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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260408T103000
DTEND;TZID=America/Los_Angeles:20260408T123000
DTSTAMP:20260514T053057
CREATED:20260401T221604Z
LAST-MODIFIED:20260401T221932Z
UID:26619-1775644200-1775651400@idre.ucla.edu
SUMMARY:XRI Tech Talk with Pier Paolo Bellini
DESCRIPTION:Immersive Communication for the Enhancement of Cultural Heritage: Opportunities and Questions\n\nJoin us for a presentation by Pier Paolo Bellini\, Associate Professor of Sociology of Cultural Processes at the University of Molise. Professor Bellini teaches Sociology of Communication\, Sociology of the Media\, Sociology of Educational and Communicative Processes\, and Sound Management Laboratory in Multimedia Products. Recently publishing The Creative Gesture: Contexts\, Processes\, Actors of Creativity in 2024\, the central themes of his research focus on the study of two cultural processes: expressiveness linked to symbolic dynamics (particularly those of a creative nature) and the educational processes that underlie the construction of identity. \nOver the last several years\, he has been working on projects dedicated to the use of technology (virtual reality\, augmented reality\, and the metaverse) for the enhancement of cultural heritage\, publishing. In particular\, his upcoming project will introduce artificial intelligence (in the form of an avatar) to guide visitors through the archaeological sites of our region. \nSchedule: \n\n10:30 a.m. Coffee and registration\n11:00 a.m.  Presentation\n11:30 a.m.  Discussion\n12-12:30 p.m. Wrap up and conclusion\n\nSupport for this XRI event provided by DataX and OARC.
URL:https://idre.ucla.edu/calendar-event/xri-tech-talk-with-pier-paolo-bellini
LOCATION:OARC Portal\, Math Sciences 5628\, 5628 Math Science Building\, UCLA
CATEGORIES:Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20250502T113000
DTEND;TZID=America/Los_Angeles:20250502T123000
DTSTAMP:20260514T053057
CREATED:20250423T111527Z
LAST-MODIFIED:20250616T164658Z
UID:25882-1746185400-1746189000@idre.ucla.edu
SUMMARY:Extracting low-order representations of vortex dominated flows using deep neural networks
DESCRIPTION:Speaker: Barbara Lopez-Doriga\, Ph.D.\nIDRE Postdoctoral Fellow\nMechanical and Aerospace Engineering\nUniversity of California Los Angeles \nPlace: Virtual (Register here for the zoom link) \n  \n\n\nAbstract: There is significant practical interest in understanding and modeling fluid systems\, not only to gain insights into the complex dynamics that govern them\, but also to enable their control for different purposes. These systems are often characterized by a vast number of degrees of freedom and typically demand large amounts of high-fidelity data and computational resources for accurate simulation. In this talk\, I will briefly review several fluid dynamics problems currently being tackled with the aid of large-scale computational tools\, before focusing on the specific challenge addressed by my research. \nUnsteady aerodynamic effects are prevalent in the atmospheric boundary layer and can negatively impact the performance and stability of small- to medium-scale air vehicles. This research aims to identify the parameters and physical factors that can help mitigate these unsteady effects (modeled here as vortex gust encounters) on the aerodynamic loads experienced by such vehicles. To achieve this\, we compile a dataset of gust interactions\, varying in strength and size\, with fixed airfoils of different geometries and angles of attack. We analyze the trends that emerge across these different scenarios and examine how these dynamics are captured and encoded into a low-dimensional latent space via an observable autoencoder. This framework not only enhances our understanding of gust-induced aerodynamic phenomena but also lays the groundwork for future shape optimization studies aimed at identifying airfoil designs that minimize transient aerodynamic loads. \nAbout the speaker: Dr. Lopez-Doriga recently started her position as a postdoctoral scholar in Professor Kunihiko (Sam) Taira’s lab in the Department of Mechanical and Aerospace Engineering at UCLA. Barbara received an MS and a BS in Mechanical Engineering from the Polytechnic University of Madrid\, Spain (UPM). She then received her ME and PhD in Mechanical and Aerospace Engineering from Illinois Institute of Technology (Chicago\, IL). Since joining Taira’s lab\, her interest has been in developing a data-driven machine-learning-based framework to find the optimal airfoil design and control systems for gust mitigation.
URL:https://idre.ucla.edu/calendar-event/barbara-ldoriga-may-2-2025
CATEGORIES:Conferences and Seminars,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240628T113000
DTEND;TZID=America/Los_Angeles:20240628T123000
DTSTAMP:20260514T053057
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:20240531T113000
DTEND;TZID=America/Los_Angeles:20240531T123000
DTSTAMP:20260514T053057
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:20240328T113000
DTEND;TZID=America/Los_Angeles:20240328T123000
DTSTAMP:20260514T053057
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:20240315T113000
DTEND;TZID=America/Los_Angeles:20240315T123000
DTSTAMP:20260514T053057
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:20240301T113000
DTEND;TZID=America/Los_Angeles:20240301T123000
DTSTAMP:20260514T053057
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:20240126T113000
DTEND;TZID=America/Los_Angeles:20240126T123000
DTSTAMP:20260514T053057
CREATED:20240109T204343Z
LAST-MODIFIED:20240213T051136Z
UID:24634-1706268600-1706272200@idre.ucla.edu
SUMMARY:Data-driven prediction of vortex dynamics with hierarchical graph neural networks
DESCRIPTION:Alec Linot \n  \nSpeaker: Alec Linot\, Ph.D.\nIDRE Fellow\nMechanical and Aerospace Engineering\nUniversity of California Los Angeles \n  \n  \nLocation: Zoom (Registration required)\n \nTime: 11:30 AM – 12:30 PM (PST)\nVideo Link: https://youtu.be/E8f2lrHMOa8 \n  \nAbstract: Forecasting the dynamics of fluid flows plays a crucial role in our understanding of processes such as the swimming of fish\, turbulence on a plane\, and hurricane formation. Unfortunately\, simulating these systems can be prohibitively expensive even though we often know the equations of motion. Due to this high computational cost\, major effort has gone toward developing reduced-order models (ROMs) of fluid flows both from first principles and in a data-driven manner. Various ROMs using Galerkin methods and neural networks\, for example\, have been shown to accurately predict the dynamics of fluid systems with far fewer degrees of freedom than needed in high-resolution simulations. However\, these ROMs typically apply to very specific systems with a fixed state size (e.g. grid size or latent space size). In this work\, we present a data-driven ROM method for discovering vortex dynamics that overcomes the challenge of a fixed state size by using a hierarchy of graph neural networks (GNNs). This method allows us to consider a fluid flow as a graph of the vortices within a flow. Then\, by grouping clusters of vortices\, we construct a hierarchy of graphs with which we train GNNs to predict vortex dynamics. Notably\, this hierarchal approach mirrors our intuition on how groups of vortices often cluster to act as a cohesive unit. We show that this hierarchical method is both more accurate and faster than constructing a fully connected GNN\, and we show that this approach allows us to predict vortex dynamics with state sizes (i.e. the number of vortices) outside of our training data. \nAbout the speaker: Dr. Alec Linot is a postdoctoral researcher with Prof. Kunihiko (Sam) Taira in the Mechanical and Aerospace Engineering Department at UCLA. He received a BS in Chemical Engineering from Kansas State University. His Ph.D is in Chemical and Biological Engineering from the University of Wisconsin – Madison. In his Ph.D.\, he developed machine learning techniques for modeling and controlling turbulent flows. His current research is in modeling\, control\, and stability of chaotic dynamical systems. Chaotic dynamical systems are deterministic systems where small perturbations to the system result in dramatically different dynamics over time.
URL:https://idre.ucla.edu/calendar-event/idre-fellow-jan26-2024
CATEGORIES:Conferences and Seminars,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20231005T113000
DTEND;TZID=America/Los_Angeles:20231005T133000
DTSTAMP:20260514T053057
CREATED:20230919T224332Z
LAST-MODIFIED:20231005T235108Z
UID:24313-1696505400-1696512600@idre.ucla.edu
SUMMARY:Intro to Julia: A fast dynamic language for statistical computing and data science
DESCRIPTION:  \n \n  \n  \nSpeaker: Seyoon Ko\, Ph.D.\nIDRE Fellow and Assistant Adjunct Professor\,\nMathematics Department\,\nUniversity of California Los Angeles \n  \n  \nLocation: Virtual\nLink to the recording: https://youtu.be/lmtHtuyl-Q0  \nAbstract: Julia (http://julialang.org) is a modern open-source programming language for technical computing. Its design offers much greater speed and productivity compared to R or Python\, as high-performance code does not need to be wrapped in a low-level language like C or Fortran. After almost a decade of active development\, Julia reached its first major release\, v1.0\, in 2018\, and is quickly gaining popularity in scientific computing and data science communities. In this workshop\, I will present the basic concepts of Julia and show a little comparison between Julia and other languages\, such as R\, C\, and Python. \nAbout the speaker: Dr. Ko is an Assistant Adjunct Professor at UCLA Mathematics. Previously\, he was a Postdoctoral Scholar working with Dr. Ken Lange and Dr. Hua Zhou in the Department of Computational Medicine. Dr. Ko’s research interests include large-scale computational methods in biostatistics and bioinformatics using parallel and distributed computing. He earned a Ph.D. degree in Statistics from Seoul National University in South Korea\, as well as a M.S. degree in Computational Sciences and a B.S. degree in Physics\, Mathematical Sciences\, and Computational Science.
URL:https://idre.ucla.edu/calendar-event/julia-by-seyoon-ko-ecr
CATEGORIES:Conferences and Seminars,Education and Training,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230918T110000
DTEND;TZID=America/Los_Angeles:20230918T143000
DTSTAMP:20260514T053057
CREATED:20230828T212729Z
LAST-MODIFIED:20230923T045719Z
UID:24166-1695034800-1695047400@idre.ucla.edu
SUMMARY:On Functional Brain Network and Dynamic Multivariate task fMRI Analysis
DESCRIPTION:Speaker: Prof. Nathan Spreng\nJames McGill Professor of Neurology and Neurosurgery\, McGill University\nDirector\, Laboratory of Brain and Cognition\, Montreal Neurological Institute. \nRSVP: Link to the recording of the second session. \nThe impact of loneliness on functional brain network organization across the lifespan (11:00 AM – 12:00 PM): Loneliness emerges when one’s need for interpersonal connection is unmet. Loneliness is a modifiable risk factor associated with poor mental and brain health across the lifespan. Over a series of studies examining the impact of loneliness on brain function\, measured with resting-state functional connectivity\, and analyzed using partial least squares analysis (PLS)\, we have demonstrated that associations between self-reported loneliness and functional network organization changes over the adult life course. In early adulthood\, higher levels of loneliness are associated with greater integration of visual regions with higher order association networks. From late middle-age and into older adulthood\, this pattern shifts\, with greater integration observed among higher order association networks and a relative isolation of the visual system. We hypothesize that these age-differences in network organization in the context of loneliness may reflect a shift from externally-oriented processing (e.g.\, perceiving negative social cues) in young\, to more internally-oriented processing (e.g.\, reminiscing or mentalizing about social experiences) in the later decades of life. These findings raise the intriguing possibility that the phenomena of loneliness may be a qualitatively different experience depending upon age. I will conclude with new directions of research into the impact of loneliness on older adults at risk for Alzheimer’s disease \nDynamic multivariate task fMRI analysis using Partial Least Squares in Matlab (1:00 PM – 2:30 PM): Whole brain imaging provides extraordinary opportunities to identify coherent patterns in the spatial structure and spatiotemporal functioning of cortical and subcortical brain regions. This has led to an explosion of network neuroscience research over the past two decades. Initially\, network studies adopted a general linear modelling (GLM) approach\, following the early structural and functional activation studies. However\, fMRI data is more amenable to multivariate approaches that consider dynamic aspects of brain function given its high dimensionality\, temporal complexity\, and the issue of multiple statistical comparisons. In this workshop\, I will review a dynamic multivariate approach for task based fMRI data\, Partial Least Squares (PLS). In this workshop\, I will review practical aspects of PLS statistical modelling and analyses\, introduce the PLS GUI interface in Matlab\, and include key elements of analysis implementation and results interpretation. \nAbout Speaker: Dr. Nathan Spreng is the James McGill Professor of Neurology and Neurosurgery at McGill University\, and director of the Laboratory of Brain and Cognition at the Montreal Neurological Institute. His research examines large-scale brain network dynamics and their role in cognition. Currently\, he is investigating the links between memory\, attention\, cognitive control\, and social cognition and the interacting brain networks that support them. He is also actively involved in the development and implementation of novel multivariate statistical approaches to assess activity and interactivity of large scale brain networks. His work adopts a network neuroscience approach to investigating complex cognitive processes as they change across the lifespan\, both in normal aging and brain disease.
URL:https://idre.ucla.edu/calendar-event/jason-nomi-9-18-2023
CATEGORIES:Conferences and Seminars,Education and Training,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230630T113000
DTEND;TZID=America/Los_Angeles:20230630T123000
DTSTAMP:20260514T053057
CREATED:20230614T224625Z
LAST-MODIFIED:20230724T234540Z
UID:24118-1688124600-1688128200@idre.ucla.edu
SUMMARY:Leveraging big data in ecology and atmospheric science to study impacts of wildfire smoke on birds
DESCRIPTION:  \nSpeaker: Olivia Sanderfoot\, Ph.D.\nIDRE Fellow\nEcology & Evolutionary Biology\nUniversity of California Los Angeles \n  \n  \nLocation: Link to the recording \nTime: 11:30 AM – 12:30 PM (PST)\nRegistration Link: https://youtu.be/Xked2hZBq44\n \n  \nAbstract: Global wildfire activity is increasing globally\, and people and wildlife are increasingly exposed to hazardous smoke. Despite the well-established risks wildfire smoke poses to public health\, few studies have investigated how smoke impacts non-human animals. Birds are especially vulnerable to smoke due to their heightened sensitivity to air pollution. In this talk\, I will share my vision for linking big data from ecology and atmospheric science to learn more about the effects of smoke on the health and behavior of birds and discuss several case studies that demonstrate the potential of interdisciplinary\, cross-campus collaborations to address critical knowledge gaps and inform conservation. \nAbout the speaker: Dr. Olivia Sanderfoot studies the impacts of wildfire smoke on birds and other wildlife. As the 2023 La Kretz Center for California Conservation Science Postdoctoral Fellow\, Olivia is exploring how wildfire smoke influences bird behavior and shapes species distributions in California. Additionally\, she is partnering with the Natural History Museum of Los Angeles County to launch a new community science project in southern California to learn more about how smoke impacts local birds. \nBefore moving to Los Angeles\, Olivia conducted her doctoral research in the School of Environmental and Forest Sciences at the University of Washington in Seattle. Her dissertation explored how wildfire smoke and urban air pollution impacted the detection of birds in Washington state. \nOlivia has been interviewed about her research by National Geographic\, TIME\, Discover\, and Audubon magazines\, Popular Science\, The Seattle Times\, The Washington Post\, and several local radio and TV stations. \nOlivia was born and raised in Madison\, Wisconsin\, and is a proud alumna of the University of Wisconsin – Madison; she received her B.S. in biology and Spanish in 2015 and her M.S. in environmental science in 2017. Born and raised in Wisconsin\, Olivia is driven by her passion for environmental policy and conservation\, her love for birds\, and her strong belief in the Wisconsin Idea\, the philosophy that a university’s research should be applied to solve problems and improve the health\, well-being\, and environment of the community it serves.
URL:https://idre.ucla.edu/calendar-event/olivia-sanderfoot-06-30-2023
CATEGORIES:Conferences and Seminars,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230525T113000
DTEND;TZID=America/Los_Angeles:20230525T123000
DTSTAMP:20260514T053057
CREATED:20230412T212045Z
LAST-MODIFIED:20230601T230618Z
UID:23905-1685014200-1685017800@idre.ucla.edu
SUMMARY:When will Quantum Computing be ready for Scientific Computing?
DESCRIPTION:Speaker: Jens Palsberg\, Ph.D.\, MBA\nProfessor of Computer Science\nSamueli School of Engineering \nUniversity of California Los Angeles \n  \nRecording link: https://youtu.be/NCcigLa_c7E \n\n  \n\nDescription: Quantum computing is rapidly getting better but still has some way to go before it can make a difference in science and business. I will introduce the field\, give the status of current hardware and simulators\, and point to resources for learning more about the technology and algorithms. Along the way\, I will mention some of the many quantum researchers at UCLA\, and I will highlight UCLA’s new quantum masters degree.\n  \nAbout the speaker: Jens Palsberg is a Professor and former Department Chair of Computer Science at University of California\, Los Angeles (UCLA). His research interests span the areas of programming languages\, software engineering\, and quantum computing. He is the director of the UCLA-Amazon Science Hub for Humanity and Artificial Intelligence\, an associate editor of ACM Transactions on Quantum Computing\, and a member of the ACM Executive Committee. In 2012 he received the ACM SIGPLAN Distinguished Service Award\, and in 2023 he received the Eon Instrumentation Inc. Excellence in Teaching Award at UCLA.\n\n 
URL:https://idre.ucla.edu/calendar-event/quantum-computing-readiness
CATEGORIES:Conferences and Seminars,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230428T113000
DTEND;TZID=America/Los_Angeles:20230428T123000
DTSTAMP:20260514T053057
CREATED:20230417T200200Z
LAST-MODIFIED:20230430T034600Z
UID:23981-1682681400-1682685000@idre.ucla.edu
SUMMARY:Stability and Resolvent Analysis of Fluid Flows - Methods and Challenges
DESCRIPTION:Speaker: Victoria Rolandi\, Ph.D.\nIDRE Fellow\nMechanical and Aerospace Department\nUniversity of California Los Angeles \n  \n\n\n\n\n\n\nLocation: Virtual via Zoom\n \nRecording available at: https://youtu.be/m9MTRk0ggrk \n\n\n\n\n\n\n\n\nAbstract: Understanding the transition of fluid flows has been and still is a crucial focus in fluid dynamics. Stability theory has greatly helped on this side and has opened the door to other branches in fluid dynamics\, such as flow control. By leveraging insights on flow transition\, flow control technology can help mitigate the human impact of environmental and noise pollution caused by fluid-based systems such as aircraft\, automobiles\, and wind turbines\, all while improving their overall performance. \nFrom linear stability analysis to resolvent analysis\, this talk will cover some of the methods that enable such investigations and the limitations\, in terms of computational resources\, on applying them to turbulent flows. \nAbout Speaker: Dr. Rolandi obtained a BSc in Mathematical Engineering from Politecnico di Torino and an MSc in Computational Science and Engineering from Politecnico di Milano. She later completed a Ph.D. in Fluid Dynamics at the Institute Supérieure de l’Aéronautique et de l’Espace (ISAE-Supaero) before joining the Mechanical and Aerospace department at UCLA as a postdoctoral researcher at Professor Taira’s Lab. Her research at UCLA focuses on developing and implementing algorithms helpful in characterizing\, modeling\, and controlling turbulent flows.
URL:https://idre.ucla.edu/calendar-event/victoria-4-28-2023
CATEGORIES:Conferences and Seminars,Education and Training,Meetings,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230324T113000
DTEND;TZID=America/Los_Angeles:20230324T123000
DTSTAMP:20260514T053057
CREATED:20230308T173309Z
LAST-MODIFIED:20230422T065444Z
UID:23719-1679657400-1679661000@idre.ucla.edu
SUMMARY:Urban biodiversity: the importance of scale
DESCRIPTION:Speaker: Nannan Gao\, Ph.D.\nIDRE Fellow\nDepartment of Ecology and Evolutionary Biology\nUniversity of California Los Angeles \n\n\n\n\n\n\n  \n\n\n\n\n\n\nLocation: Virtual via zoom\n \nRegistration Link: https://ucla.zoom.us/meeting/register/tJ0sdeGgqj0pHNzapieckX5w-dQAFTDr3d5D \n\n\n\n\n\n\n\n\nAbstract: While much is known about the scaling of biodiversity\, less is known about specifically how biodiversity scales in urban areas. This is an important question because over two-thirds of humans live in urban areas. Understanding how\, precisely\, biodiversity scales in urban areas will inform management. Linear relationships would imply that similar interventions should work across the range of city sizes (from small towns to the largest mega-cities) whereas non-linear relationships would imply that biodiversity strategies must be tailored to the size of the city. We focused on avian biodiversity because more than half of the species are found in urban areas (6120 species out of 11\,162 species)\, including at least 350 threatened ones. We calculated species richness in 2\,568 cities and used eBird\, a community science platform\, to estimate species richness. After controlling for a variety of variables that might explain variation in avian biodiversity\, we found a non-linear relationship in cities and contrasted this to a well-established power law found in natural areas. After controlling for other key variables that might explain variation in urban biodiversity\, the log-log relationship between city area and avian biodiversity had a slope of 0.42 until cities got bigger than 331 km2\, beyond which it decreased to 0.15. This suggests that unique processes affect urban biodiversity in smaller and larger cities. When we focused on the subset of threatened species\, we found a linear relationship with a slope of 0.20. Urbanization not only contributes to a global extinction\, but urban areas may provide important habitat for threatened species. \nAbout Speaker: Dr. Nannan Gao is a Postdoctoral associate with Daniel T. Blumstein in the Department of Ecology and Evolutionary Biology at UCLA. Her research mainly focuses on studying the relationship between urban biodiversity and city size by creating global urban biodiversity datasets that include small towns to megacities involving spatiotemporal advanced computing\, statistical computing and data science. Dr. Gao received her PhD in Chinese Academy of Science\, also studied human geography and urban planning in Peking University. She seeks to balance humans and animals in urban areas.
URL:https://idre.ucla.edu/calendar-event/urban-biodiversity
CATEGORIES:Conferences and Seminars,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230106T113000
DTEND;TZID=America/Los_Angeles:20230106T123000
DTSTAMP:20260514T053057
CREATED:20221213T011535Z
LAST-MODIFIED:20230109T215851Z
UID:23508-1673004600-1673008200@idre.ucla.edu
SUMMARY:Unsupervised Discovery of Ancestry Informative Markers and Genetic Admixture Proportions in Biobank-Scale Data Sets
DESCRIPTION:Speaker: Seyoon Ko\, Ph.D.\nIDRE Fellow\nComputational Medicine\nUniversity of California Los Angeles \n\n\n\n\n\n\n  \n  \nLocation: Virtual \nRecording of the presentation: https://youtu.be/8YAyHAp9Pfc \nAbstract: Admixture estimation is crucial in ancestry inference and genomewide association studies (GWAS). Computer programs such as ADMIXTURE and STRUCTURE are commonly employed to estimate the admixture proportions of sample individuals. However\, these programs can be overwhelmed by the computational burdens imposed by the 10^5 to 10^6 samples and millions of markers commonly found in modern biobanks. An attractive strategy is to run these programs on a set of ancestry informative SNP markers (AIMs) that exhibit substantially different frequencies across populations. Unfortunately\, existing methods for identifying AIMs require knowing ancestry labels for a subset of the sample. This supervised learning approach creates a chicken and the egg scenario. This talk presents an unsupervised\, scalable framework that seamlessly carries out AIM selection and likelihood-based estimation of admixture proportions. The simulated and real data examples show that this approach is scalable to modern biobank data sets. \n\n\n\n\n\n\nAbout the speaker: Dr. Ko is a Postdoctoral Scholar working with Dr. Ken Lange and Dr. Hua Zhou in the Department of Computational Medicine. Dr. Ko’s research interests include large-scale computational methods in biostatistics and bioinformatics using parallel and distributed computing. He earned a Ph.D. degree in Statistics from Seoul National University in South Korea\, as well as a M.S. degree in Computational Sciences and a B.S. degree in Physics\, Mathematical Sciences\, and Computational Science.\n \n\n\n\n\n\n\n 
URL:https://idre.ucla.edu/calendar-event/scale-data-set-01-06-2023
CATEGORIES:Conferences and Seminars,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221130T140000
DTEND;TZID=America/Los_Angeles:20221130T150000
DTSTAMP:20260514T053057
CREATED:20221114T213135Z
LAST-MODIFIED:20221201T211153Z
UID:23445-1669816800-1669820400@idre.ucla.edu
SUMMARY:Understanding scientific fields via network analysis and topic modeling
DESCRIPTION:  \nSpeaker: Harlin Lee\, Ph.D.\nIDRE Fellow\nMathematics Department\nUniversity of California Los Angeles \n  \nLocation: Virtual \nRecording: https://youtu.be/EkY_4gre9yU\n \n  \nAbstract: As scientific disciplines get larger and more complex\, it becomes impossible for an individual researcher to be familiar with the entire body of literature. This forces them to specialize in a sub-field\, and unfortunately\, such insulation can hinder the birth of ideas that arise from new connections\, eventually slowing down scientific progress. As such\, discovering fruitful interdisciplinary connections by analyzing scientific publications is an important problem in the science of science. This talk will present several past and ongoing projects towards answering that question using tools from network analysis and topic modeling: 1) a dynamic-embedding-based method for link prediction in a machine learning/AI semantic network\, 2) finding communities in cognitive science that study similar topics but do not cite each other or publish in the same venues\, and 3) developing theoretically grounded hypergraph embedding methods to capture surprising collaborations or missed opportunities. \nAbout the speaker: \nDr. Harlin Lee is a Hedrick Assistant Adjunct Professor at UCLA Mathematics. She received her Ph.D. in Electrical and Computer Engineering at Carnegie Mellon University in 2021. She also has an MS in Machine Learning from Carnegie Mellon University\, and a BS + MEng in Electrical Engineering and Computer Science from MIT. Her research is on learning from high-dimensional data supported on structures such as graphs (networks)\, low-dimensional subspace\, or sparsity\, motivated by applications in healthcare and social science. Dr. Lee’s lifelong vision is to use data theory to help everyone live physically\, mentally\, and socially healthier.
URL:https://idre.ucla.edu/calendar-event/harlin-lee-nov-30-2022
CATEGORIES:Conferences and Seminars,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220826T113000
DTEND;TZID=America/Los_Angeles:20220826T123000
DTSTAMP:20260514T053057
CREATED:20220808T235653Z
LAST-MODIFIED:20220901T235608Z
UID:23112-1661513400-1661517000@idre.ucla.edu
SUMMARY:Machine Learning of the Ocean Overturning Circulation
DESCRIPTION:  \nSpeaker: Aviv Solodoch\, Ph.D.\nIDRE Scholar\,\nAtmospheric and Oceanic Sciences\,\nUniversity of California Los Angeles \nLocation: Virtual (Click here for the recording)  \n  \nAbstract: The meridional overturning circulation (MOC) in the oceans is a fundamental circulation pattern whereby surface water cool and densify in polar regions\, and subsequently sink to great depths. These dense waters then spread horizontally at depth to cover virtually all deep ocean basins globally. The MOC has critical roles in the climate system\, including influencing global circulation patterns and heat fluxes\, and regulating the amount of anthropogenic heat and CO2 that is absorbed into the deep ocean\, buffering the advance of climate change. Therefore\, monitoring MOC variability and its interaction with climate change are of fundamental importance. In-situ monitoring of the MOC presents significant technological and logistical challenges due to the global extent of this circulation pattern. However\, some aspects of ocean circulation are now regularly measured via satellite remote sensing\, e.g.\, sea surface elevation and ocean bottom pressure. Therefore\, we develop a methodology to monitor MOC variability based on machine learning of satellite-measured ocean properties. We test this methodology within a data-constrained numerical simulation of the oceans\, i.e.\, using its output “satellite-observable’’ variables and MOC strength series as the ocean “truth’’. \nWe find that\, using a simple 1-layer feed-forward Neural Network (NN) with Bayesian regularization\, the MOC time-variability across most latitudes can be reconstructed with high skill. The reconstruction skill is higher than that of previously published dynamically based methods. To gain insight into the relations learned by the NN we use machine-learning interpretability techniques\, showing for example that most of the Southern Ocean MOC reconstruction skill is due to data from just a few key locations (mainly large seabed ridges)\, qualitatively consistent with fundamental physical theory. We further examine which satellite observables hold the most potential for MOC reconstruction. Finally\, we evaluate the robustness of the methodology and discuss a roadmap for implementing the method with real satellite data. \nAbout speaker: Aviv Solodoch obtained a BSc in Math and Physics from Tel Aviv University\, and a MSc in Physics from the Weizmann Institute of Science in Israel. He later completed a PhD in Atmospheric and Oceanic Sciences at UCLA\, where he is currently a postdoctoral researcher. During his MSc\, Aviv investigated air-sea interaction and heat exchange. During his PhD\, Aviv investigated processes causing instability\, offshore material exchange\, and vortex formation in oceanic currents\, using both numerical simulations and theory\, with a focus on currents which form part of the overturning circulation in the North Atlantic. Aviv also conducted observational research with UCLA Marine Operations\, studying coastal circulation dynamics in the Gulf of Mexico. He is presently studying the overturning circulation in the Southern Ocean\, as well as the dynamics of transport of material between the coastal and deep ocean regions.
URL:https://idre.ucla.edu/calendar-event/aviv-solodoc-idre-scholar
CATEGORIES:Conferences and Seminars,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220818T100000
DTEND;TZID=America/Los_Angeles:20220818T110000
DTSTAMP:20260514T053057
CREATED:20220623T162225Z
LAST-MODIFIED:20220623T162248Z
UID:23054-1660816800-1660820400@idre.ucla.edu
SUMMARY:Accessibility Testing Training
DESCRIPTION:In this live hour-long webinar\, the UCLA Disabilities and Computing Program will introduce the basics of accessibility testing. The ability to identify accessibility errors is the first step in making your content accessible. This class will focus on HTML accessibility and Document accessibility testing. \nAny questions about this workshop can be emailed to tlee@oarc.ucla.edu. \nRegister here: https://docs.google.com/forms/d/e/1FAIpQLScqbYJaXvDlJJ2BigBuD4ro3Eyaiblw2I3d8howZBY5635oyw/viewform
URL:https://idre.ucla.edu/calendar-event/accessibility-testing-training-3
LOCATION:Zoom
CATEGORIES:Presentations,UCLA event
ORGANIZER;CN="Disabilities and Computing Program":MAILTO:dcp@oit.ucla.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220527T120000
DTEND;TZID=America/Los_Angeles:20220527T130000
DTSTAMP:20260514T053057
CREATED:20220513T003636Z
LAST-MODIFIED:20220528T071335Z
UID:22965-1653652800-1653656400@idre.ucla.edu
SUMMARY:What is Causal Inference and Where is Data Science Going?
DESCRIPTION:  \n  \nSpeaker: Judea Pearl\nProfessor\nUCLA Computer Science Department\nUniversity of California Los Angeles \nDate and Time:May 27\, 2022 @12:00 PM (PST) \nPresentation slides: idre-may2022.pdf \nVideo recording: https://youtu.be/MNyI1Xkapxg \nAbstract: The availability of massive amounts of data coupled with an impressive performance of machine learning algorithms has turned data science into one of the most active research areas in academia. UCLA is no exception. The past few years\, however\, have uncovered basic limitations in the model-free direction that data science has taken. An increasing number of researchers have come to realize that statistical methodologies and the “black-box” data-fitting strategies used in machine learning are too opaque and brittle and must be enriched by a Causal Inference component to achieve their stated goal: Extract knowledge from data. Interest in Causal Inference has picked up momentum\, and it is now one of the hottest topics in data science*. \nThe purpose of this talk is to tell my colleagues at UCLA\, especially IDRE-minded researchers and students\, what Causal Inference is all about\, how it can be harnessed to solve practical data-scientific problems that cannot be solved by traditional methods\, and why it holds the key to the future of data science. \nAfter summarizing some glaring deficiencies of “data fitting” methods\, I will contrast them with “model-based” approaches and demonstrate how the latter can achieve a state of knowledge we can call “Deep Understanding”\, that is\, the capacity to answer questions of three types: predictions\, interventions\, and counterfactuals. \nI will further describe a computational model that facilitates reasoning at these three levels and demonstrate how features normally associated with “understanding” follow from this model. These include generating explanations\, generalizing across domains\, integrating data from several sources\, assigning credit and blame\, recovering from missing data\, and more. I will conclude by describing future research directions\, including automated scientific explorations and personalized decision-making. \n  \nBio sketch: Judea Pearl is Chancellor professor of computer science and statistics and director of the Cognitive Systems Laboratory at UCLA\, where he conducts research in artificial intelligence\, human reasoning\, and the philosophy of science. He is the author of Heuristics (1983) Probabilistic Reasoning (1988) and Causality (2000\,2009) and a founding editor of the Journal of Causal Inference. Among his awards are the Lakatos Award in the philosophy of science\, The Allen Newell Award from the Association for Computing Machinery\, the Benjamin Franklin Medal\, the Rumelhart Prize from the Cognitive Science Society\, the ACM Turing Award\, and the Grenander Prize from the American Mathematical Society. He is the co-author (with Dana MacKenzie) of The Book of Why: The New Science of Cause and Effect which brings Causal Inference to a general audience. \n  \n*Background material: \n\nhttps://ucla.in/3d2c2Fi\nhttps://ucla.in/3iEDRVo\nhttps://ucla.in/2HI2yyx\n\n  \n 
URL:https://idre.ucla.edu/calendar-event/causal-inference-and-data-science
CATEGORIES:Conferences and Seminars,Education and Training,Meetings,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220324T100000
DTEND;TZID=America/Los_Angeles:20220324T130000
DTSTAMP:20260514T053057
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:20220216T100000
DTEND;TZID=America/Los_Angeles:20220216T120000
DTSTAMP:20260514T053057
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
CATEGORIES:Classes and Workshops,Education and Training,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220209T100000
DTEND;TZID=America/Los_Angeles:20220209T120000
DTSTAMP:20260514T053057
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
CATEGORIES:Classes and Workshops,Education and Training,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220128T113000
DTEND;TZID=America/Los_Angeles:20220128T123000
DTSTAMP:20260514T053057
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;VALUE=DATE:20201117
DTEND;VALUE=DATE:20201120
DTSTAMP:20260514T053057
CREATED:20201030T214602Z
LAST-MODIFIED:20201030T214731Z
UID:20164-1605571200-1605830399@idre.ucla.edu
SUMMARY:UC GIS Week
DESCRIPTION:Register now for the first UC GIS Week conference from Nov. 17th – 19th!  \n \nThe UC GIS Week committee is proud to announce the first UC-wide GIS Week. Join us for a 3-day virtual conference which celebrates the GIS work of the University of California faculty\, staff\, students\, and alumni. The University of California system is holding an inaugural UC GIS Week on November 17th – 19th\, 2020 through Zoom. \nWe will celebrate all things mapping and geospatial. In light of the challenging times\, we are coming together virtually to share our work with our community. Researchers\, students\, industry partners\, alumni\, and community mappers\, will share their accomplishments and inspire others through their mapping. \nThis is an opportunity for you to learn and engage with experts and mapping projects across the UC system and beyond! Ask questions during the thematic mapping panels\, engage with GIS industry professionals\, interact with posters presenters\, and connect during social events. \n  \nAll talks are free and open to the public! \n  \nYour registration entitles you attend any or all of the tentatively scheduled events below: \nTuesday – 11/17 \n11am – 12pm: Opening plenary – Collaboration Across the UCs \n1pm – 2pm: Historical GIS | Policy Poster Session \n3pm – 4pm: Afternoon Historical GIS Workshop | Career Panel #1 \n  \nWednesday – 11/18 \n11am – 12pm: Remote Sensing | Mapping for Equality \n1pm – 2pm: Public Health | Career Panel #2 \n3pm – 4pm: Policy and Mapping – Lightning Talks | Environmental Science and Public Health Poster Session \n  \nThursday – 11/19 \n11am – 12pm: Environmental Science and Mapping – Lightning Talks \n1pm – 2pm: Regional and Urban GIS \n3pm – 4pm: Afternoon Risk Assessments Workshop \n  \nRegister now to stay informed and get early access to the 1st UC GIS Week digital swag bag! \nFor more info visit the UC GIS Week page. Would you like to contribute digital swag or have questions? Email: ucgisweek@gmail.com
URL:https://idre.ucla.edu/calendar-event/uc-gis-week
LOCATION:Zoom
CATEGORIES:Classes and Workshops,Conferences and Seminars,Education and Training,Presentations,UCLA event
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20201028
DTEND;VALUE=DATE:20201031
DTSTAMP:20260514T053057
CREATED:20201019T200439Z
LAST-MODIFIED:20201019T200748Z
UID:19741-1603843200-1604102399@idre.ucla.edu
SUMMARY:4th Annual Humanitarian Mapathon with USC and UCLA
DESCRIPTION:REGISTRATION IS NOW OPEN\, RSVP HERE! \n\n\n\nWednesday October 28th\, 10am (PDT): \n\nWelcome message and humanitarian map training\n\nThursday October 29th: \n\nContinue mapping and a day of workshops9am Open Street Map with Python\n\n11am Open Data and Tableau\n1pm GIS with R\n3pm Introduction to QGIS\n\n\n\nFriday October 30th\, 10am (PDT): \n\nWrap-up and closing Keynote with Ben Welsh from the Los Angeles Times\nBen Welsh (LA Times Data Journalist)\n\nLocation: Zoom\nGo to website for more details \n\nOnce again\, UCLA and USC are hosting a special 3 day humanitarian mapathon. Last year we had nearly 150 mappers collectively map 17\,126 building outlines for projects around the world that were impacted by climate change. Our event was one of the single largest mapathons in the world that day! This year we will highlight mapping projects impacted by COVID-19 as well as other urgent projects that need our attention. \nOur goal is to map more than 20\,000 buildings. We can only do this if we work together. \nThis year’s event begins on Wednesday with a welcome from your organizers and a day of virtual training on how to use OSM. The next day you can continue mapping and also join us for a diverse set of GIS/mapping workshops. Finally on Friday we will announce how many buildings we have mapped\, give out prizes to the top mappers from each school\, and have a discussion with our closing keynote speaker\, Ben Welsh\, from the Los Angeles Times. \nShare this with friends\, students\, faculty — anyone who might be interested. This year continues to be challenging on so many fronts. We want this event to be a space where we can come together from USC\, UCLA\, and all across Los Angeles to make a difference in people’s lives. \nFor more information visit our website. Once you register we will keep you updated as the event gets closer with pre-event training opportunities and materials. \nHope to see you soon\, \nUCLA+USC organizing committee for the 2020 Humanitarian Mapathon \nFor questions or inquiries: \nUSC – Andy Rutkowski arutkows@usc.edu\nUCLA – Yoh Kawano yohman@gmail.com
URL:https://idre.ucla.edu/calendar-event/4th-annual-humanitarian-mapathon-with-usc-and-ucla
LOCATION:Zoom
CATEGORIES:Classes and Workshops,Conferences and Seminars,Education and Training,Meetings,Presentations,UCLA event
ATTACH;FMTTYPE=image/png:https://idre.ucla.edu/wp-content/uploads/2020/10/4th-Annual-Mapathon.png
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20201019T100000
DTEND;TZID=America/Los_Angeles:20201019T120000
DTSTAMP:20260514T053057
CREATED:20200929T033125Z
LAST-MODIFIED:20201007T002313Z
UID:19270-1603101600-1603108800@idre.ucla.edu
SUMMARY:Running Applications on the Hoffman2 Cluster: Introduction
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 the Hoffman2 and how to submit batch 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 the environmental modules application set-up and how to find/install/run needed applications. \nPlease register here. \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 Raffaella D’Auria
URL:https://idre.ucla.edu/calendar-event/running-applications-on-the-hoffman2-cluster-introduction-4
LOCATION:Zoom
CATEGORIES:Classes and Workshops,Education and Training,Presentations,UCLA event
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20200807T110000
DTEND;TZID=America/Los_Angeles:20200807T120000
DTSTAMP:20260514T053057
CREATED:20200717T204426Z
LAST-MODIFIED:20200717T205701Z
UID:18324-1596798000-1596801600@idre.ucla.edu
SUMMARY:National Leadership Class Computing Resources and Opportunities for UCLA Researchers
DESCRIPTION:The Department of Energy\, National Science Foundation\, and the National Aeronautical Space Agency support an ecosystem of “leadership class” computing facilities housing some of the world’s most advanced supercomputers and high-end visualization and data analysis resources. These facilities provide “free” computing cycles at scale and storage to researchers from academia. Access to these resources is obtained 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 “leadership class” computing facilities. It will also describe how IDRE may help transition UCLA researchers from local resources and take advantage of these “free” magnificent computing facilities. \nThe presentation will be virtual via zoom. The link will be sent once rsvp is received. \nRSVP link: https://ucla.zoom.us/meeting/register/tJElduGuqDIqGtVUsyivGzy_lPMqT0dzM-ZE
URL:https://idre.ucla.edu/calendar-event/national-leadership-class-computing-resources-and-opportunities-for-ucla-researchers-4
LOCATION:Zoom
CATEGORIES:Education and Training,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20200806T100000
DTEND;TZID=America/Los_Angeles:20200806T120000
DTSTAMP:20260514T053057
CREATED:20200622T235457Z
LAST-MODIFIED:20200724T203121Z
UID:17316-1596708000-1596715200@idre.ucla.edu
SUMMARY:Deep Learning in Medicine
DESCRIPTION:Recent years have witnessed a dramatic resurgence of interest in applying deep learning in various research and application areas. In this 2 hour session\, we will present a broad and high-level overview on what deep-learning technologies can do for the domains of medicine and healthcare. Our discussion will focus on the three major application fields: medical imaging analysis\, natural language processing and deep reinforcement learning. In each field\, some of the landscape will be sketched by taking a brief literature survey on the current deep-learning-related research. At the same time we will dig into a couple of specific topics via reviewing some recent exciting achievements as illustrating examples for the subject. The talk will be closed with a general discussion about the challenges of deep learning in the medical and healthcare field. \nThis workshop is for all audiences\, which means the presentation is oriented for people with a wide range of backgrounds (e.g. from data scientists to medical professionals) and for both novices and experts. \nPlease REGISTER in advance for this Zoom Meeting before joining. \nRegister \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/deep-learning-in-medicine
LOCATION:Zoom
CATEGORIES:Classes and Workshops,Conferences and Seminars,Education and Training,Presentations
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20200605T120000
DTEND;TZID=America/Los_Angeles:20200605T130000
DTSTAMP:20260514T053057
CREATED:20200520T201957Z
LAST-MODIFIED:20200605T230136Z
UID:17216-1591358400-1591362000@idre.ucla.edu
SUMMARY:Epidemic Model Guided Machine Learning for COVID-19 Forecasts
DESCRIPTION:Time:  12:00 PM – 1:00 PM\nDate: June 05\, 2020\nLocation:  Zoom (you will receive an email after your rsvp) \nRSVP HERE \nLink to the presentation’s recording and slides \n\n\nAbstract: The novel coronavirus (COVID-19)\, which causes an acute respiratory disease in humans\, has emerged as a global pandemic\, and caused an over 250\,000 death toll in the world. Our lab recently launched a project (https://covid19.uclaml.org) to use machine learning to better understand the spread of COVID-19 and further facilitate the decision making of the government agencies. In this talk\, I will focus on an epidemic model-guided machine learning approach for the confirmed case and death forecasts for COVID-19\, and peak date projection in both state and national level. In specific\, we found that standard epidemic models such as SIR and SEIR are insufficient for modeling the spread of COVID-19. We therefore propose a variant of the SEIR model that takes into account the untested/unreported cases of COVID-19\, and then use a machine learning algorithm to train this model. Validation based on a week ahead prediction indicates that our model is more accurate than many other models including the model proposed by IHME at the University of Washington. \nAbout Speaker: Dr. Quanquan Gu is an Assistant Professor of Computer Science at UCLA. His current research is in the area of artificial intelligence and machine learning\, with a focus on developing and analyzing nonconvex optimization algorithms for machine learning and building the theoretical foundations of deep learning. He received his Ph.D. degree in Computer Science from the University of Illinois at Urbana-Champaign in 2014. He is a recipient of the Yahoo! Academic Career Enhancement Award\, NSF CAREER Award\, Simons Berkeley Research Fellowship\, Adobe Data Science Research Award\, Salesforce Deep Learning Research Award and AWS Machine Learning Research Award.
URL:https://idre.ucla.edu/calendar-event/covid-19-forecasts
LOCATION:Zoom
CATEGORIES:Classes and Workshops,Conferences and Seminars,Presentations,UCLA event
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20200526T090000
DTEND;TZID=America/Los_Angeles:20200526T120000
DTSTAMP:20260514T053057
CREATED:20200417T175632Z
LAST-MODIFIED:20200422T023530Z
UID:16555-1590483600-1590494400@idre.ucla.edu
SUMMARY:Talk: "Power and Sample Size" with Stata Corp's Chuck Huber
DESCRIPTION:In this talk\, I introduce the concepts and jargon of power and sample size calculations such as alpha levels\, power\, and minimum detectable effect sizes.  I do several simple calculations manually and then demonstrate how to replicate these calculations using Stata’s -power- commands.  Next\, I demonstrate how to create tables and graphs for power\, sample size\, and minimum detectable effect sizes for a range of values. We will conclude with a discussion of strategies to increase statistical power. \nThe second part of the talk demonstrates how to calculate power using simulation methods and how to create your own custom power calculation programs that leverage Stata’s -power- command to create custom tables and graphs.  We will work examples that simulate power for a t-test\, the interaction term in a linear regression model\, and the interaction term in a multilevel model.  Along the way you will learn how to create simulated datasets\, use Stata’s -simulate- command\, and how to write your own Stata commands using -program- and -syntax-. \nThe information for the Zoom meeting will be sent out the day before the presentation.
URL:https://idre.ucla.edu/calendar-event/talk-power-and-sample-size-with-stata-corps-chuck-huber
LOCATION:Zoom
CATEGORIES:Classes and Workshops,Education and Training,Presentations
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END:VCALENDAR