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DTSTART;TZID=America/Los_Angeles:20170501T090000
DTEND;TZID=America/Los_Angeles:20170501T120000
DTSTAMP:20260619T223547
CREATED:20170321T173853Z
LAST-MODIFIED:20170321T174404Z
UID:7976-1493629200-1493640000@idre.ucla.edu
SUMMARY:Analyzing and Visualizing Interactions in SAS
DESCRIPTION:This workshop introduces methods of analyzing interactions (moderated effects) in regression models:  calculating\, comparing and graphing simple effects and slopes.  Specifically\, we emphasize the use of proc plm and the lsmeans and estimates statements in SAS in conjunction with a solid understanding of the regression equation.  Examples include two- and three-way interactions in linear regression and two-way interactions in logistic regression.  Although the concepts of moderation and interaction are reviewed in the seminar\, some background in regression and moderation is recommended.
URL:https://idre.ucla.edu/calendar-event/analyzing-visualizing-interactions-sas
LOCATION:CA
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20170424T090000
DTEND;TZID=America/Los_Angeles:20170424T120000
DTSTAMP:20260619T223547
CREATED:20170321T173637Z
LAST-MODIFIED:20170321T175314Z
UID:7972-1493024400-1493035200@idre.ucla.edu
SUMMARY:Introduction to Mplus
DESCRIPTION:Mplus is a powerful statistical package used for the analysis of both observed and latent variables. Among the kinds of analysis it can perform are exploratory factor analysis\, confirmatory factor analysis\, latent class analysis\, latent growth curve modeling\, structural equation modeling and multilevel modeling. This workshop is designed for people who are just getting started using Mplus. Our aim is to orient participants to the basic structure\, syntax\, data and output associated with this package. Mplus version 7.4 will be used for this workshop. \n 
URL:https://idre.ucla.edu/calendar-event/introduction-to-mplus
LOCATION:CA
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20170412T114500
DTEND;TZID=America/Los_Angeles:20170412T130000
DTSTAMP:20260619T223547
CREATED:20170313T195634Z
LAST-MODIFIED:20170313T195634Z
UID:7870-1491997500-1492002000@idre.ucla.edu
SUMMARY:Accelerating Next-Generation DNA Sequencing
DESCRIPTION:  \nSpeaker: Dr. Zhenman Fang\, Ph.D.\,\nIDRE Scholar\,\nComputer Science Department\,\nUniversity of California\, Los Angeles \nTime: 11:45 A.M. – 1 P.M. (Lunch will be serverd*)\nDate: Apr 12\, 2017\nLocation: 5628\, Math Sciences Building\nRSVP: https://idre.ucla.edu/calendar-event/accel-next-gen-dna-seqn#rsvp \n  \nAbstract: Modern medical research is being transformed with the advance of next-generation sequencing technologies that dramatically reduce the cost of sequencing an individual human genome from $10M to $1\,000 in the past decade. This sequencing technology is widely utilized in research and is transitioning into the clinic for applications such as sequencing cancer tumors. To be more cost-effective\, genome sequencers obtain the sequence of billions of small fragments in the range of a few hundred nucleotides (called short reads) of a whole genome. Therefore\, we have to reconstruct all these short reads back into a whole human genome for genome variant calling and cancer discovery. This poses great computational challenges: state-of-the-art DNA sequencing pipeline takes around a week on a 12-core CPU server. \nIn this talk\, I will present various ways to accelerate the next-generation DNA sequencing pipeline done in our Center for Domain-Specific Computing (CDSC)\, with the final goal to reduce the computation time to a few hours. First\, we scale out the computation by leveraging the power of a CPU cluster/datacenter. Second\, we scale up the computation by developing hardware accelerators on commodity energy-efficient FPGAs that can be plugged into the CPU server. Moreover\, we combine these two techniques and address the new challenges in FPGA-enabled datacenters. I will talk about our current status in accelerating the DNA sequencing pipeline and show some promising results we have achieved using the aforementioned techniques [FCCM 2015\, HotCloud 2016\, ACM SOCC 2016]. \n\nAbout Speaker: Dr. Zhenman Fang is an IDRE scholar and a postdoc in the Computer Science Department\, UCLA\, working with Prof. Jason Cong and Prof. Glenn Reinman. He is a member of the NSF/Intel funded multi-university Center for Domain-Specific Computing (CDSC) and the SRC/DARPA funded multi-university Center for Future Architectures Research (C-FAR). Zhenman received his PhD in June 2014 from Fudan University\, China and spent the last 15 months of his PhD program visiting University of Minnesota at Twin Cities. Zhenman’s research lies at the boundary of big data workloads and systems\, heterogeneous and energy-efficient accelerator-rich architectures and systems\, and system-level design automation. He has published 10+ papers in top venues that span across computer architecture (HPCA\, TACO\, ICS)\, design automation (DAC\, ICCAD\, FCCM)\, and cloud computing (ACM SOCC). He received several awards\, including a best paper nominee of HPCA 2017\, a best demo award (3rd place) at the C-FAR center annual review. More details can be found in his personal website: https://sites.google.com/site/fangzhenman/. \n\n *Lunch will be served at 11:45 AM.\n**To ensure you have a space at the seminar\, please RSVP by April 6\, 2017.
URL:https://idre.ucla.edu/calendar-event/accel-next-gen-dna-seqn
LOCATION:CA
ORGANIZER;CN="T V Singh":MAILTO:tvsingh@ucla.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20170410T090000
DTEND;TZID=America/Los_Angeles:20170410T120000
DTSTAMP:20260619T223547
CREATED:20170321T172918Z
LAST-MODIFIED:20170329T224633Z
UID:7968-1491814800-1491825600@idre.ucla.edu
SUMMARY:Survey Data Analysis in SAS
DESCRIPTION:This workshop covers descriptive analyses\, both numerical and graphical\, with both continuous and categorical variables.  Subpopulation analysis will be discussed\, and then examples of OLS regression and logistic regression will be considered.
URL:https://idre.ucla.edu/calendar-event/survey-data-analysis-sas-2
LOCATION:CA
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20170404T090000
DTEND;TZID=America/Los_Angeles:20170404T163000
DTSTAMP:20260619T223547
CREATED:20170315T190127Z
LAST-MODIFIED:20170404T231412Z
UID:7878-1491296400-1491323400@idre.ucla.edu
SUMMARY:HPC and Big Data Analytics using Comet
DESCRIPTION:UCLA-IDRE and SDSC are organizing the workshop “HPC and Big Data Analytics using Comet” in order to introduce the Comet supercomputer and its usage to the researchers at UCLA. \nComet\, a petascale supercomputer at San Diego Supercomputing Center (SDSC)\, is one of the key resources within the NSF’s XSEDE (Extreme Science and Engineering Discovery Environment) program. It provides “free” computer time via XSEDE portal to the researchers across USA. The participants will be able to get hands-on experience on Comet during the workshop’s different sessions. \nThe RSVP link and the agenda for the workshop are as follows: \nRSVP: https://idre.ucla.edu/calendar-event/hpc-big-data-analytics-using-comet#rsvp \nAgenda:  \n(Link to slides: https://github.com/sdsc-scicomp/2017-04-04-comet-workshop-ucla) \n9:00 AM – 9:10 AM: Introduction & Welcome \n9:10 AM – 10:00 AM: Comet – SDSC’s 2 PetaFLOPS HPC Resource \n\nArchitecture\, queue/partition info\, software stack\nExamples for compute\, shared\, gpu\, and gpu-shared partitions\nHands-on on Comet to help prep for next sessions which will use Comet\n\n10:00 AM – 10:30 AM: Science Gateways \n10:30 AM – 10:40 AM: Short break \n10:40 AM- 12:00 PM:  Introduction to Hadoop on Comet \n\nOverview of running Hadoop within scheduler frameworks (using myHadoop)\nDemonstration/Hands on of Hadoop cluster spin up\, interactive usage\nNew technologies/approaches like RDMA-Hadoop and hands on with RDMA-Hadoop\n\n12 PM – 1 PM: Lunch (provided by IDRE)\n \n1:00 PM – 2:00 PM: Data Analytics and Data Mining  \n\nR and parallel execution of R\nData mining/machine learning\n\n2:00 PM- 3:00 PM: Python for Scientific Computing \n\nHow to run Jupyter notebook on Comet\nUse IPython Parallel for distributed computation\nEasy multithreading and distributed computing with dask\n\n3:00 PM-3:10 PM: Short break \n3:05 PM – 4:30 PM: Spark for Scientific Computing \n\nOverview of the capabilities of Spark and how they can be leveraged to solve problems in Scientific Computing\nHands-on introduction to Spark\, from batch and interactive usage on Comet to running a sample map/reduce example in Python\nTwo key libraries in the Spark ecosystem: Spark SQL\, a general purpose query engine that can interface to SQL databases or JSON files and Spark MLlib\, a scalable Machine Learning library\n\n4:30 PM: Wrap up
URL:https://idre.ucla.edu/calendar-event/hpc-big-data-analytics-using-comet
LOCATION:CA
CATEGORIES:Classes and Workshops,Education and Training,Presentations
ORGANIZER;CN="T V Singh":MAILTO:tvsingh@ucla.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20170308T114500
DTEND;TZID=America/Los_Angeles:20170308T130000
DTSTAMP:20260619T223547
CREATED:20170206T211937Z
LAST-MODIFIED:20170303T215336Z
UID:7649-1488973500-1488978000@idre.ucla.edu
SUMMARY:Polycrystalline crystal plasticity with grain boundary evolution
DESCRIPTION:  \n  \n  \n  \nSpeaker: Nikhil Chandra Admal\, Ph.D.\,\nIDRE Scholar\,\nDepartment of Materials Science and Engineering\,\nUniversity of California\, Los Angeles \n  \nTime:  11:45 a.m. to 1 p.m. (Lunch will be served*)\nDate: March 8\, 2017\nLocation:  5628\, Math Sciences Building \nRSVP:  https://idre.ucla.edu/calendar-event/polycrystalline-…undary-evolution#rsvp \n\n\n\nAbstract: Dynamic recrystallization can be defined as a spontaneous change in the mi- crostructure of a material during deformation at an elevated temperature due to the growth of defect-free grains through the motion of high angle grain boundaries. One of the most important uses of recrystallization is in metal processing\, where recrystallized grains increase the ductility\, resulting in better control of the grain structure. On the other hand\, it is undesirable from a design perspective\, since recrystallization alters the microstructure resulting in a change in the material’s macroscopic properties. In this talk\, I will describe our ongoing work on modeling grain growth during recrystallization in the presence of external loads. \nDynamic recrystallization is a uniquely challenging phenomenon to model since the microstructure and the material deformation evolve at the same time scale. Grain boundary motion in the absence of deformation is commonly modeled using phase field models\, while the deformation of a material with a fixed grain boundary structure is commonly modeled using crystal plasticity. In this work\, we develop a thermodynamically consistent model which models deformation and grain growth simultaneously\, thus enabling us to understand dynamic recrystalliza- tion. The highlight of this model is it is a non-classical gradient elastic model that can simulate various interesting phenomena observed in dynamic recrystallization\, where a grain rotates to increase/decrease its misorientation as its grain boundary evolves. \nAbout Speaker: Dr. Nikhil  Chandra Admal is postdoctoral research scholar working with Prof. Jaime Marian in the Materials Science and Engineering department at UCLA. He is broadly interested in the multiscale modeling of materials at various length and times scales ranging from the atomic scale to the continuum scale. Currently\, the focus of his research is on the study of recrystallization in refractory materials to increase their operating temperature\, and development of first-principles strain gradient elastic models to include non-local effects relevant in micromechanical systems\, and systems with defects. \nPrior to joining UCLA\, Dr. Admal obtained his PhD from the Department of Aerospace Engineering and Mechanics at the University of Minnesota. \n*Lunch will be served at 11:45 AM.\n**To ensure you have a space at the seminar\, please RSVP by March 05\, 2017.
URL:https://idre.ucla.edu/calendar-event/polycrystalline-crystal-plasticity-grain-boundary-evolution
LOCATION:CA
CATEGORIES:Conferences and Seminars,Meetings,Presentations
ORGANIZER;CN="T V Singh":MAILTO:tvsingh@ucla.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20170307T090000
DTEND;TZID=America/Los_Angeles:20170307T120000
DTSTAMP:20260619T223547
CREATED:20161102T230647Z
LAST-MODIFIED:20170214T231138Z
UID:6983-1488877200-1488888000@idre.ucla.edu
SUMMARY:Graphics in R: Introduction to ggplot2
DESCRIPTION:This workshop introduces how to use the R ggplot2 package to produce publication-quality graphics\, particularly for data analysis accompanying a planned regression model. First\, the underlying grammar (system) of graphics is introduced with demonstrations. Then the usage of ggplot2 for exploratory graphs\, model diagnostics\, and presentation of model results is illustrated through 3 examples.
URL:https://idre.ucla.edu/calendar-event/introduction-to-ggplot2
LOCATION:CA
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20170228T090000
DTEND;TZID=America/Los_Angeles:20170228T120000
DTSTAMP:20260619T223547
CREATED:20161102T230553Z
LAST-MODIFIED:20170214T235956Z
UID:6980-1488272400-1488283200@idre.ucla.edu
SUMMARY:Introduction to R
DESCRIPTION:R is a powerful statistical package that runs on many platforms\, including Windows\, Macintosh and Unix. This class is designed for people who are just getting started using R. The students in the class will have a hands-on experience using R for statistics\, graphics\, and data management. The R class notes do not contain any of the computer output. The class notes are not meant to be an R textbook or a reference manual. However\, it is possible for individuals to use the class notes to help in learning R even if they don’t enroll in the workshop.
URL:https://idre.ucla.edu/calendar-event/introduction-to-r-4
LOCATION:CA
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20170217T100000
DTEND;TZID=America/Los_Angeles:20170217T120000
DTSTAMP:20260619T223547
CREATED:20170123T183349Z
LAST-MODIFIED:20170202T031956Z
UID:7353-1487325600-1487332800@idre.ucla.edu
SUMMARY:Python for High Performance Computing II
DESCRIPTION:Python\, originally developed as a general purpose programming language\, has gained its popularity in the scientific community in recently years owning to its elegant and easy- to-understand syntax and powerful libraries. Python fully supports both functional and object-oriented programming styles. This class will present a number useful features of Python in the context of scientific computing\, and introduce a number of supporting packages\, including numpy for array-based computations and h5py to access HDF5 files\, and the use of Python in parallel computing (MPI style). \nThis is part 2 of a 2-part presentation.
URL:https://idre.ucla.edu/calendar-event/python-high-performance-computing-ii
LOCATION:CA
CATEGORIES:Classes and Workshops,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20170215T114500
DTEND;TZID=America/Los_Angeles:20170215T130000
DTSTAMP:20260619T223547
CREATED:20170118T200050Z
LAST-MODIFIED:20170211T053711Z
UID:7310-1487159100-1487163600@idre.ucla.edu
SUMMARY:Data as Infrastructure: CDS\, Astronomy and beyond
DESCRIPTION:  \n  \n  \nSpeaker: Dr. Françoise Genova\,\nAstronomer\, Centre de Données astronomiques de Strasbourg \nTime:  12 p.m. to 1 p.m. (Lunch will be served*)\nDate: Feb 15\, 2017\nLocation:  5628\, Math Sciences Building \nRegistration: https://idre.ucla.edu/calendar-event/data-as-infrastructure#rsvp ‎ \n  \nAbstract: Science data sharing is currently high in the political agenda\, but some disciplines began to share their data long ago. Astronomy has been at the forefront\, and now data is one of the discipline research infrastructures widely used by astronomers in their daily research work. The pioneering work of Strasbourg astronomical data centre CDS\, which was founded in 1972\, will be described\, as well as the astronomical data network and its global interoperability layer\, the Virtual Observatory. Many other disciplines are establishing structures to share their data\, which vary considerably by their culture and history. A few French examples (humanities\, earth sciences) will be described. Finally\, the way the Research Data Alliance (RDA) tackles the general question of enabling research data sharing will be briefly discussed. \nSpeaker: Françoise Genova was the director of the Strasbourg astronomical data centre CDS from 1995 to 2015\, and one of the founding parents of the astronomical Virtual Observatory project. She has coordinated several projects dealing with the European Virtual Observatory. She currently leads the “Data Access\, Discovery and Interoperability” Work Package of the European ASTERICS astronomy Cluster\, which aims to optimize the usage of data from large astronomical projects through the Virtual Observatory. She was a member of the High Level Expert Group on Scientific Data of the European Commission\, which wrote the “Riding the wave” report (2010) and the subsequent “Data Harvest” report. She is co-chair of the RDA Technical Advisory Board\, and an active member to several RDA Europe projects. She is a current member of the Data Seal of Approval Board\, and a past member of the WDS Scientific Committee (2009-2015) and of CODATA Executive Committee (2010-2012). \n*Lunch will be served at 11:45 AM.\n**To ensure you have a space at the seminar\, please RSVP by Feb. 10\, 2017.
URL:https://idre.ucla.edu/calendar-event/data-as-infrastructure
LOCATION:CA
CATEGORIES:Conferences and Seminars,Meetings,Presentations
ORGANIZER;CN="T V Singh":MAILTO:tvsingh@ucla.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20170214T090000
DTEND;TZID=America/Los_Angeles:20170214T120000
DTSTAMP:20260619T223547
CREATED:20161102T230444Z
LAST-MODIFIED:20161102T230444Z
UID:6977-1487062800-1487073600@idre.ucla.edu
SUMMARY:Introduction to Regression with SPSS
DESCRIPTION:This workshop will introduce some fundamental topics in regression analysis using SPSS in three parts. The first part will begin with a brief overview of the SPSS environment\, as well simple data exploration techniques to ensure accurate analysis using simple and multiple regression. The second part will introduce regression diagnostics such as checking for normality of residuals\, unusual and influential data\, homoscedasticity and multicollinearity. The third part of this workshop will introduce categorical variables.  Special attention will be given to interpreting a two-way categorical interaction with dummy variables and multiple-category predictors.
URL:https://idre.ucla.edu/calendar-event/introduction-regression-spss-2
LOCATION:CA
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20170210T100000
DTEND;TZID=America/Los_Angeles:20170210T120000
DTSTAMP:20260619T223547
CREATED:20170123T183535Z
LAST-MODIFIED:20170202T032015Z
UID:7351-1486720800-1486728000@idre.ucla.edu
SUMMARY:Python for High Performance Computing I
DESCRIPTION:Python\, originally developed as a general purpose programming language\, has gained its popularity in the scientific community in recently years owning to its elegant and easy- to-understand syntax and powerful libraries. Python fully supports both functional and object-oriented programming styles. This class will present a number useful features of Python in the context of scientific computing\, and introduce a number of supporting packages\, including numpy for array-based computations and h5py to access HDF5 files\, and the use of Python in parallel computing (MPI style). \nThis is part 1 of a 2-part presentation.
URL:https://idre.ucla.edu/calendar-event/python-high-performance-computing
LOCATION:CA
CATEGORIES:Classes and Workshops,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20170209T100000
DTEND;TZID=America/Los_Angeles:20170209T120000
DTSTAMP:20260619T223547
CREATED:20170123T183807Z
LAST-MODIFIED:20170123T183807Z
UID:7349-1486634400-1486641600@idre.ucla.edu
SUMMARY:Using Hoffman2 cluster
DESCRIPTION:This session is a general introduction to how to use UCLA Hoffman2 Cluster. The objective is to familiarize current and potential cluster users with the Hoffman2 Cluster\, so they can make the best use of UCLA computational resources. The following topics will be covered: \n1. How to access and login to the Hoffman2 Cluster\, primarily in terminal/command-line mode.\n2. Exploration of how to run various computational tasks on or from the Hoffman2 Cluster\, illustrated by hands-on example transcripts.\n3. A brief introduction to Univa Grid Engine (UGE) commands and how to achieve more control over resources. \nThis session is appropriate for entry-level and mid-level cluster users. No prerequisite knowledge is required\, but some working experience with basic Unix system commands and Fortran or C programming languages will be helpful.  The registrants are recommended to do a quick survey in the following link before the class: https://www.surveymonkey.com/r/5KW8LQ2
URL:https://idre.ucla.edu/calendar-event/using-hoffman2-cluster-2017-winter
LOCATION:CA
CATEGORIES:Classes and Workshops,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20170208T114500
DTEND;TZID=America/Los_Angeles:20170208T130000
DTSTAMP:20260619T223547
CREATED:20170118T195927Z
LAST-MODIFIED:20170206T185451Z
UID:7323-1486554300-1486558800@idre.ucla.edu
SUMMARY:Big Data and Information Policies for Behavior Change
DESCRIPTION:  \n  \nSpeaker: Omar I. Asensio\, Ph.D.\, IDRE Scholar\nInstitute of the Environment & Sustainability\,\nAnderson School of Management Ziman Center\,\nUCLA \nTime:  12 p.m. to 1 p.m. (Lunch will be served*)\nDate: Feb 8\, 2017\nLocation:  5628\, Math Sciences Building \nRegistration:   https://idre.ucla.edu/calendar-event/big-data-and-information-policies#rsvp‎ \n  \nAbstract:\nMobile apps and smart metering technologies can provide a wealth of data and information to guide real-time decisions about consumption or investment. However\, we often have limited understanding of how information provided with these technologies can be framed to meet social or policy objectives. In this talk\, I will discuss experimental evidence on the effectiveness of information to drive energy conservation behavior in residential and commercial buildings. Emphasis will be placed on the framing of incentives\, smart metering and approaches to accelerate the adoption of innovations through changes in behavior. \nSpeaker’s bio:\nDr. Omar I. Asensio is a postdoctoral scholar at UCLA’s Institute of the Environment & Sustainability and the Anderson School of Management Ziman Center. He uses field experiments and quantitative methods to address innovation challenges related to energy\, transportation and urban sustainability. His forthcoming research on energy efficiency strategies in commercial buildings will be featured in Science – Editor’s choice section. He holds a doctorate in environmental science and engineering from UCLA and is a former National Science Foundation IGERT fellow with a topic in clean energy for green industry. \n*Lunch will be served at 11:45 AM.\n**To ensure you have a space at the seminar\, please RSVP by Feb 05\, 2017.
URL:https://idre.ucla.edu/calendar-event/big-data-and-information-policies
LOCATION:CA
ORGANIZER;CN="T V Singh":MAILTO:tvsingh@ucla.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20170207T090000
DTEND;TZID=America/Los_Angeles:20170207T120000
DTSTAMP:20260619T223547
CREATED:20161102T230016Z
LAST-MODIFIED:20161102T230016Z
UID:6973-1486458000-1486468800@idre.ucla.edu
SUMMARY:Applied Survey Data Analysis with Stata
DESCRIPTION:This workshop will show how descriptive analyses\, both numerical and graphical\, can be done with continuous and categorical variables.  Subpopulation analysis will be discussed\, and then examples of OLS regression and logistic regression will be considered.
URL:https://idre.ucla.edu/calendar-event/applied-survey-data-analysis-stata
LOCATION:CA
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20170131T090000
DTEND;TZID=America/Los_Angeles:20170131T120000
DTSTAMP:20260619T223547
CREATED:20161102T225632Z
LAST-MODIFIED:20161102T230250Z
UID:6969-1485853200-1485864000@idre.ucla.edu
SUMMARY:Multiple Imputation in SAS 9.4
DESCRIPTION:The purpose of this workshop is to discuss commonly used techniques for handling missing data and common issues that could arise when these techniques are used. In particular\, the se workshop will focus on the one of the most commonly used modern methods\, multiple imputation.  The workshop will cover multiple imputation using the multivariate normal and imputation by chained equations as well as imputation diagnostics.
URL:https://idre.ucla.edu/calendar-event/multiple-imputation-sas-9-4
LOCATION:CA
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20170125T113000
DTEND;TZID=America/Los_Angeles:20170125T130000
DTSTAMP:20260619T223547
CREATED:20170104T222730Z
LAST-MODIFIED:20170111T214330Z
UID:7146-1485343800-1485349200@idre.ucla.edu
SUMMARY:Hoffman2 Users Group Meeting - Sold Out
DESCRIPTION:If you currently use Hoffman2 or are interested in doing so\, this is a great opportunity to get information on UCLA’s shared high-performance computing environment and provide feedback to the IDRE Research Technology Group on the future direction of the service. \nThe meeting will include a quick overview of the Hoffman2 cluster\, HPC storage\, and our Cloud Archival Storage Service (CASS). There will also be technical presentations on the scheduling system\, using tiered storage\, as well as other topics suggested by our user community. Most importantly we want to hear from you\, so bring your questions and ideas and get them heard. \nLunch will be served\, so please be sure to RSVP. \nA detailed agenda will be provided within the next couple of weeks. \nIf you have suggestions for topics that you feel would appeal to a broad audience of your fellow Hoffmn2 users\, please email them to Bill Labate\, labate@idre.ucla.edu. We will make every effort to incorporate your suggestions into the meeting as time permits. \nWe hope to see you there! \nThe IDRE Research Technology Group \n 
URL:https://idre.ucla.edu/calendar-event/hoffman2-users-group-meeting
LOCATION:CA
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20161116T100000
DTEND;TZID=America/Los_Angeles:20161116T120000
DTSTAMP:20260619T223547
CREATED:20161102T225342Z
LAST-MODIFIED:20161102T225342Z
UID:6966-1479290400-1479297600@idre.ucla.edu
SUMMARY:Introduction to Structural Equation Modeling Using Stata
DESCRIPTION:This talk will introduce the concepts and jargon of structural equation modeling (SEM).  We will demonstrate how to fit SEMs for continuous outcomes using the -sem- command in Stata.  We will also demonstrate how use Stata’s -gsem- command to fit multilevel structural equation models that include continuous\, binary\, multinomial\, ordinal and count outcomes using a wide variety of link functions.
URL:https://idre.ucla.edu/calendar-event/introduction-structural-equation-modeling-using-stata
LOCATION:CA
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20161109T114500
DTEND;TZID=America/Los_Angeles:20161109T130000
DTSTAMP:20260619T223547
CREATED:20161005T205330Z
LAST-MODIFIED:20161108T002215Z
UID:6612-1478691900-1478696400@idre.ucla.edu
SUMMARY:The Hacker Web Project: Exploring the Dark Side of the Web
DESCRIPTION:  \n  \n  \nSpeaker: Hsinchun Chen\, Ph.D.;\nArizona Regents’ Professor\,\nThomas R. Brown Chair Professor in Management and Technology\, University of Arizona;\nDirector\, Artificial Intelligence Lab; Fellow\, ACM\, IEEE\, AAAS \nTime:  12 p.m. to 1 p.m. (Lunch will be served*)\nLocation:  Kerckhoff Hall – Charles E. Young Grand Salon\nRegistration: https://idre.ucla.edu/calendar-event/hacker-web-project#rsvp\nAbstract: \nIn this talk I will review our highly-acclaimed NSF-funded Hacker Web research\, which develops advanced data\, text and web mining techniques to explore the international underground hacker community. Selected research in identifying key hackers\, important hacker assets\, and emerging threats in the carding community will be presented. Via collaboration with the intelligence community and the industry\, we have also developed tools and datasets for assisting the law enforcement and security analytics community. \nFor more project information\, see: https://ai.arizona.edu/research/cyber\nFor recent NSF press information\, see: https://nsf.gov/discoveries/disc_summ.jsp?cntn_id=136513&org=NSF \nAbout Speaker: \nDr. Hsinchun Chen graduated with BS at the National Chiao-Tong University (Taiwan)\,  MBA at SUNY Buffalo\, and MS and Ph.D. at New York University. He is the University of Arizona Regents’ Professor and Thomas R. Brown Chair Professor in Management and Technology. He is also a Fellow of ACM\, IEEE and AAAS. Dr. Chen recently served as the lead Program Director (expert) of the Smart and Connected (SCH) Program at the NSF (2014-2015)\, a multi-year multi-agency health IT research program of USA. He is author/editor of 20 books\, 280 SCI journal articles\, and 150 refereed conference articles covering digital library\, data/text/web mining\, business analytics\, security informatics\, and health informatics. His overall h-index is 91 (25\,000 citations for 900 papers according to Google Scholar)\, among the highest in management information systems and top 50 in computer science. Dr. Chen founded the Artificial Intelligence Lab at the University of Arizona in 1989\, which has received more than $40M in research funding from NSF\, NIH\, NLM\, DOD\, DOJ\, CIA\, DHS\, and other agencies (90 grants\, 40 from NSF). He has served as Editor-in-Chief of major ACM/IEEE\, and Springer journals and conference/program chair of major ACM/IEEE/MIS conferences in digital library\, information systems\, security informatics\, and health informatics. He is also a successful IT entrepreneur. His COPLINK/i2 system for security analytics was commercialized in 2000 and acquired by IBM as its leading government analytics product in 2011. Dr. Chen has served as an advisor to major federal research programs and was a Scientific Counselor of the National Library of Medicine (USA)\, National Library of China\, and Academia Sinica (Taiwan). He is a visiting chair professor at several major universities in China (Tsinghua University) and Taiwan (National Taiwan University). He is internationally renowned for leading the research and development in the health analytics (data and text mining; health big data; DiabeticLink and SilverLink) and security informatics (counter terrorism and cyber security analytics; security big data; COPLINK\, Dark Web and Hacker Web) communities. See: http://ai.arizona.edu/hchen. \n*Lunch will be ready at 11:45 AM.\n**To ensure you have a space at the seminar\, please RSVP by Nov. 3\, 2016. \n 
URL:https://idre.ucla.edu/calendar-event/hacker-web-project
LOCATION:Kerckhoff –  Charles E. Young Grand Salon\, 308 Westwood Plaza\, Los Angeles\, 90095\, United States
CATEGORIES:Conferences and Seminars,Education and Training,Presentations,UCLA event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20161108T090000
DTEND;TZID=America/Los_Angeles:20161108T120000
DTSTAMP:20260619T223547
CREATED:20161011T191119Z
LAST-MODIFIED:20161011T191119Z
UID:6659-1478595600-1478606400@idre.ucla.edu
SUMMARY:Introduction to R
DESCRIPTION:Introduction to R\, November 8:  R is a powerful statistical package that runs on many platforms\, including Windows\, Macintosh and Unix. This class is designed for people who are just getting started using R. The students in the class will have a hands-on experience using R for statistics\, graphics\, and data management. The R class notes do not contain any of the computer output. The class notes are not meant to be an R textbook or a reference manual. However\, it is possible for individuals to use the class notes to help in learning R even if they don’t enroll in the workshop.
URL:https://idre.ucla.edu/calendar-event/introduction-to-r-3
LOCATION:CLICC Classroom C\, 320 Powell Library\, 10740 Dickson Court\, Los Angeles\, CA\, 90095\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20161024T090000
DTEND;TZID=America/Los_Angeles:20161024T120000
DTSTAMP:20260619T223547
CREATED:20160808T223143Z
LAST-MODIFIED:20160815T213619Z
UID:6238-1477299600-1477310400@idre.ucla.edu
SUMMARY:Introduction to R
DESCRIPTION:Introduction to R\, October 24:  R is a powerful statistical package that runs on many platforms\, including Windows\, Macintosh and Unix. This class is designed for people who are just getting started using R. The students in the class will have a hands-on experience using R for statistics\, graphics\, and data management. The R class notes do not contain any of the computer output. The class notes are not meant to be an R textbook or a reference manual. However\, it is possible for individuals to use the class notes to help in learning R even if they don’t enroll in the workshop. \n 
URL:https://idre.ucla.edu/calendar-event/introduction-to-r-2
LOCATION:CLICC Classroom B\, 320 Powell Library\, 10740 Dickson Court\, Los Angeles\, CA\, 90095\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20161020T140000
DTEND;TZID=America/Los_Angeles:20161020T160000
DTSTAMP:20260619T223547
CREATED:20160912T214439Z
LAST-MODIFIED:20160912T220443Z
UID:6340-1476972000-1476979200@idre.ucla.edu
SUMMARY:Computing Environment on Linux – II
DESCRIPTION:The second session of the Computing Environment on Linux is about the use of the Linux system for computation. It will describe the compilation and execution procedures for a given source program. A sample software code will be used to demonstrate the computing tools\, such as makefile\, debugger\, and profiler\, available on most flavors of the Linux environment.
URL:https://idre.ucla.edu/calendar-event/computing-linux-ii
LOCATION:Kerckhoff –  Charles E. Young Grand Salon\, 308 Westwood Plaza\, Los Angeles\, 90095\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20161020T100000
DTEND;TZID=America/Los_Angeles:20161020T110000
DTSTAMP:20260619T223547
CREATED:20161012T235018Z
LAST-MODIFIED:20161012T235018Z
UID:6736-1476957600-1476961200@idre.ucla.edu
SUMMARY:A Tour and Discussion of Free SAS Resources for Teaching
DESCRIPTION:A SAS representative would like to introduce professors (and UCLA researchers in general) about free SAS resources that can be used for teaching.  The event will involve a short presentation by the SAS representative\, but will mostly be a Q&A session.
URL:https://idre.ucla.edu/calendar-event/tour-discussion-free-sas-resources-teaching
LOCATION:CA
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20161018T140000
DTEND;TZID=America/Los_Angeles:20161018T160000
DTSTAMP:20260619T223547
CREATED:20160912T213214Z
LAST-MODIFIED:20160912T220542Z
UID:6336-1476799200-1476806400@idre.ucla.edu
SUMMARY:Computing Environment on Linux - I
DESCRIPTION:Part-I session of Computing Environment on Linux class is aimed to help researchers who are new to Linux system. This two hour session will introduce basic Unix/Linux commands\, shells\, as well as a few editors available on most of the flavors of Linux operating system. The  user should be able to log in to a Linux system and use it to do normal tasks after going through this session.
URL:https://idre.ucla.edu/calendar-event/computing-linux-i
LOCATION:Kerckhoff –  Charles E. Young Grand Salon\, 308 Westwood Plaza\, Los Angeles\, 90095\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20161017T090000
DTEND;TZID=America/Los_Angeles:20161017T120000
DTSTAMP:20260619T223547
CREATED:20160808T223041Z
LAST-MODIFIED:20160815T213606Z
UID:6237-1476694800-1476705600@idre.ucla.edu
SUMMARY:Introduction to SPSS
DESCRIPTION:Introduction to SPSS\, October 17:  SPSS is a very easy-to-use statistical package that runs on Windows\, Macintosh and UNIX platforms. This class is designed for people who are just starting to use SPSS. The students in the class will have a hands-on experience using SPSS for doing statistics\, graphics\, and data management. The class notes are the scripts for the class. The SPSS class notes do not contain any of the computer output. The class notes are not meant to be an SPSS textbook or a reference manual. However\, it is possible for individuals to use the class notes to help them learn SPSS even if they don’t enroll in the workshop.  These notes were developed using SPSS version 22\, but most of the material should work with slightly earlier or later versions of SPSS. \n  \n 
URL:https://idre.ucla.edu/calendar-event/introduction-to-spss-2
LOCATION:CLICC Classroom B\, 320 Powell Library\, 10740 Dickson Court\, Los Angeles\, CA\, 90095\, United States
ORGANIZER;CN="UCLA IDRE Statistical Consulting":MAILTO:idrestat@ucla.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20161013T140000
DTEND;TZID=America/Los_Angeles:20161013T160000
DTSTAMP:20260619T223547
CREATED:20160822T171213Z
LAST-MODIFIED:20160822T220928Z
UID:6267-1476367200-1476374400@idre.ucla.edu
SUMMARY:Introduction to MPI (Message Passing Interface)
DESCRIPTION:MPI (message passing interface) is the de facto standard for distributed-memory parallel scientific computing. While the entire MPI API is quite extensive\, this class will cover a number of key ingredients commonly used in practice. This class is useful for those who plan to start writing MPI code\, and for those who would like to know how MPI works in order to operate an existing MPI code. Working knowledge of C and Fortran programming languages will be very helpful to follow the class materials.  \nSpecifically\, we will discuss: \n\nMPI basics\nOne-to-one communication examples\nCollective communication examples\nRunning MPI programs
URL:https://idre.ucla.edu/calendar-event/introduction-to-mpi-2016-fall
LOCATION:CA
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20161012T140000
DTEND;TZID=America/Los_Angeles:20161012T160000
DTSTAMP:20260619T223547
CREATED:20160822T171358Z
LAST-MODIFIED:20160926T233306Z
UID:6265-1476280800-1476288000@idre.ucla.edu
SUMMARY:Job scheduling on Hoffman2 cluster
DESCRIPTION:We will discuss how to effectively run jobs on Hoffman2 cluster. Hoffman2 cluster serves a wide spectrum of user applications and is almost always heavily loaded. Different kinds of jobs impose conflicting conditions in terms of job scheduling\, given available computing resources. We will first review the components of Hoffman2 cluster\, the shared cluster model\, followed by fundamentals of using it’s job scheduler\, Univa Grid Engine. Then a number of use cases will be discussed in details. The materials covered in “Using Hoffman2 cluster” is highly recommended\, but not strictly required\, prior to attending this class. \nSpecifically\, we will discuss: \n\nSingle-CPU jobs\nMulti-CPU\, same-node jobs\nMultiple-node (MPI-style) jobs\nJob arrays\nTechniques to inspect and fix stuck jobs
URL:https://idre.ucla.edu/calendar-event/job-scheduling-on-hoffman2-cluster-2016-fall
LOCATION:CA
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20161010T090000
DTEND;TZID=America/Los_Angeles:20161010T120000
DTSTAMP:20260619T223547
CREATED:20160808T222927Z
LAST-MODIFIED:20160815T213411Z
UID:6236-1476090000-1476100800@idre.ucla.edu
SUMMARY:Introduction to SAS
DESCRIPTION:Introduction to SAS\, October 10:  SAS is a powerful statistical package that runs on many platforms\, including Windows and Unix. This class is designed for people who are just getting started using SAS. The students in the class will have a hands-on experience using SAS for statistics\, graphics\, and data management. The SAS class notes do not contain any of the computer output. The class notes are not meant to be a SAS textbook or a reference manual. However\, it is possible for individuals to use the class notes to help in learning SAS even if they don’t enroll in the workshop. \n  \n 
URL:https://idre.ucla.edu/calendar-event/introduction-to-sas-2
LOCATION:CLICC Classroom B\, 320 Powell Library\, 10740 Dickson Court\, Los Angeles\, CA\, 90095\, United States
ORGANIZER;CN="UCLA IDRE Statistical Consulting":MAILTO:idrestat@ucla.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20161006T140000
DTEND;TZID=America/Los_Angeles:20161006T160000
DTSTAMP:20260619T223547
CREATED:20160819T201048Z
LAST-MODIFIED:20160822T171254Z
UID:6263-1475762400-1475769600@idre.ucla.edu
SUMMARY:Using Hoffman2 Cluster
DESCRIPTION:This session is a general introduction to how to use UCLA Hoffman2 Cluster. The objective is to familiarize current and potential cluster users with the Hoffman2 Cluster\, so they can make the best use of UCLA computational resources. The following topics will be covered: \n\n How to access and login to the Hoffman2 Cluster\, primarily in terminal/command-line mode.\n Exploration of how to run various computational tasks on or from the Hoffman2 Cluster\, illustrated by hands-on example transcripts.\n A brief introduction to Univa Grid Engine (UGE) commands and how to achieve more control over resources.\n\nThis session is appropriate for entry-level and mid-level cluster users. No prerequisite knowledge is required\, but some working experience with basic Unix system commands and Fortran or C programming languages will be helpful. \nPlease submit this pre-class survey when you sign up: https://www.surveymonkey.com/r/6P6RH6J
URL:https://idre.ucla.edu/calendar-event/using-hoffman2-cluster-2016-fall
LOCATION:CA
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20161003T090000
DTEND;TZID=America/Los_Angeles:20161003T120000
DTSTAMP:20260619T223547
CREATED:20160808T210907Z
LAST-MODIFIED:20160815T214043Z
UID:6234-1475485200-1475496000@idre.ucla.edu
SUMMARY:Introduction to Stata
DESCRIPTION:Introduction to Stata\, October 3:  Stata is a powerful and yet easy-to-use statistical package that runs on Windows\, Macintosh and Unix platforms.  This class is designed for people who are just getting started using Stata.  The students in the class will have a hands-on experience using Stata for statistics\, graphics and data management.  The class notes are the scripts for the class available to the students in the class and to others on the Internet.  The Stata class notes do not contain any of the output.  The class notes are not meant to be a Stata textbook or a reference manual.  However\, it is possible for individuals to use the class notes to help in learning Stata even if they don’t enroll in the workshop. \n 
URL:https://idre.ucla.edu/calendar-event/introduction-to-stata-2
LOCATION:CLICC Classroom B\, 320 Powell Library\, 10740 Dickson Court\, Los Angeles\, CA\, 90095\, United States
ORGANIZER;CN="UCLA IDRE Statistical Consulting":MAILTO:idrestat@ucla.edu
END:VEVENT
END:VCALENDAR