BEGIN:VCALENDAR
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PRODID:-//USC Big Data Health Science Center - ECPv6.15.18//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:USC Big Data Health Science Center
X-ORIGINAL-URL:https://bigdata.sc.edu
X-WR-CALDESC:Events for USC Big Data Health Science Center
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:UTC
BEGIN:STANDARD
TZOFFSETFROM:+0000
TZOFFSETTO:+0000
TZNAME:UTC
DTSTART:20210101T000000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=UTC:20220930T090000
DTEND;TZID=UTC:20220930T130000
DTSTAMP:20260403T233851
CREATED:20220818T124748Z
LAST-MODIFIED:20230804T105613Z
UID:4655-1664528400-1664542800@bigdata.sc.edu
SUMMARY:Big Data Health Science Center Annual Retreat 2022
DESCRIPTION:ePlease see the below for information about the upcoming BDHSC retreat and networking luncheon (9/30). This event is intended for BDHSC affiliates and stakeholders to gather and discuss extramurally funded research\, opportunities for collaboration\, and challenges in data acquisition. Students must seek permission prior to registering. BDHSC faculty affiliates and core members are encouraged to attend. \nRegister (in-person only) at BDHSC Annual Retreat Registration (google.com).
URL:https://bigdata.sc.edu/event/bdhsc-annual-retreat-2022/
LOCATION:Campus Room\, Capstone Hall\, 902 Barnwell St\, Columbia\, SC\, 29208\, United States
CATEGORIES:Retreats
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20221028T110000
DTEND;TZID=UTC:20221028T120000
DTSTAMP:20260403T233851
CREATED:20221012T170943Z
LAST-MODIFIED:20221012T173603Z
UID:5063-1666954800-1666958400@bigdata.sc.edu
SUMMARY:BDHSC Pilot Project Showcase
DESCRIPTION:Join us as we hear about the projects of four 2021 Big Data Health Science Center Pilot Project Recipients!\nFriday\, October 28 from 11-12pm\nIn-person: Discovery 1\, Room 140 and virtual option available\nRegistration required. Register at in-person: https://docs.google.com/forms/d/e/1FAIpQLScNdjmGrrp3u2bfyZtsGMvvV7VAJ7T7Y0FXT2qm0jSOvo2w9w/viewform?usp=sf_link\nVirtual: https://us02web.zoom.us/webinar/register/WN_znlpwqA5SKuS7277fz2lrg or by scanning the QR code below.\nLunch provided. \nDezhi Wu\, Ph.D.\, College of Engineering and Computing\nExploring Sentiment and Communication Exchange Patterns of Substance Use Disorder (SUD) Associated with Pregnant Women on Twitter Before and During COVID-19 Pandemic\nSubstance use among pregnant women is a significant public health concern. Recent studies have shown an alarming increase in substance use; however\, it is still unknown how the COVID-19 pandemic has impacted vulnerable pregnant women. We applied NLP\, text mining and machine learning techniques to extract just-in-time substance use (SU) data among pregnant women on Twitter\, and then explored their communication patterns\, risky health perceptions\, sentiment\, and maternal and fetal health outcomes. Our study findings are informative to perinatal healthcare practice and related public health policy changes. \nPeiyin Hung\, Ph.D.\, Arnold School of Public Health\nRural and Racial Disparities in Maternal Telehealth Health Care Access during the COVID-19 Pandemic.\nEnsuring equitable telehealth uptake in prenatal care is critical for the optimal outcomes of newly developed prenatal care guidelines. This study aims to quantify the trends of prenatal care via telehealth before and during the COVID-19 pandemic\, and assess the variations by maternal race\, ethnicity\, and residence. We used a statewide Medicaid claims data for Medicaid-insured women in South Carolina to assess prenatal telehealth uptake before and during the COVID-19 pandemic. Using an interrupted time series approach\, we found that prenatal care visits via telehealth uptake increased substantially at the beginning of the COVID-19 pandemic\, decreased within a few months\, but remained more prevalent than the pre-pandemic rates. This study highlights the disproportionate telehealth access among rural women and women from racial minority groups who have historically faced barriers to accessing prenatal care. \nGreg Trevors\, Ph.D.\, College of Education\nIdentifying Optimal Vaccine Promotion Messages for Vulnerable Subgroups from Large-Scale Gamified Interventions\nThe long-term goal of this project is to inform the design of subsequent digital health promotion interventions that will dynamically personalize to participants based on empirical insights gained from machine learning analyses on our large-scale digital intervention data. To accomplish these long-term goals\, the immediate objectives in this proposal are (1) identify distinct vaccine hesitancy subgroups from our prior intervention participants; and (2) identify optimal content that is associated with an increase likelihood of healthy behavioral intentions and attitudes\, including vaccine intent and confidence\, for each VH subgroup. \nChen Liang\, Ph.D.\, Arnold School of Public Health\nDeep Phenotyping individuals with PASC using a Graph representational model of S3C\nStudies found 47-87% of patients with persistent symptoms and multi-system organ dysfunction after the acute phase of COVID-19\, denoted as Post-Acute Sequela of SARS-CoV-2 infection (PASC). Leveraging a biomedical informatics and data science approach\, we will design an innovative Graph representational model on top of a multi-center clinical dataset [South Carolina COVID-19 Cohort (S3C)\, NIH/NIAID R01A127203-4S1]. Using this Graph model\, we will develop and pilot test a new semi-supervised machine-learning deep phenotyping algorithm to identify individuals with PASC and characterize their electronic phenotypes. This study will result in a clinically plausible\, interpretable\, generalizable\, and high-throughput deep phenotyping algorithm application for identifying possible PASC cases at COVID-19 recovery clinics\, supporting patient referral\, outreach\, and therapeutics development. \n 
URL:https://bigdata.sc.edu/event/bdhsc-pilot-project-showcase/
LOCATION:Room 140\, Discovery I\, 915 Greene Street\, Columbia\, SC\, 29208\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20221116T103000
DTEND;TZID=UTC:20221116T113000
DTSTAMP:20260403T233851
CREATED:20221101T120519Z
LAST-MODIFIED:20221101T121425Z
UID:5122-1668594600-1668598200@bigdata.sc.edu
SUMMARY:Alzheimer's Disease Registry Seminar
DESCRIPTION:An Overview of the South Carolina Alzheimer’s Disease Registry by Dr. Maggi Miller (USC). \nRegister at https://forms.gle/LVZDeiz1SmtNHc19A.
URL:https://bigdata.sc.edu/event/alzheimers-disease-registry-seminar/
LOCATION:Room 140\, Discovery I\, 915 Greene Street\, Columbia\, SC\, 29208\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20221207T110000
DTEND;TZID=UTC:20221207T120000
DTSTAMP:20260403T233851
CREATED:20221128T162509Z
LAST-MODIFIED:20221130T150334Z
UID:5425-1670410800-1670414400@bigdata.sc.edu
SUMMARY:Learning Individualized Treatment Rules with Many Treatments
DESCRIPTION:Please join us on December 7 for a virtual seminar “Learning Individualized Treatment Rules with Many Treatments” by Dr. Yufeng Liu\, the University of North Carolina at Chapel Hill. This seminar is hosted by our Electronic Health Records Core. \nRegistration required. Please REGISTER HERE
URL:https://bigdata.sc.edu/event/learning-individualized-treatment-rules-with-many-treatments/
LOCATION:Virtual
CATEGORIES:Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20221212
DTEND;VALUE=DATE:20221213
DTSTAMP:20260403T233851
CREATED:20221107T202330Z
LAST-MODIFIED:20221107T203002Z
UID:5141-1670803200-1670889599@bigdata.sc.edu
SUMMARY:Deadline for Abstracts Submission - 2023 Annual Big Data Health Science Conference
DESCRIPTION:The Big Data Health Science Center is seeking research and program-based abstracts for oral and poster presentations responsive to its 4th annual conference theme\, “Unlocking the Power of Big Data in Health: Translating Data Science into Program Development and Implementation”. This conference will be held in-person at the Pastides Alumni Center in Columbia\, SC on February 10-11\,2023. Accepted abstracts will be published in conference proceedings Research and program-based abstracts in the areas of infectious diseases\, AI for Sensing and Diagnosis\, EHR\, social media data\, genomics analysis\, geospatial research\, GIS\, infrastructural and capacity development\, professional development\, community/industry engagement\, academic training\, and methodological advances are desired. \nLearn more at https://www.sc-bdhs-conference.org/.
URL:https://bigdata.sc.edu/event/deadline-abstract-submission-2023bdhs-conference/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20230125T130000
DTEND;TZID=UTC:20230125T140000
DTSTAMP:20260403T233851
CREATED:20230112T155001Z
LAST-MODIFIED:20230112T161558Z
UID:5800-1674651600-1674655200@bigdata.sc.edu
SUMMARY:BDHSC Pilot Project Showcase Part 2
DESCRIPTION:Please join us for a Big Data seminar showcasing 4 of our 2021 pilot project recipients. Speakers will discuss their research questions\, data\, methods\, and future directions. This event is free and boxed lunch will be provided on a first come first served basis. Register at https://forms.gle/RoryZogDVET3FCRF9.
URL:https://bigdata.sc.edu/event/bdhsc-pilot-project-showcase-2/
LOCATION:Room 140\, Discovery I\, 915 Greene Street\, Columbia\, SC\, 29208\, United States
CATEGORIES:Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20230203
DTEND;VALUE=DATE:20230206
DTSTAMP:20260403T233851
CREATED:20221027T155606Z
LAST-MODIFIED:20230926T184831Z
UID:5118-1675382400-1675641599@bigdata.sc.edu
SUMMARY:National Big Data Health Science Student Case Competition 2023
DESCRIPTION:
URL:https://bigdata.sc.edu/event/big-data-health-science-student-case-competition-2023/
LOCATION:Virtual
CATEGORIES:Case Competition
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20230210
DTEND;VALUE=DATE:20230212
DTSTAMP:20260403T233851
CREATED:20221027T154602Z
LAST-MODIFIED:20221027T154602Z
UID:5110-1675987200-1676159999@bigdata.sc.edu
SUMMARY:National Big Data Health Science Conference 2023
DESCRIPTION:
URL:https://bigdata.sc.edu/event/national-big-data-health-science-conference-2023/
LOCATION:Pastides Alumni Center\, Columbia\, SC\, 900 Senate St\, Columbia\, SC\, 29201\, United States
CATEGORIES:Conference
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20230215
DTEND;VALUE=DATE:20230216
DTSTAMP:20260403T233851
CREATED:20221108T161241Z
LAST-MODIFIED:20221108T161241Z
UID:5173-1676419200-1676505599@bigdata.sc.edu
SUMMARY:Deadline for NIH-funded T35 Research Training Program Applications
DESCRIPTION:
URL:https://bigdata.sc.edu/event/deadline-for-nih-funded-t35-research-training-program-applications/
CATEGORIES:Training
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20230301
DTEND;VALUE=DATE:20230302
DTSTAMP:20260403T233851
CREATED:20230221T165634Z
LAST-MODIFIED:20230221T170412Z
UID:5960-1677628800-1677715199@bigdata.sc.edu
SUMMARY:Deadline for 2023 Health GIS Scholars Program
DESCRIPTION:
URL:https://bigdata.sc.edu/event/deadline-for-2023-health-gis-scholars-program/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20230322T120000
DTEND;TZID=UTC:20230322T130000
DTSTAMP:20260403T233851
CREATED:20230224T171652Z
LAST-MODIFIED:20230301T134246Z
UID:5981-1679486400-1679490000@bigdata.sc.edu
SUMMARY:An Overview of the Federal Statistical Research Data Centers
DESCRIPTION:
URL:https://bigdata.sc.edu/event/an-overview-of-the-federal-statistical-research-data-centers/
LOCATION:Zoom Webinar
CATEGORIES:Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20230414
DTEND;VALUE=DATE:20230415
DTSTAMP:20260403T233851
CREATED:20230111T013540Z
LAST-MODIFIED:20230301T134426Z
UID:5767-1681430400-1681516799@bigdata.sc.edu
SUMMARY:Deadline for 2023 Pilot Project Proposals
DESCRIPTION:University of South Carolina Big Data Health Science Center (BDHSC) is seeking proposals for the conduct and uptake of pilot research projects focusing on the Big Data analytics in addressing critical issues related to health behavior\, healthcare\, and population health. \nThe purpose of this RFP is to invite pilot project applications on the utilization of Big Data analytics in health-related research. The primary goals of this pilot project program will be to promote interdisciplinary collaboration in Big Data health science research and support meritorious applications that can leverage existing data to address critical issues related to health behavior\, clinical care\, healthcare delivery\, and population health. Interdisciplinary research that involves linking and integrating data sets from multiple sources are particularly encouraged. Existing data may include\, but are not limited to electronic health records data\, social media data\, geospatial data\, genomic data\, or artificial intelligence for sensing and diagnosis. To get more information\, please check out the full 2023 Pilot Project RFP here. \nFor questions regarding this RFP and proposal submission\, please contact Ms. Miranda Nixon at mc95@mailbox.sc.edu; 803-777-5027.
URL:https://bigdata.sc.edu/event/deadline-for-2023-pilot-project-proposals/
CATEGORIES:Request for Proposal
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20230523T110000
DTEND;TZID=UTC:20230524T173000
DTSTAMP:20260403T233851
CREATED:20230517T200142Z
LAST-MODIFIED:20230517T200634Z
UID:6219-1684839600-1684949400@bigdata.sc.edu
SUMMARY:NSF ACCESS HPC Monthly Workshop: Machine Learning and Big Data
DESCRIPTION:Research Computing and the USC Big Health Data Science Center will jointly co-host an in-person NSF ACCESS HPC Monthly Workshop on “Machine Learning and Big Data” sponsored by ACCESS and presented by the Pittsburgh Supercomputing Center.  The workshop will be held on May 23-24\, 2023\, from 11AM-5PM on May 23 and 11AM-5:30PM on May 24. \nThis workshop will focus on topics including big data analytics and machine learning with Spark\, and deep learning using Tensorflow.  This will be an IN-PERSON event hosted by various satellite sites\, there WILL NOT be a direct to desktop option for this event.  Registration is on a first come first served basis. Interested applicants must first have an ACCESS ID.  If you do not have an ACCESS ID\, please visit this page to create one: \nACCESS USER REGISTRATION \nOnce you have an ACCESS ID\, please complete the following registration page by Sunday\, May 21 at Noon Eastern time: \nEventbrite Reservation \nClassroom location and further details will be provided once your registration has been processed.
URL:https://bigdata.sc.edu/event/nsf-access-hpc-workshop-machine-learning-and-big-data/
CATEGORIES:Workshop
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20230612T100000
DTEND;TZID=UTC:20230714T160000
DTSTAMP:20260403T233851
CREATED:20230502T160745Z
LAST-MODIFIED:20230515T122505Z
UID:6147-1686564000-1689350400@bigdata.sc.edu
SUMMARY:Summer Workshops in Bioinformatics and Data Analytics
DESCRIPTION:Please use the below form to register for the workshops.\nhttps://forms.gle/2q98LD1BKtVr9b7z9
URL:https://bigdata.sc.edu/event/summer-workshops-in-bioinformatics-and-data-analytics/
CATEGORIES:Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20230830T103000
DTEND;TZID=UTC:20230830T113000
DTSTAMP:20260403T233851
CREATED:20230728T132543Z
LAST-MODIFIED:20230728T132848Z
UID:6698-1693391400-1693395000@bigdata.sc.edu
SUMMARY:Utilizing Big Spatiotemporal Data to Understand COVID and its Impact
DESCRIPTION:Utilizing Big Spatiotemporal Data to Understand COVID and its Impacts by Dr. Chaowei Phil Yang\n\nEvent Time: Wednesday August 30\, 2023 @10:30-11:30am\nEvent Address: Discovery Building\, Rm 140 (915 Greene St\, Columbia\, SC 29201)\nPlease register here.Spatiotemporal
URL:https://bigdata.sc.edu/event/utilizing-big-spatiotemporal-data-to-understand-covid-and-its-impact/
LOCATION:Room 140\, Discovery I\, 915 Greene Street\, Columbia\, SC\, 29208\, United States
CATEGORIES:Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20230929T090000
DTEND;TZID=UTC:20230929T130000
DTSTAMP:20260403T233851
CREATED:20230804T110249Z
LAST-MODIFIED:20230831T153357Z
UID:6718-1695978000-1695992400@bigdata.sc.edu
SUMMARY:Big Data Health Science Center Annual Retreat 2023
DESCRIPTION:Please join us for the 2023 BDHSC Annual Retreat. See below for full details. Please help us to get an accurate head count for food by registering here.\n\nThis retreat is geared towards faculty. Post docs and doctoral candidates welcome.
URL:https://bigdata.sc.edu/event/bdhsc-annual-retreat-2023/
LOCATION:Campus Room\, Capstone Hall\, 902 Barnwell St\, Columbia\, SC\, 29208\, United States
CATEGORIES:Retreats
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20231025T113000
DTEND;TZID=UTC:20231025T123000
DTSTAMP:20260403T233851
CREATED:20231002T184027Z
LAST-MODIFIED:20231002T184027Z
UID:7023-1698233400-1698237000@bigdata.sc.edu
SUMMARY:The Rhino Federated Computing Platform Unlocks the World's Data Silos for Collaborative Research
DESCRIPTION:Please join us for our October 25th (11:30-12:30) Big Data seminar featuring Dr. Malhar Patel\, Director of Clinical Engagement at Rhino Health. \nRegister for this free virtual event at https://us02web.zoom.us/webinar/register/WN_yYq0S83RT0693cpOXjkiig
URL:https://bigdata.sc.edu/event/the-rhino-federated-computing-platform-unlocks-the-worlds-data-silos-for-collaborative-research/
LOCATION:Virtual
CATEGORIES:Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20231129T110000
DTEND;TZID=UTC:20231129T120000
DTSTAMP:20260403T233851
CREATED:20231101T164924Z
LAST-MODIFIED:20231101T164924Z
UID:7082-1701255600-1701259200@bigdata.sc.edu
SUMMARY:Place Matters: Utility of Geospatial Data in Health Research
DESCRIPTION:Registration required. Register here. https://us02web.zoom.us/webinar/register/WN_899MmYukTsSvvV5RYkRDkg. \n \nThe increasing focus on health equity research will require projects that examine and address the geographic contexts where we live\, work\, and play. Such contexts are important drivers of health inequities given that the characteristics of neighborhoods and other spaces have been driven by historic and current structural inequities. This seminar will provide an orientation to spatial framing and methods\, including traditional and emerging spatial methodologies such as global positioning systems (GPS) and location aware technologies. \nDr. Katherine Theall is a Professor at Tulane University’s School of Public Health and Tropical Medicine\, Senior Director of the Tulane Violence Prevention Institute and Director of the Mary Amelia Center for Women’s Health Equity Research. As a social and spatial epidemiologist\, her research focuses on reducing health inequities by understanding and altering neighborhood environments and social policies in underserved populations locally\, nationally\, and internationally. She has been PI or co-PI of more than 25 federally- and privately-supported research and training awards and has a highly interdisciplinary background\, with educational and practical experience in social/spatial epidemiology and community health and prevention sciences. Her work involves close collaboration with both state and city governments as well as international partners\, where she has been involved in research\, programming\, and translational efforts to improve health equity and well-being.
URL:https://bigdata.sc.edu/event/place-matters-utility-of-geospatial-data-in-health-research/
LOCATION:Virtual
CATEGORIES:Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20231207T100000
DTEND;TZID=UTC:20231207T110000
DTSTAMP:20260403T233851
CREATED:20231128T194951Z
LAST-MODIFIED:20231128T195024Z
UID:7212-1701943200-1701946800@bigdata.sc.edu
SUMMARY:A Bayesian Machine Learning Approach for Estimating Heterogeneous Survivor Causal Effects: Applications To a Critical Care Trial
DESCRIPTION:Registration is required. Please register here.
URL:https://bigdata.sc.edu/event/a-bayesian-ml-approach-for-estimating-heterogeneous-survivor-causal-effects-applications-to-a-critical-care-trial/
LOCATION:Koger Center for the Arts\, Gallery Room\, 1051 Greene St\, Columbia\, SC\, 29201\, United States
CATEGORIES:Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20240126
DTEND;VALUE=DATE:20240129
DTSTAMP:20260403T233851
CREATED:20230926T185052Z
LAST-MODIFIED:20230926T191352Z
UID:6982-1706227200-1706486399@bigdata.sc.edu
SUMMARY:National Big Data Health Science Student Case Competition 2024
DESCRIPTION:
URL:https://bigdata.sc.edu/event/national-bdhs-student-case-competition-2024/
LOCATION:Virtual
CATEGORIES:Case Competition
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20240202
DTEND;VALUE=DATE:20240204
DTSTAMP:20260403T233851
CREATED:20230926T184702Z
LAST-MODIFIED:20231214T174224Z
UID:6969-1706832000-1707004799@bigdata.sc.edu
SUMMARY:National Big Data Health Science Conference 2024
DESCRIPTION:Funding for this conference was made possible (in part) by R13LM014347 from the National Library of Medicine. The views expressed in written conference materials or publications and by speakers and moderators do not necessarily reflect the official policies of the Department of Health and Human Services; nor does mention by trade names\, commercial practices\, or organizations imply endorsement by the U.S. Government.
URL:https://bigdata.sc.edu/event/national-bdhs-conference-2024/
LOCATION:Columbia Metropolitan Convention Center\, 1101 Lincoln St\, Columbia\, SC\, 29201\, United States
CATEGORIES:Conference
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20240301
DTEND;VALUE=DATE:20240302
DTSTAMP:20260403T233851
CREATED:20231122T202239Z
LAST-MODIFIED:20231122T202316Z
UID:7188-1709251200-1709337599@bigdata.sc.edu
SUMMARY:Deadline for Big Data Analytics Emerging Scholar Training Program for URM Undergrads in SC
DESCRIPTION:The USC Big Data Health Science Center is now accepting applications for the BDHSC’s newly funded training program\, Big Data Analytics Emerging Scholar Training Program for URM Undergrads in South Carolina (1R25AI172761-01). Please click for full details about the program\, including eligibility\, application process\, FAQ\, etc. The application deadline is March 1\, 2024.
URL:https://bigdata.sc.edu/event/deadline-for-nih-r25-e-scholar/
CATEGORIES:Training
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20240314
DTEND;VALUE=DATE:20240315
DTSTAMP:20260403T233851
CREATED:20240206T200522Z
LAST-MODIFIED:20240206T200522Z
UID:7353-1710374400-1710460799@bigdata.sc.edu
SUMMARY:Deadline for Big Data Health Science Fellow Program
DESCRIPTION:Supported by NIAID (R25AI164581-03)\, the USC Big Data Health Science Center (BDHSC) has been implementing a Big Data Health Science Fellow (“Big Data Fellow”) program since 2021. The program will recruit around 4 USC junior faculty per year and provide them with salary support (25%) to participate in the training program. Please click to see the call for applications to the 2024-2025 Big Data Health Science Fellow program. Details about program requirements\, eligibility\, and deadlines can be found in the Request for Applications. Apply by March 14\, 2024.
URL:https://bigdata.sc.edu/event/deadline-for-big-data-health-science-fellow-program/
CATEGORIES:Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20240411T150000
DTEND;TZID=UTC:20240411T160000
DTSTAMP:20260403T233851
CREATED:20240327T132136Z
LAST-MODIFIED:20240327T132136Z
UID:7756-1712847600-1712851200@bigdata.sc.edu
SUMMARY:Geospatial Modeling for Disease Vector Surveillance in Brazil and Beyond
DESCRIPTION:Please join the Big Data Health Science Center for its 37th seminar featuring Dr. Gabriel Z. Laporta from Centro Universitário FMABC.\n\nGeospatial Modeling for Disease Vector Surveillance in Brazil and Beyond\nThursday\, April 11 | 3:00-4:00pm\nDiscovery Room 259\nTo receive a link for virtual attendance\, register at https://us02web.zoom.us/webinar/register/WN_SWwAHafFQgqMbqBb7VDOpg.
URL:https://bigdata.sc.edu/event/geospatial-modeling-for-disease-vector-surveillance-in-brazil-and-beyond/
LOCATION:Discovery Room 259\, 915 Greene Street\, Columbia\, SC\, 29201\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20240731
DTEND;VALUE=DATE:20240802
DTSTAMP:20260403T233851
CREATED:20240702T182150Z
LAST-MODIFIED:20240702T182150Z
UID:8511-1722384000-1722556799@bigdata.sc.edu
SUMMARY:NSF ACCESS HPC Monthly Workshop on “Machine Learning and Big Data”
DESCRIPTION:The USC Research Computing\, Division of Information Technology\, and Big Data Health Science Center will host a remote site for the NSF ACCESS NSF ACCESS HPC Monthly Workshop on “Machine Learning and Big Data” presented by the Pittsburgh Supercomputing Center.  The workshop will be held on July 31 and August 1\, 2024\, from 11 a.m. to 5 p.m. in Room 1400 of the Innovation Center Building\, 550 Assembly Street\, Columbia\, SC 29201. This will be an in-person event hosted by various satellite sites; there WILL NOT be a direct-to-desktop option for this event. \nThis workshop will focus on topics including big data analytics\, machine learning using Spark\, and deep learning using Tensorflow. \nThe deadline to register for this event is July 26\, 2024. Interested applicants must first set up an access ID. For instructions on how to set up your ACCESS ID and register for this workshop\, please visit the “HPC Monthly Workshop: Machine Learning and Big Data” webpage at https://www.psc.edu/resources/training/hpc-workshop-big-data-july-2024/.
URL:https://bigdata.sc.edu/event/nsf-access-hpc-monthly-workshop-on-machine-learning-and-big-data/
LOCATION:Innovation Center Building Room 1400\, 550 Assembly Street\, Columbia\, SC\, 29201\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20240823T080000
DTEND;TZID=UTC:20240823T170000
DTSTAMP:20260403T233851
CREATED:20240731T174147Z
LAST-MODIFIED:20240731T174147Z
UID:8593-1724400000-1724432400@bigdata.sc.edu
SUMMARY:Deadline to apply for Community Scholar (c-Scholar) Training Program
DESCRIPTION:Read more about the c-Scholar program at https://bigdata.sc.edu/r25-c-scholar-program/  \nThe NIH Strategic Plan for Data Science suggests that a Big Data approach will uniquely advance our understanding of disease prevention\, identification\, control\, and treatment in the coming decades and will be a key to reducing national and global health disparities. Despite rapidly increased efforts in the application of Big Data and advanced data analytics for health science research\, the progress of translating Big Data research findings to effective public health and clinical practices for improved health outcomes has been slow due to many challenges. Such challenges include the limited participation of community members in Big Data health science research and a lack of effective communication between data science researchers and communities. As a multi-stakeholder effort\, health data science crosses boundaries between research and practice\, as well as between science and health policy. The involvement of and communication with members of local communities is critical to actualizing the benefits of data science research. \nTo address this critical need for community involvement in Big Data health science research\, we offer data science training and mentored hands-on research experience to a group of community scholars through the R25 Community Scholar (“c-Scholar”) program. Guided by a citizen science model\, the c-Scholar program provides structured support to four community scholars from various governmental and community organizations in South Carolina each year. Specifically\, the R25 c-Scholar program (1) identifies and recruits community members interested in participating in Big Data infectious disease research and utilizing Big Data research findings to improve the health outcomes of their communities; (2) implements a multi-module training program that provides mentoring\, curriculum-based training\, and hands-on research experience to better equip c-Scholars with necessary knowledge\, skills\, and competence for Big Data infectious disease research; and (3) trains and supports c-Scholars to promote and utilize Big Data research in their communities by developing or improving their necessary professional skills (e.g.\, health communication\, presentation of scientific findings to the public\, community outreach and engagement). \nInterested individuals should attach their resume or CV to an email expressing their interest in the program and their desire to promote and utilize Big Data infectious disease research in their community to Dr. Banky Olatosi (olatosi@mailbox.sc.edu) by close of business on August 23\, 2024. \nThe R25 Executive Committee will evaluate all applications and contact finalists for additional documentation\, including a letter from their employer or supervisor stating their approval and agreement for the applicant to participate in this one-year program. \nImportant Dates (subject to change)\nApplication deadline: August 23\, 2024\nSelection of finalists: September 2\, 2024\nFormal acceptance of offer and submission of follow up documentation: September 9\, 2024\nProgram start: October 8\, 2024
URL:https://bigdata.sc.edu/event/deadline-to-apply-for-community-scholar-c-scholar-training-program/
CATEGORIES:Request for Proposal,Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20240927T090000
DTEND;TZID=UTC:20240927T130000
DTSTAMP:20260403T233851
CREATED:20240829T142901Z
LAST-MODIFIED:20240910T153513Z
UID:8629-1727427600-1727442000@bigdata.sc.edu
SUMMARY:Big Data Health Science Center 2024 Retreat
DESCRIPTION:Please join us for the 2024 BDHSC Annual Retreat \nFriday\, September 27\n9am-1pm (with a networking luncheon from 12-1pm)\nCampus Room\, Capstone Building\, USC Columbia Campus \n\nConnect with USC leadership and representatives from government agencies and community partners\nIdentify opportunities for collaboration with faculty engaged in Big Data research\nNetwork via round table discussions and a networking luncheon\n\nThis retreat is intended for USC faculty. Postdocs and doctoral candidates must receive prior approval from BDHSC before registering. Email Miranda Nixon at mc95@mailbox.sc.edu with inquiries. \nRegistration required. Register today at https://forms.gle/h9X2h9grdL1UqhCz8  \n \n 
URL:https://bigdata.sc.edu/event/big-data-health-science-center-2024-retreat/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20241009T100000
DTEND;TZID=UTC:20241009T110000
DTSTAMP:20260403T233852
CREATED:20241014T194707Z
LAST-MODIFIED:20241014T194707Z
UID:8739-1728468000-1728471600@bigdata.sc.edu
SUMMARY:Vector-Borne Diseases in Colombia: Current Situation of Dengue Fever and Chagas Disease and the Potential use of Big Data in the Solution of these Problems
DESCRIPTION:Vector-Borne Diseases in Colombia: Current Situation of Dengue Fever and Chagas Disease and the Potential use of Big Data in the Solution of these Problems \nDr. Omar Cantillo-Barraza\,\nInstitute of Biology\, Biology and Infectious Disease Control Laboratory\, University of Antioquia \nOctober 9 | 10-11am\nDiscovery Building Rm 331 (915 Greene St)\nThis seminar will be conducted in a hybrid format\, with in-person attendance encouraged. Online attendance via Teams
URL:https://bigdata.sc.edu/event/vector-borne-diseases-in-colombia-current-situation-of-dengue-fever-and-chagas-disease-and-the-potential-use-of-big-data-in-the-solution-of-these-problems/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20241129T170000
DTEND;TZID=UTC:20241129T170000
DTSTAMP:20260403T233852
CREATED:20241014T195108Z
LAST-MODIFIED:20241014T200042Z
UID:8743-1732899600-1732899600@bigdata.sc.edu
SUMMARY:2025 National Big Data Health Science Conference Abstract Submission Deadline
DESCRIPTION:Abstract Submissions Deadline\n2025 National Big Data Health Science Conference\nFebruary 13-14\, 2025\, Columbia\, SC \nThe University of South Carolina Big Data Health Science Center invites you to submit abstracts for oral and poster presentations at the 6th National Big Data Health Science Conference\, to be held February 13-14\, 2025\, in Columbia\, SC. \nAbstracts may be submitted for\, \n\nIn-Person Poster Presentations\nDelegates will hang their poster in the poster hall during a designated hour and engage in Q&A with an in-person audience. Delegates will also have the option to participate in the virtual poster hall on the conference app\, Whova to boost engagement for their poster.\nVirtual Poster Presentations\nDelegates will upload their poster and an optional video presentation to the conference app\, Whova. This option is intended for individuals who cannot travel to this in-person conference.\n15-Minute Oral Presentations\nDelegates will have 15 minutes to present their abstract in a relevant breakout session.\n\nAbstracts must be responsive to the theme “Unlocking the Power of Big Data in Health: Transforming Data into Actionable Intelligence.” Abstracts may be research- or program-based\, regardless of presentation format. \nResearch-based abstracts describe empirical studies or methodological studies. They may focus on data or data analytics in the following areas\, among others: Big Data analytics and emerging methodologies; Big Data policy\, ethics\, cyber infrastructure and cybersecurity; Big Data for public health and community health; Big Data for biomedical research; Big Data for clinical practice and patient care; Other   \nProgram-based abstracts must describe problems or lessons learned from program development and implementation or policy issues related to Big Data analytics and their application in health science research in the following areas\, among others: Infrastructure and capacity development; Professional development; Community/industry engagement; Academic training; Policy\, law and regulation; Other   \nAuthors will have the option of publishing their abstract in the 2025 Conference Proceedings (with Biomedical Central\, a part of Springer Nature) at no cost. The deadline for submission is November 29th\, 2024\, by COB. \nVisit https://www.sc-bdhs-conference.org/ for more information \n \n 
URL:https://bigdata.sc.edu/event/2025-national-big-data-health-science-conference-abstract-submission-deadline/
CATEGORIES:Conference
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20250207T080000
DTEND;TZID=UTC:20250209T170000
DTSTAMP:20260403T233852
CREATED:20241014T195322Z
LAST-MODIFIED:20241014T200054Z
UID:8747-1738915200-1739120400@bigdata.sc.edu
SUMMARY:2025 National Big Data Health Science Student Case Competition
DESCRIPTION:
URL:https://bigdata.sc.edu/event/2025-national-big-data-health-science-student-case-competition/
CATEGORIES:Case Competition
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END:VCALENDAR