Upcoming Events

Roots CoLab: Create A Website: Styling (Intro To CSS)

Monday, Oct 18, 2021  5pm-7pm
Enroll at https://colab.duke.edu/roots/course/css-intro#enroll

So you have created an HTML file, and it holds all your content, but it’s lacking inspiration. It is time to add color to your world! In this second class in our Create a Website series, we are introducing a new language: CSS. CSS is the styling language for the web and it can make “most” of our web styling related dreams come true! With that said, CSS is a vast language with loads of possibilities and just like with everything, we must start small to one day go big. This class is geared towards CSS beginners, who have done some HTML work in the past. If you have never touched HTML before, we recommend you first take the Create a Website: Structure class to get all caught up. In this class, you will learn the basics of CSS, the styling language of the web. We will explore CSS usage, its syntax and best practices when it comes to CSS file setups. We will also look into key features of CSS such as the cascading model, and the specificity model. Finally we will put all that into practice by styling a simple web page using Codepen.io

Instructor:
Sandra Bermond | Innovation Co-Lab Program Manager
Sandra manages the Innovation Co-Lab roots program as well as teaches several workshops. She has a background in web design and front-end development, as well as a passion for artistic endeavors regardless of the medium.

This class is part of our Web Development (Front End) Track

+DS vLE: Break it, fix it, trash it, change it, plot, update it

Tuesday, Oct 19, 2021  4pm-5pm
Register here: https://duke.zoom.us/webinar/register/WN_Q0S5WK4_Sz-1ZA0-CGERUA

Presented by: Mine Çetinkaya-Rundel

In this session, we will work on a data visualization makeover exercise. We will start with a plot that would benefit from a thorough makeover and update it, step-by-step, using the ggplot2 package in R as well as a few other packages that play nicely with ggplot2. Along the way, we will discuss how each version of the plot improves on the previous one and why it can benefit from further improvement. The session will feature live coding and audience participation. Coding-along is encouraged, however those who would just like to watch and/or contribute ideas in the chat for improvements are equally welcome! Basic familiarity with R and ggplot2 will be helpful, however the only requirement for participation is a browser and a stable internet connection.

This session is part of the Duke+DataScience (+DS) program virtual learning experiences (vLEs). To learn more, please visit https://plus.datascience.duke.edu

+DS vLE: Simulation-based machine learning for computational microscopy

Wednesday, Oct 20, 2021  4pm-5pm
Register here: https://duke.zoom.us/webinar/register/WN_fMx6M-ddR5udN7DEF2A_8g

Presented by Srinivas Turaga, PhD;
Computation & Theory, HHMI Janelia Research Campus

Supervised machine learning is a well-established paradigm for training deep neural networks. However, there are many settings where it is challenging or impossible to collect ground truth data for supervised learning. In this session, Dr. Srinivas Turaga will describe how to use the framework of auto-encoders and combine differentiable physics-based simulations with deep networks to solve two problems in computational microscopy.

 

1. Single molecule localization microscopy is fluorescence based super-resolution microscopy technique. Dr. Turaga will explain how a biophysically realistic simulation of such microscopy data, along with the appropriate neural network architecture, and a new spatial point process based loss function can enable exciting new capabilities for such microscopy.

Speiser, Muller, et al, “Deep learning enables fast and dense single-molecule localization with high accuracy”, Nature Methods 2021.

 

2. Programmable microscopy is enabled by newly available programmable optical elements. Such microscopes offer the possibility of optimizing the imaging process to the biological specimen to achieve the best possible trade off of spatial resolution, temporal resolution, and signal to noise. Dr. Turaga will show how to build a differentiable wave-optics simulation of a programmable microscope, and to combine it with a new neural network architecture to engineer microscope parameters for fast 3D snapshot microscopy of whole brain neural activity in larval zebrafish.

Deb et al, “Programmable 3D snapshot microscopy with Fourier convolutional networks”, arxiv 2021.

This session is part of the Duke+DataScience (+DS) program virtual learning experiences (vLEs). To learn more, please visit https://plus.datascience.duke.edu

CDVS: Intro to Gephi for Network Visualization

Thursday, Oct 21, 2021 10am-12pm
Register at https://duke.libcal.com/event/8064664

Networks (or graphs) are a compelling way of studying relationships between people, places, object, ideas, etc. Generating network data and visualizations, however, can be an involved and unintuitive process requiring specialized tools. This workshop will explore some of the easier ways to produce, load, and visualize network data using Gephi, an open source, multi-platform network analysis and visualization application.

Presented by the Duke Center for Visualization Services (CDVS)

Roots CoLab: SQL – Beyond The Basics (1 of 3)

Thursday, Oct 21, 2021  1pm-3pm
Enroll at https://colab.duke.edu/roots/course/advanced-sql1#enroll

This course will provide an introduction to intermediate SQL concepts, including data manipulation with built-in arithmetic and date functions, set operations, and nested queries. The skills gained in this course will allow users to answer a variety of questions about their data.

Instructor
Mary Clair Thompson | Office of Information Technology
I am a Data Engineer and Data Scientist on OIT’s Data Analytics team, with previous industry experience working with big data in the cloud.

This class will be hosted via Zoom. You will receive an email with the Zoom link a day before the class. Attendance will be taken and the session will be recorded.

This class is part of our Databases Track

Roots CoLab: Create A Website: Layouts (Responsive CSS)

Monday, Oct 25, 2021  5pm-7pm
Enroll at https://colab.duke.edu/roots/course/css-layout#enroll

You are getting the hang of those basic CSS rules, and even though your site is starting to look good, you feel like you could do more. If this is you, then this class is for you. We will not be diving into completely uncharted territory, but we will build upon what was done in the Create a Website: Styling workshop. In this class, we will talk about why responsiveness is the way to design any site. We will look into the different markers that make up a responsive site, before diving into the different ways to change a layout (displays, floats, flexbox, grid). Finally we will work on a couple of exercises to get comfortable with the new concepts taught in the class. This class assumes that you have some basic knowledge of HTML and CSS.

Instructor:
Sandra Bermond | Innovation Co-Lab Program Manager
Sandra manages the Innovation Co-Lab roots program as well as teaches several workshops. She has a background in web design and front-end development, as well as a passion for artistic endeavors regardless of the medium.

This class is part of our Web Development (Front End) Track

CDVS: Advanced: Preparing Data for Publishing

Tuesday Oct 26, 2021 1pm-2:30pm
Register at https://duke.libcal.com/event/8061498

This workshop will explore strategies and best practices for sharing and publishing data to support open science, reproducibility, and future innovation. Topics covered will include the use of data and metadata standards to support interoperability and harmonization. An overview of repository options and examples of disciplinary repositories will be explored as well as methods to publish data to increase the impact of research projects. Participants will also engage in discussions regarding how academia and communities can develop policies, norms, and procedures that enable data sharing in line with the FAIR Guiding Principles (i.e., Findable, Accessible, Interoperable, and Reusable).

Presented by the Duke Center for Visualization Services (CDVS)

Roots CoLab: Singularity Containers

Wednesday, Oct 27, 2021  1pm-3pm
Enroll at https://colab.duke.edu/roots/course/singularity-containers#enroll

This workshop provides researchers in the humanities, arts, and sciences an opportunity to become familiar with containerization tools, which are in wide use in the research computing world. The workshop will introduce the tools and provide hands-on experience. Researchers with software they want to package — or “containerize” — for use on the cluster or elsewhere will be able to do so. We will introduce Gitlab-CI (https://about.gitlab.com/features/gitlab-ci-cd/) and Singularity (https://sylabs.io) and tools that OIT programmers have built to automate the production of “cluster-ready” Singularity containers. Who should take part? Users of the Duke Compute Cluster; researchers who are using software with specific and perhaps exotic library dependencies; researchers who are using computers at other locations, including XSEDE supercomputers, Open Science Grid (OSG), or computers shared with colleagues at other institutions, researchers who want to increase the likelihood that their computational methods are transportable and reproducible. Time will be available for participants to ask questions about building their own containers.

Instructor:
Mike Newton | Analyst IT, sr

This class will be hosted via Zoom. You will receive an email with the Zoom link a day before the class. Attendance will be taken and the session may be recorded.

This class is part of our Research Computing Track

Roots CoLab: SQL – Grouping, Joins, And Aggregations (2 of 3)

Thursday, Oct 28, 2021  1pm-3pm
Enroll at https://colab.duke.edu/roots/course/advanced-sql2#enroll

This course will provide an introduction to a few advanced sql concepts, including grouping and aggregations. Users will also learn the differences between the various types of joins.

Instructor
Mary Clair Thompson | Office of Information Technology
I am a Data Engineer and Data Scientist on OIT’s Data Analytics team, with previous industry experience working with big data in the cloud.

This class will be hosted via Zoom. You will receive an email with the Zoom link a day before the class. Attendance will be taken and the session will be recorded.

This class is part of our Databases Track

Roots CoLab: High Performance Computing And The Duke Compute Cluster

Tuesday, Nov 2, 2021  1pm-3pm
Enroll at https://colab.duke.edu/roots/course/hpc-dcc#enroll

The Duke Compute Cluster (DCC) is a general purpose, high performance, Linux computing cluster with software used for a broad array of scientific projects. The DCC is made up of machines that the University has provided for community use and researchers have purchased to conduct their research. This workshop will provide Duke University researchers with a brief overview of Research Computing resources including the Duke Compute Cluster. The majority of the session will be a hands on tutorial using the Duke Compute Cluster: running interactive and batch jobs, using slurm job arrays, running multi-cre and parallel jobs, and specifying job dependencies. There is time at the end for questions and help on existing jobs.

Instructor:
Tom Milledge | Analyst IT, sr

Please note: students attending this class should already have access to the DCC. For more information on the DCC, including how to obtain access, visit: rc.duke.edu This course will be online via Zoom, link will be provided to registrants the day before the session.

This class is part of our Research Computing Track

+DS vLE: Exploring Machine Learning Resources in Microsoft Azure

Tuesday, Nov 2, 2021  4pm-5pm
Register here: https://duke.zoom.us/webinar/register/WN_ggsA7201SBmPasUxoGzeHA

Presented by:
Fabricio Lopes Sanchez, Sr. Cloud Solution Architect at Microsoft

John Brown, Sr. Cloud Solution Architect at Microsoft

In this session Fabricio Lopes Sanches and John Brown, Senior Cloud Solution Architects at Microsoft, will guide you through some of the of the various possibilities in Microsoft’s cloud platform (Azure) designed to power up your machine learning projects. From a pre-built set of APIs (called Cognitive Services) to a powerful online machine learning studio (Azure ML) that allows you to build out your own models, and making them available to consumption through restful APIs, you will come to realize all the different approaches you can take out of your projects, bringing the best of the cloud into your daily work.

This session is part of the Duke+DataScience (+DS) program virtual learning experiences (vLEs). To learn more, please visit https://plus.datascience.duke.edu

Roots CoLab: Intro To R

Monday, Nov 8, 2021  1pm-3pm
Enroll at https://colab.duke.edu/roots/course/rintro#enroll

Are you interested in data visualization and data analysis? You’ve come to the right place. This workshop will cover basic setup, concepts, syntax and visualization in R, an open source programming language for statistical computing. We’ll go through a series of exercises step by step, so have no fear! 

Instructor:
Anni Yan | Innovation Co-Lab Developer & Instructor
Anni is a recent grad from Duke University, and she is working at the Co-Lab now. She is passionate about data visualization, game designs and web development. Outside of work, Anni loves to hangout with Yuki(her cat), bake and play games.

This class is part of our Research Computing Track

CDVS: Designing a Reproducible Workflow with R and GitHub

Tuesday, Nov 9, 2021 10am-12pm
Register at https://duke.libcal.com/event/8061587

Part of the Rfun series. The importance of reproducibility, replication, and transparency in the research endeavor is increasingly discussed in academia. This workshop will introduce foundational strategies that can increase the reproducibility of your work and present a potential end-to-end reproducible workflow using a suite of tools, including git, RStudio, Binder, and Zenodo. Configuration for the hands-on portion of the workshop will be sent to participants one week before the workshop. Participants are expected to bring their laptop already configured for the workshop. 

Presented by the Duke Center for Visualization Services (CDVS)

Roots CoLab: SQL – Temporary Tables And Windows (3 of 3)

Thursday, Nov 11, 2021  1pm-3pm
Enroll at https://colab.duke.edu/roots/course/advanced-sql3

This course will show students how to create and use temporary tables when constructing queries, and provide an introduction to the concept of windowing. Students will also learn how to apply bounds to their windows for advanced data analysis.

Instructor
Mary Clair Thompson | Office of Information Technology
I am a Data Engineer and Data Scientist on OIT’s Data Analytics team, with previous industry experience working with big data in the cloud.

This class will be hosted via Zoom. You will receive an email with the Zoom link a day before the class. Attendance will be taken and the session will be recorded.

This class is part of our Databases Track

Roots CoLab: Intro To Shiny

Monday, Nov 15, 2021  1pm-3pm
Enroll at https://colab.duke.edu/roots/course/shiny-intro#enroll

This series is intended to assist students and researchers (with some experience in R) migrate their important work and results from the desktop (R and RStudio) to the web.
Shiny is a package that helps you develop web pages in an R environment. Using Shiny lets people, with no knowledge of R, interact with your data, models and results on a web page. In this new series, hosted by the Innovation Co-Lab and Research Computing, learn how to interactively tell your research story and migrate your important work and results in R and RStudio to the Web.

Instructor:
Anni Yan | Innovation Co-Lab Developer & Instructor
Anni is a recent grad from Duke University, and she is working at the Co-Lab now. She is passionate about data visualization, game designs and web development. Outside of work, Anni loves to hangout with Yuki(her cat), bake and play games.

This class is part of our Research Computing Track

Roots CoLab: Data Visualization With Shiny

Monday, Nov 22, 2021  1pm-3pm
Enroll at https://colab.duke.edu/roots/course/shinyviz#enroll

Let’s say you created some really awesome interactive data viz in R, and you shared the GitHub link with your families. Your family is probably going to be really confused. Not to mention showing all the hard work you did with data manipulation and how you got the conclusion. The good news is Shiny can help you with all of this! Hopefully you’ve got some Shiny experience. If not, you should checkout the Intro to Shiny workshop at Co-Lab! Look no further, let’s go started!

Instructor:
Anni Yan | Innovation Co-Lab Developer & Instructor
Anni is a recent grad from Duke University, and she is working at the Co-Lab now. She is passionate about data visualization, game designs and web development. Outside of work, Anni loves to hangout with Yuki(her cat), bake and play games.

This class is part of our Research Computing Track

+DS vLE: Introduction to Gaussian processes for Machine Learning

Thursday, Nov 18, 2021  11am-12pm
Register here: https://duke.zoom.us/webinar/register/WN_KE7I-sLuQNmpJHnR_BcLig

In this session, Prof. Mauricio Álvarez will define a Gaussian process (GP) model and describe how it is used to tackle (non-linear) regression problems including defining the kernel function, the key function that defines the Gaussian process. He will define how we can use optimization of the marginal likelihood to estimate (hyper-)parameters in the GP model, and (time permitting) how GPs are used for pattern classification, multiple-output regression, unsupervised learning and Bayesian optimization.

Mauricio A. Álvarez, PhD. is an Associate Professor in the Department of Computer Science at The University of Sheffield in the United Kingdom.

This session is part of the Duke+DataScience (+DS) program virtual learning experiences (vLEs). To learn more, please visit https://plus.datascience.duke.edu

+DS vLE: Difficulties and Dangers in Estimating Human Pose from Video

Friday, Nov 19, 2021  12pm-1pm
Register here: https://duke.zoom.us/webinar/register/WN_bYEoMcqzSI6LMLbZFbSviw

Presented by: Helge Rhodin, PhD; Department of Computer Science; University of British Columbia

Estimating the 3D pose of a human from a single image or video is a very challenging computer vision problem since a picture contains little information on the depth. Moreover, humans move in complex ways, and their diversity in appearance and shape is immense. The recent advances in deep learning bring about new levels of accuracy, but they are prone to bias in the training sets that rarely represent the variety present in our global population. Moreover, automatic monitoring raises privacy concerns. Dr. Helge Rhodin will present personalized solutions that mitigate bias and suggest alternatives to video-based surveillance and its associated dangers.

Helge Rhodin, PhD is an Assistant Professor at the University of British Columbia, a member of the computer vision and graphics labs. His research interests range from computer graphics and augmented reality, over 3D computer vision, to machine learning. Dr. Rhodin received a BSc and MSc degree in Computer science from Saarland University. He graduated with a PhD in 2016 for is work at the Max-Planck Institute for Informatics and was a postdoctoral researcher and lecturer at EPFL.


(website: https://www.cs.ubc.ca/~rhodin/)

This session is part of the Duke+DataScience (+DS) program virtual learning experiences (vLEs). To learn more, please visit https://plus.datascience.duke.edu