging datasets\, processing data by groups\, and using loops for repetitive tasks.  The workshop is focused on preparing data for statistical analysis.
URL:https://idre.ucla.edu/calendar-event/stata-data-management-2
LOCATION:Zoom
CATEGORIES:Classes and Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220218T100000
DTEND;TZID=America/Los_Angeles:20220218T120000
DTSTAMP:20260406T070525
CREATED:20211214T204022Z
LAST-MODIFIED:20220901T204819Z
UID:22537-1645178400-1645185600@idre.ucla.edu
SUMMARY:Learning Convolutional Neural Networks (2)
DESCRIPTION:Workshop will be conducted in Zoom in PST time. Please Register here in advance for this lecture. \n\nThis workshope will be the second lecture on the introduction to convolutional neural network. We will continue our learning on how to apply data augmentation and transfer learning techniques to get a better solution for the classic Dogs-vs-Cats problem using PyTorch. The knowledge of topics covered in the previous sessions is assumed. Working experience of Python\, Jupyter Notebooks and linear algebra will be helpful. \nTo register: https://ucla.zoom.us/meeting/register/tJ0od-usrz8rHNNJR69SESkwcsqctmkZUzVj \nAfter registering\, you will receive a confirmation email containing information about joining the meeting. \nIf you have any further questions regarding the workshop\, please contact instructor Qiyang Hu.
URL:https://idre.ucla.edu/calendar-event/learning-convolutional-neural-networks-2
LOCATION:Zoom
CATEGORIES:Classes and Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220216T100000
DTEND;TZID=America/Los_Angeles:20220216T120000
DTSTAMP:20260406T070525
CREATED:20220106T173957Z
LAST-MODIFIED:20220901T204715Z
UID:22570-1645005600-1645012800@idre.ucla.edu
SUMMARY:Running Applications on the Hoffman2 Cluster\, Part II
DESCRIPTION:Registration link: https://ucla.zoom.us/meeting/register/tJIvd-igpjMiGNVkod90GFNhBTuT7pwRfj5- \n\n\n\n\nThe Hoffman2 Cluster is a powerful computational resource for the UCLA research community. This workshop is part of a three-seminar series designed to introduce users to the Hoffman2 Cluster environment and to clarify the process of porting applications or using applications already available on the cluster. It also addresses how to port your workflow to Hoffman2 and how to submit batch and run interactive applications.\nPart II addresses specific workflow classes such as: serial\, multi core\, parallel and array job submissions. It addresses the process of creating MATLAB standalone executables and running MATLAB in batch. Example of how to submit array jobs using MATLAB\, Abaqus\, R and other applications are discussed\, with hands on demonstration of various types of job submissions. While the three seminars are designed as a series\, each of the seminars stands on its own and does not require attendance to the preceding one.\n\n\n\n\nAfter registering\, you will receive a confirmation email containing information about joining the seminar.
URL:https://idre.ucla.edu/calendar-event/running-applications-on-the-hoffman2-cluster-part-ii-3
LOCATION:Zoom
CATEGORIES:Classes and Workshops,Education and Training,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220215T130000
DTEND;TZID=America/Los_Angeles:20220215T160000
DTSTAMP:20260406T070525
CREATED:20211214T203907Z
LAST-MODIFIED:20220901T204650Z
UID:22535-1644930000-1644940800@idre.ucla.edu
SUMMARY:R Markdown Basics
DESCRIPTION:Registration: https://ucla.zoom.us/meeting/register/tJwpd-uoqDIvG91UKYByaA-7Xcbn4V38rA1k \nR 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 workshop covers basic coding and conventions of the three frameworks upon which R Markdown depends:  Markdown for formatting text\, knitr for R code chunks\, and YAML for rendering the document.  The workshop 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.
URL:https://idre.ucla.edu/calendar-event/r-markdown-basics-3
LOCATION:Zoom
CATEGORIES:Classes and Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220211T140000
DTEND;TZID=America/Los_Angeles:20220211T170000
DTSTAMP:20260406T070525
CREATED:20211214T203759Z
LAST-MODIFIED:20220106T172339Z
UID:22533-1644588000-1644598800@idre.ucla.edu
SUMMARY:Practical Parallel Computing 3: Introduction to PETSc
DESCRIPTION:MPI (Message Passing Interface) is a standardized interface for portable distributed-memory scientific parallel computing. The portability ensures that a properly-written\, standard-conforming MPI program can work the same way on different platforms ranging from laptop computers to massively parallel supercomputers. MPI has been widely used in advanced simulations\, data analysis and visualization in the last two decades. A typical MPI program would launch as a set of processes distributed across multiple CPU cores or compute nodes. Each process would perform a part of the computations; the processes communicate with each other as needed (by making MPI function calls). The communication is transparently controlled by the user code\, and the processes are managed by the MPI runtime system\, which can also be controlled by the user. This series of workshop aims to introduceing MPI for scientific computing from a user’s perspective: \n– Part 1 (January 21\, 2022)\, running MPI programs\, explores various aspects of the MPI runtime/process management system\, and how it interacts with the job scheduler of a HPC cluster. We will cover both Intel MPI/MPICH and OpenMPI libraries\, and use Hoffman2 cluster as a target machine. Given a MPI program (either your own code\, or a community/research code)\, what are the things that you can adjust/control in order to run the code “optimally” on the target machine? \n– Part 2 (January 28\, 2022)\, MPI programming\, focuses on how to write (basic) MPI programs. We will discuss the basic send/receive MPI communication mechanisms and explore their connections to select problems in scientific computing. We will show examples of calling MPI from different languages\, including Fortran\, C/C++\, Python and Julia. \n– Part 3 (February 11\, 2022)\, Introduction to PETSc\, will discuss the PETSc library\, which is built on top of MPI\, among other things\, as a way to simplify MPI programming for scientific computing. We will explore the built-in data structures and solvers in PETSc and show how to build MPI/PETSc programs that are easier to maintain and develop than “plain” MPI programs. \nThis is Part 3 of a 3-part series. \nRegistration: https://ucla.zoom.us/meeting/register/tJwpdu2ppzgqG9CSWGjWV26ognThi_MjFn3S
URL:https://idre.ucla.edu/calendar-event/practical-parallel-computing-3-introduction-to-petsc
LOCATION:Zoom
CATEGORIES:Classes and Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220211T100000
DTEND;TZID=America/Los_Angeles:20220211T123000
DTSTAMP:20260406T070525
CREATED:20211214T203652Z
LAST-MODIFIED:20220901T203610Z
UID:22531-1644573600-1644582600@idre.ucla.edu
SUMMARY:Learning Convolutional Neural Networks (1)
DESCRIPTION:Workshop will be conducted in Zoom in PST time. Please Register here in advance for this lecture. \n\nThis workshope will be an introduction on convolutional neural network. We will start our learning on how to use PyTorch to do image processing for classic Dogs-vs-Cats problem. The knowledge of topics covered in the previous sessions is assumed. Working experience of Python\, Jupyter Notebooks and linear algebra will be helpful. \nTo register: https://ucla.zoom.us/meeting/register/tJMpde6pqTgsHNYBPoJmhNelXw3PeHH4AWzT \nAfter registering\, you will receive a confirmation email containing information about joining the meeting. \nIf you have any further questions regarding the workshop\, please contact instructor Qiyang Hu.
URL:https://idre.ucla.edu/calendar-event/learning-convolutional-neural-networks-1
LOCATION:Zoom
CATEGORIES:Classes and Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220209T100000
DTEND;TZID=America/Los_Angeles:20220209T120000
DTSTAMP:20260406T070525
CREATED:20220106T173820Z
LAST-MODIFIED:20220901T203519Z
UID:22568-1644400800-1644408000@idre.ucla.edu
SUMMARY:Running Applications on the Hoffman2 Cluster\, Part I
DESCRIPTION:Registration link: https://ucla.zoom.us/meeting/register/tJYqc-6rqz0qGdCvJuus9bUKV2xVtQHZQnHu \n\nThe Hoffman2 Cluster is a powerful computational resource for the UCLA research community. This workshop is part of a three-seminar series designed to introduce users to the Hoffman2 Cluster environment and to clarify the process of porting applications or using applications already available on the cluster. It also addresses how to port your workflow to Hoffman2 and how to submit batch jobs and run interactive applications.\nThis introductory workshop addresses the specifics of the Hoffman2 Cluster set-up\, it provides a survival guide on how to use the existing documentation\, how to navigate the unix command prompt and how to submit a variety of tasks for interactive or batch execution. It provides in class demonstrations on how to connect to the cluster via the traditional unix shell and how to run jupyter notebooks on the Hoffman2 Cluster. It introduces users to loading applications via environmental modules and how to find/install/run needed applications. \n\nAfter registering\, you will receive a confirmation email containing information about joining the seminar. \n 
URL:https://idre.ucla.edu/calendar-event/running-applications-on-the-hoffman2-cluster-part-i-3
LOCATION:Zoom
CATEGORIES:Classes and Workshops,Education and Training,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220209T090000
DTEND;TZID=America/Los_Angeles:20220209T110000
DTSTAMP:20260406T070525
CREATED:20211211T002932Z
LAST-MODIFIED:20220901T203431Z
UID:22483-1644397200-1644404400@idre.ucla.edu
SUMMARY:Introduction to Remote Sensing with Python
DESCRIPTION:Landsat imagery of the 2020 Bobcat wildfire generated using Python \nRegister here \nSatellites are circling our planet\, allowing us to “sense” things about the Earth. It is the art and science of making measurements using sensors. Remote sensing has thus become a valuable tool in research and applications in a wide range of disciplines\, such as engineering\, geology\, geography\, urban planning\, public health\, archeology\, environmental studies\, disaster research\, forestry\, and agriculture. \nIn this workshop\, you will: \n\nlearn the basic principles of remote sensing methods in research\nhave a hands-on session on using Jupyter Notebooks to code in Python\nimport Landsat imagery using Google Earth Engine’s Python library\nconduct a basic NDVI (Normalized Difference Vegetation Index) analysis\n\nWhile there are no prerequisites to take this workshop\, participants are encouraged to come with a Google Earth Engine account\, which can be obtained here: \nhttps://earthengine.google.com/
URL:https://idre.ucla.edu/calendar-event/introduction-to-remote-sensing-with-python
LOCATION:Zoom
CATEGORIES:Classes and Workshops
ATTACH;FMTTYPE=image/png:https://idre.ucla.edu/wp-content/uploads/2021/12/remote2.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220203T100000
DTEND;TZID=America/Los_Angeles:20220203T120000
DTSTAMP:20260406T070525
CREATED:20211214T203509Z
LAST-MODIFIED:20220901T203326Z
UID:22529-1643882400-1643889600@idre.ucla.edu
SUMMARY:Converting plots from Matlab to Python/matplotlib
DESCRIPTION:This workshop will introduce how to use Python/matplotlib and other packages to generate data visualization and animation for publications or presentations. We will discuss plotting functions and techniques available in both Matlab and Python to handle and customize your graphics in practice. The materials include simple 2D/3D plots to present scalers and vectors\, filled plots to handle continuously spatial data\, geographic plots to deal with geographic information\, and animation to show variation in temporal data. We will also include the methods to save figures in specific file formats and resolutions. \nRegistration: https://ucla.zoom.us/meeting/register/tJUuce2grj4pHdf-QP7rwgcxHpwaF_A06_jh
URL:https://idre.ucla.edu/calendar-event/converting-plots-from-matlab-to-python-matplotlib
LOCATION:Zoom
CATEGORIES:Classes and Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220128T140000
DTEND;TZID=America/Los_Angeles:20220128T153000
DTSTAMP:20260406T070525
CREATED:20211214T203335Z
LAST-MODIFIED:20220106T172025Z
UID:22527-1643378400-1643383800@idre.ucla.edu
SUMMARY:Practical Parallel Computing 2: MPI Programming
DESCRIPTION:MPI (Message Passing Interface) is a standardized interface for portable distributed-memory scientific parallel computing. The portability ensures that a properly-written\, standard-conforming MPI program can work the same way on different platforms ranging from laptop computers to massively parallel supercomputers. MPI has been widely used in advanced simulations\, data analysis and visualization in the last two decades. A typical MPI program would launch as a set of processes distributed across multiple CPU cores or compute nodes. Each process would perform a part of the computations; the processes communicate with each other as needed (by making MPI function calls). The communication is transparently controlled by the user code\, and the processes are managed by the MPI runtime system\, which can also be controlled by the user. This series of workshop aims to introduceing MPI for scientific computing from a user’s perspective: \n– Part 1 (January 21\, 2022)\, running MPI programs\, explores various aspects of the MPI runtime/process management system\, and how it interacts with the job scheduler of a HPC cluster. We will cover both Intel MPI/MPICH and OpenMPI libraries\, and use Hoffman2 cluster as a target machine. Given a MPI program (either your own code\, or a community/research code)\, what are the things that you can adjust/control in order to run the code “optimally” on the target machine? \n– Part 2 (January 28\, 2022)\, MPI programming\, focuses on how to write (basic) MPI programs. We will discuss the basic send/receive MPI communication mechanisms and explore their connections to select problems in scientific computing. We will show examples of calling MPI from different languages\, including Fortran\, C/C++\, Python and Julia. \n– Part 3 (February 11\, 2022)\, Introduction to PETSc\, will discuss the PETSc library\, which is built on top of MPI\, among other things\, as a way to simplify MPI programming for scientific computing. We will explore the built-in data structures and solvers in PETSc and show how to build MPI/PETSc programs that are easier to maintain and develop than “plain” MPI programs. \nThis is Part 2 of a 3-part series. \nRegistration: https://ucla.zoom.us/meeting/register/tJYvc-mhrzMjHNAY0Vm2QbKcCrt7CXMvhsuP
URL:https://idre.ucla.edu/calendar-event/practical-parallel-computing-2-mpi-programming
LOCATION:Zoom
CATEGORIES:Classes and Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220128T113000
DTEND;TZID=America/Los_Angeles:20220128T123000
DTSTAMP:20260406T070525
CREATED:20220125T202545Z
LAST-MODIFIED:20220208T020508Z
UID:22623-1643369400-1643373000@idre.ucla.edu
SUMMARY:Phenological responses of North American birds to global change: Ecology in the age of big data
DESCRIPTION:Speaker: Casey Youngflesh\nIDRE Scholar\,\nDepartment of Ecology and Evolutionary Biology\,\nUniversity of California Los Angeles \n  \nTime: 11:30 AM – 12:30 PM (PST)\nDate: Jan 28\, 2022\nLocation: Zoom (RSVP here for the link) \n  \nAbstract: Rapid abiotic environmental change is driving a multitude of shifts in natural systems across the Earth. One of the most pronounced responses to these pressures is changes in the timing of seasonal events\, known as phenology. With warming temperatures\, phenological events in spring are generally getting earlier over time\, stimulating concerns that ecological interactions are becoming increasingly mismatched in time. However\, much remains unknown\, particularly with regard to how these changes vary over space and across species\, and what the ecological consequences of these changes are. Research efforts in this regard have been hampered by the limited spatial and taxonomic resolution of traditional data resources. Using a set of flexible hierarchical Bayesian statistical modeling approaches to integrate millions of data records from community-sourced data platforms\, continent-scale bird banding projects\, and satellite-based sensors\, we characterized how the phenology of dozens of forest dwelling birds across North America is responding to global change. We estimated how species’ sensitivity to these changes varies over space and among species as well as the demographic impacts of these changes. We find that the phenology of most species is not keeping pace with environmental change\, but that some species may be better equipped to accommodate these changes. Importantly\, results show that phenology has important implications for the breeding productivity of these species’\, with years where breeding occurs too early or too late relative to the arrival of spring is associated with lower breeding output. Results from this study\, facilitated by analytical pipelines that integrate a collection of both opportunistic and structured data resources\, stand as one of the largest-scale demonstrations of the importance of phenology for demographic processes\, with important implications for understanding the drivers of recent large-scale declines in North American birds over the last 50 years. \nAbout the speaker: Casey Youngflesh is a quantitative ecologist and postdoc with Morgan Tingley in the Department of Ecology and Evolutionary Biology at UCLA. His research seeks to understand how ecological systems function\, how they are responding to rapid global change\, and what this might tell us about how best to conserve these systems. He has a particular interest in applying quantitative tools to large-scale data derived from a variety of sources\, including citizen science projects\, satellite-based sensors\, remote camera networks\, and field-based efforts. His research efforts have taken him across the world\, from Antarctica to the Galápagos Islands\, though these days he can mostly be found at his computer trying to make sense of his data.
URL:https://idre.ucla.edu/calendar-event/casey-youngflesh
LOCATION:Zoom
CATEGORIES:Classes and Workshops,Meetings,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220127T110000
DTEND;TZID=America/Los_Angeles:20220127T120000
DTSTAMP:20260406T070525
CREATED:20211214T203127Z
LAST-MODIFIED:20220106T171933Z
UID:22524-1643281200-1643284800@idre.ucla.edu
SUMMARY:Tips to run Matlab on Hoffman2 cluster
DESCRIPTION:In this workshop we will focus on the methods to execute Matlab interactively and run its programs via job scheduler on Hoffman2 cluster. (We will not describe how to write Matlab scripts nor how to use its internal/external functions.) Several methods to launch Hoffman2 Matlab GUI from different operating systems will be discussed\, including the usage of Jupyter notebook from a local web browser. We will also discuss the how to write simple job submission scripts to run Matlab codes. \nRegistration: https://ucla.zoom.us/meeting/register/tJcvduCorDsjHdQJvAlODUl2ivHNYlee5alP
URL:https://idre.ucla.edu/calendar-event/tips-to-run-matlab-on-hoffman2-cluster
LOCATION:Zoom
CATEGORIES:Classes and Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220127T090000
DTEND;TZID=America/Los_Angeles:20220127T110000
DTSTAMP:20260406T070525
CREATED:20220106T173320Z
LAST-MODIFIED:20220106T173320Z
UID:22566-1643274000-1643281200@idre.ucla.edu
SUMMARY:Make and Makefiles
DESCRIPTION:Description coming soon. \nRegister in advance:  Please REGISTER using the Zoom Meeting Link before joining! \nIf you have any questions regarding this event\, please contact Ben Winjum.
URL:https://idre.ucla.edu/calendar-event/make-and-makefiles-2
LOCATION:Zoom
CATEGORIES:Classes and Workshops,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220121T140000
DTEND;TZID=America/Los_Angeles:20220121T153000
DTSTAMP:20260406T070525
CREATED:20211214T202857Z
LAST-MODIFIED:20220106T171817Z
UID:22521-1642773600-1642779000@idre.ucla.edu
SUMMARY:Practical Parallel Computing 1: Running MPI Programs
DESCRIPTION:MPI (Message Passing Interface) is a standardized interface for portable distributed-memory scientific parallel computing. The portability ensures that a properly-written\, standard-conforming MPI program can work the same way on different platforms ranging from laptop computers to massively parallel supercomputers. MPI has been widely used in advanced simulations\, data analysis and visualization in the last two decades. A typical MPI program would launch as a set of processes distributed across multiple CPU cores or compute nodes. Each process would perform a part of the computations; the processes communicate with each other as needed (by making MPI function calls). The communication is transparently controlled by the user code\, and the processes are managed by the MPI runtime system\, which can also be controlled by the user. This series of workshop aims to introduceing MPI for scientific computing from a user’s perspective: \n– Part 1 (January 21\, 2022)\, running MPI programs\, explores various aspects of the MPI runtime/process management system\, and how it interacts with the job scheduler of a HPC cluster. We will cover both Intel MPI/MPICH and OpenMPI libraries\, and use Hoffman2 cluster as a target machine. Given a MPI program (either your own code\, or a community/research code)\, what are the things that you can adjust/control in order to run the code “optimally” on the target machine? \n– Part 2 (January 28\, 2022)\, MPI programming\, focuses on how to write (basic) MPI programs. We will discuss the basic send/receive MPI communication mechanisms and explore their connections to select problems in scientific computing. We will show examples of calling MPI from different languages\, including Fortran\, C/C++\, Python and Julia. \n– Part 3 (February 11\, 2022)\, Introduction to PETSc\, will discuss the PETSc library\, which is built on top of MPI\, among other things\, as a way to simplify MPI programming for scientific computing. We will explore the built-in data structures and solvers in PETSc and show how to build MPI/PETSc programs that are easier to maintain and develop than “plain” MPI programs. \nThis is Part 1 of a 3-part series. \nRegistration: https://ucla.zoom.us/meeting/register/tJArdOivrTwvG9fq8niOtdDXf3xQqXvT3sVi
URL:https://idre.ucla.edu/calendar-event/practical-parallel-computing-1-running-mpi-programs
LOCATION:Zoom
CATEGORIES:Classes and Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220120T090000
DTEND;TZID=America/Los_Angeles:20220120T110000
DTSTAMP:20260406T070525
CREATED:20220106T173154Z
LAST-MODIFIED:20220106T173154Z
UID:22564-1642669200-1642676400@idre.ucla.edu
SUMMARY:Version Control with Git
DESCRIPTION:Git is a software tool that helps users manage changes to their software over time. Git will allow you to maintain a complete change history of every file\, create branches for concurrent streams of changes\, trace changes with annotations\, and collaborate and share work with others. This interactive introduction will demonstrate how to use Git to track changes\, to explore history\, and to use web-based Git repositories to share work with others and collaborate. \nRegister in advance:  Please REGISTER using the Zoom Meeting Link before joining! \nIf you have questions regarding the workshop\, please contact Ben Winjum.
URL:https://idre.ucla.edu/calendar-event/version-control-with-git-4
LOCATION:Zoom
CATEGORIES:Classes and Workshops,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220107T100000
DTEND;TZID=America/Los_Angeles:20220107T150000
DTSTAMP:20260406T070525
CREATED:20211211T002301Z
LAST-MODIFIED:20220208T020643Z
UID:22481-1641549600-1641567600@idre.ucla.edu
SUMMARY:Machine learning for Oceanic & Atmospheric Sciences
DESCRIPTION:IDRE ECR Group is excited to announce Machine learning for oceanic & atmospheric sciences workshop with the following details: \nTitle: Machine Learning for Oceanic & Atmospheric Sciences \nDate and Time: Friday\, January 7\, 2022 @10 AM (PST) \nRegistration: https://ucla.zoom.us/meeting/register/tJclde2opjsiGdU0sq31tMP5YUXd8FbvCbCm \nAbstract: Machine learning (ML) denotes a host of computational methods for inferring meaningful patterns in data. Advances over recent decades in ML methodologies\, computational power\, and dataset sizes have facilitated the rapid adaptation of these methods in practically every field of science and technology. ML allows learning directly from data to utilize hidden patterns in data where scientific theory is not fully developed or is too computationally intensive. ML has proved to be a highly useful tool in climate science\, where traditional pattern recognition is confounded by high system complexity\, multiscale interactions\, chaos\, and prohibitive datasets sizes. \nThe UCLA Machine Learning for Climate Workshop will host presentations from climate and ML scientists covering ML subjects of broad interest outside of climate as well as aspects that are especially of interest in climate science. Broad interest subjects will include discussions on choosing the right ML tools for the right task and tricks of the trade for common ML methodologies. Climate-related ML topics will consist of ML learning of spatio-temporal climate patterns\, ML constrained by physical principles\, and physical interpretability of learned patterns\, as well as short research presentations. \nAgenda: Friday\, January 7\, 2021\n \n\n\n\nTime (Pacific)\nPresentation title and speaker\n\n\n10:00-10:05\nWelcome and Introduction\n\n\n10:05-10:40\nInferring physics through self-supervised learning of climate data. Kaushik Srinivasan\, UCLA\n\n\n10:40-11:15\nExplainable AI for Climate Science: Applications and Techniques. Kirsten Mayer\, Colorado State University.\n\n\n11:15-11:30\n15-minute break\n\n\n11:30-12:05\nTips for Successful Training of Deep Neural Networks. Bryor Snefjella\, UCLA.\n\n\n12:05-12:40\nMachine learning for space weather prediction. Jacob Bortnik\, UCLA. \n\n\n12:40-13:40\nLunch break\n\n\n13:40-14:10\nLearning Stochastic Closures Using Ensemble Kalman Inversion. Jinlong Wu\, Caltech.\n\n\n14:10-14:45\nGenerative Modeling for Climate Science. Aditya Grover\, UCLA.\n\n\n14:45-15:00\nQ&A with speakers\n\n\n\n 
URL:https://idre.ucla.edu/calendar-event/machine-learning-for-aos
CATEGORIES:Classes and Workshops,Conferences and Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20211119T113000
DTEND;TZID=America/Los_Angeles:20211119T123000
DTSTAMP:20260406T070525
CREATED:20220208T230110Z
LAST-MODIFIED:20220210T194322Z
UID:22719-1637321400-1637325000@idre.ucla.edu
SUMMARY:Building a patient motion model for Radiotherapy
DESCRIPTION:  \n  \nSpeaker: Ricky Savjani\, Ph.D.\nIDRE Scholar\,\nDepartment of Radiation Oncology\,\nUniversity of California Los Angeles \n  \n  \nAbstract: Several technological advances in radiotherapy have enabled the use of focused radiation to treat solid tumors within the thoracic cavity. Stereotactic Body Radiation Therapy (SBRT) offers a way to treat patients with high doses of radiation with just a few (three to five) treatments entirely non-invasively\, providing excellent tumor control for both early stage non-small cell lung cancer and metastatic disease. However\, respiratory motion causes the tumor and surrounding organs at risk to move. This movement is particularly concerning for thoracic SBRT\, as radiation pneumonitis stems largely from an inability to visualize the tumor and lungs during treatment and thus requires larger margins. Respiratory motion has been characterized as irregular (can differ from breath to breath and minute to minute) and can induce motion of 5 cm or more\, particularly at the diaphragm. Overall\, there is a pressing need to measure and monitor thoracic motion while cancer patients are being treated with radiotherapy. \nOur group at UCLA has previously created a 5DCT model to better represent a patient’s tumor motion. Patients are allowed to breathe freely while they undergo 25 fast\, low-dose helical CT scans during simulation prior to radiation therapy. An over-determined linear model is fit to find the position of any voxel based on the initial position and the current tidal volume and airflow. The corresponding imaged motion of the tumor and thoracic cavity can more accurately be measured with 5DCT compared to traditional 4DCT models. \nWe now have a large cohort of data (n = 91 patients) to begin fitting an inter-patient motion model. Working with Varian\, A Siemens Healthineers Company\, we have applied auto segmentation models to each of the 25 scans for each patient. We have trained a Conditional Variational Autoencoder (cVAE) model to generate deformations between any two pairs CT volumes. The embedded space can be visualized in 3D\, and we are now working on ways to drive the amount of inhalation/exhalation using an external surrogate (a belt the patient wears while being treated). In this way\, we envision generating 3D volumetric representations at the treatment console while patients are being treated with radiotherapy in real-time. \nAbout the speaker: Ricky Savjani is a resident physician in the Department of Radiation Oncology at UCLA. As part of his training\, he is conducting research through the American Board of Radiology Holman Research Pathway\, in addition to seeing patients clinically to become a radiation oncologist. Prior to joining UCLA\, Ricky received BS degrees in Electrical Engineering/Computer Science and Brain and Cognitive Sciences at MIT. He then pursued an MD/Ph.D. at Texas A&M College of Medicine\, where his research focused on structural and functional imaging of the human brain. Ricky loves medical imaging and hopes to continue to use advanced imaging approaches to deliver safer and better radiation to patients. \nLocation: Zoom (RSVP here for the link)
URL:https://idre.ucla.edu/calendar-event/ricky-savjani-idre-scholar
LOCATION:Zoom
CATEGORIES:Conferences and Seminars,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20211029T113000
DTEND;TZID=America/Los_Angeles:20211029T123000
DTSTAMP:20260406T070525
CREATED:20220208T215939Z
LAST-MODIFIED:20220210T195657Z
UID:22717-1635507000-1635510600@idre.ucla.edu
SUMMARY:Panel discussion on Interdisciplinary Research and Collaboration
DESCRIPTION:Video Link: https://youtu.be/RVdWM1SbB4s \nThe IDRE Early Career Researchers group is excited to restart its monthly meetings. This first meeting will introduce five IDRE scholars selected from a large pool of applicants\, followed by a panel discussion on interdisciplinary research and collaboration. The following eminent UCLA researchers will be the panelists: \n\nKaren McKinnon\, Institute of the Environment and Sustainability\, Department of Statistics\nJacob Foster\, Department of Sociology\nMiriam Marlier\, Environmental Health Sciences\nJim McWilliams\, Department of Atmospheric and Oceanic Sciences\n\nThe panel will explore the benefits and roles of interdisciplinary research and collaborations in academia. The panelists will discuss the barriers that may discourage researchers from pursuing multidisciplinary research opportunities and dive into whether the current academic training sufficiently prepares us for multidisciplinary collaboration and how to rise to the challenges of such partnerships. Each panelist has vast experience working on collaborative projects and creating multidisciplinary teams. The audience will also have a chance to ask questions. \nPlease plan to join the event and benefit from their insights.* \n*The event was virtual\, and you can view using the link: https://youtu.be/RVdWM1SbB4s
URL:https://idre.ucla.edu/calendar-event/ecr-panel-oct29-2021
LOCATION:Zoom
CATEGORIES:Conferences and Seminars,Meetings
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20210830T130000
DTEND;TZID=America/Los_Angeles:20210830T160000
DTSTAMP:20260406T070525
CREATED:20210604T225106Z
LAST-MODIFIED:20210610T235515Z
UID:21986-1630328400-1630339200@idre.ucla.edu
SUMMARY:Generalized Linear Models in R
DESCRIPTION:This workshop is designed to give an overview on generalized linear models. The workshop introduces the basic theory of generalized linear models and their implementation in R. We will talk about a broad range of regression models such as Logistic regression\, Poisson regression\, negative binomial\, zero-inflated Poisson\, and zero-inflated negative binomial and how to run them in R and how to interpret the results. Of course\, we will not be able to discuss all aspects of generalize regression models such as model diagnostics\, etc. Participants expected to have familiarity with ordinary least squares and basic R. Registration is open and to register please use the link below: \nREGISTER to obtain Zoom link \nhttps://ucla.zoom.us/meeting/register/tJIvc-CsrzkpHdE5ge2aBJtBKqO8CPOctQ5u \nAfter registering\, you will receive a confirmation email containing information about joining the meeting.
URL:https://idre.ucla.edu/calendar-event/generalized-linear-models-in-r
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20210823T130000
DTEND;TZID=America/Los_Angeles:20210823T160000
DTSTAMP:20260406T070525
CREATED:20210604T224954Z
LAST-MODIFIED:20210611T003540Z
UID:21984-1629723600-1629734400@idre.ucla.edu
SUMMARY:Statistical Writing
DESCRIPTION:Workshop description and Zoom registration link coming soon!
URL:https://idre.ucla.edu/calendar-event/statistical-writing
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20210816T130000
DTEND;TZID=America/Los_Angeles:20210816T160000
DTSTAMP:20260406T070525
CREATED:20210603T220911Z
LAST-MODIFIED:20210603T221813Z
UID:21973-1629118800-1629129600@idre.ucla.edu
SUMMARY:Intermediate Topics in Confirmatory Factor Analysis (CFA)
DESCRIPTION:This seminar is a continuation of the first seminar on Confirmatory Factor Analysis (CFA) in R with lavaan. Topics include \n\nmultiple group CFA\nmeasurement invariance\nlatent growth modeling\n\nSome time will be given at the end for interactive coding exercises. \nInstructor: Johnny Lin\, Ph.D.\, OARC/IDRE Statistical Consulting \nTime: Aug 16\, 2021 01:00 PM Pacific Time (US and Canada) \nPre-requisites: Attendance or self-learning of first seminar Confirmatory Factor Analysis (CFA) in R with lavaan \nREGISTER to obtain Zoom link \nhttps://ucla.zoom.us/meeting/register/tJEqfumgqDsjEt1S9ROTo3zdJ9qWjNXvT5Ez \nAfter registering\, you will receive a confirmation email containing information about joining the meeting.
URL:https://idre.ucla.edu/calendar-event/21973
LOCATION:Zoom
ORGANIZER;CN="UCLA IDRE Statistical Consulting":MAILTO:idrestat@ucla.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20210809T140000
DTEND;TZID=America/Los_Angeles:20210809T160000
DTSTAMP:20260406T070525
CREATED:20210603T160045Z
LAST-MODIFIED:20210603T162032Z
UID:21938-1628517600-1628524800@idre.ucla.edu
SUMMARY:Workflow automation with continuous integration and deployment (CI/CD)
DESCRIPTION:Registration required: https://ucla.zoom.us/meeting/register/tJwpfuyoqjovH9WK3qDETR_zFH7gdMqNaube
URL:https://idre.ucla.edu/calendar-event/workflow-automation-with-continuous-integration-and-deployment-ci-cd
LOCATION:Zoom
CATEGORIES:Classes and Workshops
END:VEVENT
END:VCALENDAR