Enjoy! And stay at home... Connie
Wednesday, March 18, 2020
Saturday, March 7, 2020
Tuesday, March 3, 2020
Student Research Conference Registration
Registration for the Student Research Conference (SRC) is NOW OPEN until March 6. The first 200 registrants will receive a free SRC reusable straw and portable container! To apply, you need only an abstract, a faculty mentor, and an idea of your availability on April 16, the day of the SRC. Submit your abstract online.
All students who register for the conference will be accepted to participate, and with faculty and some prospective employers present, it will be an excellent chance to hone presentation and networking skills. Research conducted in 200-level courses can also be presented if it is independent of the professor, making this an opportunity to highlight the impactful research being conducted in the humanities and social sciences. If a student has not completed their research, they are still able to present.
The SRC is attended by members of the UVM and greater Burlington community, and it spotlights hundreds of students sharing their original work with fellow presenters and attendees. Taking over the fourth floor of the Davis Center, the SRC gives visitors the opportunity to explore the creative lounge, which has been home to creative works including music, film, and virtual reality simulations. Students with poster presentations will fill the Grand Maple Ballroom, where conference attendees will be able to speak directly to student researchers about their scholarship while building connections. If you choose to share your original scholarship through an oral or paper presentations, those will be scheduled throughout the day in conference rooms in the Davis Center. The SRC schedule will be posted in mid-March.
All students who register for the conference will be accepted to participate, and with faculty and some prospective employers present, it will be an excellent chance to hone presentation and networking skills. Research conducted in 200-level courses can also be presented if it is independent of the professor, making this an opportunity to highlight the impactful research being conducted in the humanities and social sciences. If a student has not completed their research, they are still able to present.
The SRC is attended by members of the UVM and greater Burlington community, and it spotlights hundreds of students sharing their original work with fellow presenters and attendees. Taking over the fourth floor of the Davis Center, the SRC gives visitors the opportunity to explore the creative lounge, which has been home to creative works including music, film, and virtual reality simulations. Students with poster presentations will fill the Grand Maple Ballroom, where conference attendees will be able to speak directly to student researchers about their scholarship while building connections. If you choose to share your original scholarship through an oral or paper presentations, those will be scheduled throughout the day in conference rooms in the Davis Center. The SRC schedule will be posted in mid-March.
Thursday, February 27, 2020
Burlington puts more data online
New Data Tools for Public, City Savings Identified
Brian Lowe,
brian@burlingtonvt.gov
Chief Innovation Officer, Burlington
Improved Data Tools for Public, City Team
Good data management for an organization is becoming nearly as important as strong financial management. Having easy access to the different types of data the City collects can help researchers, businesses, and community members advance their work or get a better understanding of how the City is operating. And, having readily accessible data collected by multiple departments can also help City staff get information for grant applications, policy decisions, required reports, or operational evaluations that might not be accessed easily even within the City. With more than a dozen different departments and sometimes different legacy IT systems, the Mayor has requested centralized data platforms that increase opportunities for collaboration and should save City resources over time.
Good data management for an organization is becoming nearly as important as strong financial management. Having easy access to the different types of data the City collects can help researchers, businesses, and community members advance their work or get a better understanding of how the City is operating. And, having readily accessible data collected by multiple departments can also help City staff get information for grant applications, policy decisions, required reports, or operational evaluations that might not be accessed easily even within the City. With more than a dozen different departments and sometimes different legacy IT systems, the Mayor has requested centralized data platforms that increase opportunities for collaboration and should save City resources over time.
These
factors drove the development of a new interactive dashboard,
overhauled open data platform, and the first City open data policy the
City Innovation & Technology (I&T) department released at the
end of January. The dashboard shows City performance measures over time,
and allows residents to look at particular time periods or specific
data types by clicking on the various elements of the dashboard. The
open data portal provides foundational City data sets in a machine
readable format and in a way that can be easily exported or analyzed by
the public. Carolyn Felix led this work for the I&T team. You can
access the dashboard at https://www.burlingtonvt.gov/
Tuesday, February 25, 2020
Fwd: "Automatic self-configurable machine learning to enable `small-data' science for non-experts" job talk Thursday noon
Please join us for our third tenure-track faculty job talk Thursday noon, the position focus is on Data Science in the Department of Computer Science.
University of Vermont
Thurs Feb 27, 12 - 1pm, John Dewey Lounge (325 Old Mill)
Sandwiches and drinks to be served.
Automatic self-configurable machine learning
to enable "small-data" science for non-experts
The dramatic rise and popularity of machine learning, and especially deep learning, has accelerated automation, innovation, and scale in the many industries that seek to monetize "big data". In other domains, such as in academia, the adoption of deep learning has been tempered, limited largely by the scarcity of experienced data scientists and the lack of large labeled datasets. I conjecture that the development of machine learning methods that are increasingly robust and self-configurable will help to remove the hard-earned machine-learning expertise and intuition that is currently required to configure deep learning architectures, hyperparameters, and data-processing pipelines – helping to open the use of these techniques to non-machine-learning-experts. These automatic machine learning (AutoML) pipelines often rely on meta-learning – which employs a machine learning process to automatically configure other machine learning processes (i.e. learning how to learn). In this talk, I will demonstrate a meta-learning technique that is robust to the ordering of data fed into the model (enabling online continual learning) and automatically adjusts hyperparameters such as effective learning rates with unprecedented granularity. I'll further show how this technique enables "small data" or few-shot learning – successfully training a deep neural network on just 15 examples of never-before-seen classes. Finally, I'll give examples of how deep learning can impact and accelerate fields like environmental science and medicine across the UVM campus, and explore other ongoing and potential areas of future work in both theoretical and applied AutoML.
Bio: Nick Cheney is a Research Assistant Professor of Computer Science at the University of Vermont. He directs the UVM Neurobotics Lab, is a core faculty in the Vermont Complex Systems Center, an Affiliate of the Gund Institute for Environment, and a Participating Faculty in the Quantitative and Evolutionary STEM Traineeship (QuEST). Nick earned a PhD in Computational Biology from Cornell University – co-advised by Hod Lipson and Steve Strogratz – following a BS in Mathematics from the University of Vermont. He has held visiting researcher and faculty positions at Columbia University, NASA Ames, the Santa Fe Institute, and the University of Wyoming. Nick's research in machine learning focuses on multi-scale learning-to-learn processes (meta-learning) and automatic machine learning (AutoML) to design self-configurable and robust machine learning pipelines for a wide range of applications. Nick's work has also won numerous awards for scientific visualization and public communication, and been featured in popular media venues such as Wired, Popular Science, The New Yorker, NBC News, and TED.
Fwd: New Release on Prevalence of Children With Developmental Disabilities
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February 25, 2020 | NHSR No. 139 |
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 | Prevalence of Children Aged 3–17 Years With Developmental Disabilities, by Urbanicity: United States, 2015–2018 About this report:This report uses data from the 2015–2018 National Health Interview Survey (NHIS) and examines the prevalence of developmental disabilities among children in both rural and urban areas as well as service utilization among children with developmental issues in both areas. Findings from this study highlight differences in the prevalence of developmental disabilities and use of services related to developmental disabilities by rural and urban residence. Keywords: attention-deficit/hyperactivity disorder, autism spectrum disorder, urban, rural, National Health Interview Survey Full Report > |
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Prevalence of Children Diagnosed With a Developmental Disability |
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More Information on NCHS Products & National Health Statistics Reports |
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Suggested Citation |
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Zablotsky B, Black LI. Prevalence of children aged 3–17 years with developmental disabilities, by urbanicity: United States, 2015–2018. National Health Statistics Reports; no 139. Hyattsville, MD: National Center for Health Statistics. 2020. |
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Friday, February 21, 2020
Fwd: Save the Date - MEPS Workshop
You are subscribed to the Mailing List for the MEPS Periodic Digest for the Agency for Healthcare Research and Quality (AHRQ). SAVE THE DATE AHRQ will be conducting a one-day hands-on MEPS-HC Data Users' Workshop in Rockville, MD, on April 14, 2020. This workshop will consist of lectures designed to provide a general overview of the Medical Expenditure Panel Survey (MEPS) https://meps.ahrq.gov/mepsweb/ along with lectures on MEPS-HC survey design, , health care utilization, expenditures, medical conditions; and statistical issues and challenges researchers face while analyzing MEPS-HC data. There will also be time allotted for the hands-on experience to participants. The participants will apply the knowledge gained from the morning lectures and work with programmers and analysts on MEPS data in the afternoon. They will learn how to identify and assemble variables to build a data file to answer their research questions. Sample SAS as well as STATA exercises will be demonstrated. Participants are asked to bring their own laptops with their choice of software preloaded on it. We will provide the digital version of the exercises (SAS & STATA) and slides to the attendees. During the Hands-on session, participants will have opportunity to talk to programmers individually for answering their specific research questions and there will be time allotted for open discussion. The workshop is offered free of charge. A full program description, registration form, and logistical information will be available at the beginning of March on the Workshops & Events page of the MEPS Web site at: http://meps.ahrq.gov/mepsweb/about_meps/workshops_events.jsp. For any other questions, please e-mail workshopinfo@ahrq.hhs.gov.
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