In the week of July 29-Aug 2, 2019, more than 50 faculty and students from more 21 institutions participated in two R bootcamps at the University of Tennessee at Chattanooga (UTC), supported by the NSF Big Data Spoke award, Integrating Biological Big Data Research into Student Training and Education. The first bootcamp on data wrangling using R was taught by Hong Qin, a computational biologist at UTC. Materials for this R Data Wrangling bootcamp is available at a public GitHub repository https://tinyurl.com/UTC-R-camps2019. The second bootcamp, Electronic Health Records, was taught by Elvena Fong and Zhuqi Miao from the Center for Health Systems Innovation at the Oklahoma State University.
From May 27 to August 5, 2019, a group of 12 students participated in a 10-week Interdisciplinary Computing for Biological Research REU program at the University of Tennessee at Chattanooga. These undergraduate researchers are from Fisk University, Tuskegee University, Morehouse College, Norfolk State University, University of Virgin Islands, Tennessee Technological University, Rhodes College, Shippensburg University of Pennsylvania, the University of Tennessee at Chattanooga. The majors of these students include 3 Mathematics, 2 Chemical Engineering, 3 Biology, 1 Biochemistry, 2 Computer Science, and 1 Computer Engineering. The iCompBio19 includes a total of 8 faculty mentors 2019 that come from Computer Science, Mathematics, Biology, Geology, and Chemical Engineering.
All students presented their REU research results at a poster symposium on July 31.
The Program to Empower Partnerships with Industry and Government (PEPI-G) supports faculty members, research scientists, postdocs, and graduate and undergraduate students (rising juniors and seniors as of 2019) from the 16 states that comprise the South Big Data Regional Innovation Hub (South BD Hub).
James Stevenson is an undergraduate student at Northern Kentucky University and is currently pursuing his degree in Information Technology with his focus being Cybersecurity. He’s a technologist at heart and enjoys everything related to cyberinfrastructure, social cybersecurity, the internet of things, and data manipulation. His goals for his senior year of college are to gain professional experience in his career field and to develop his technical skills. This fellowship provided by the Big South Data Hub will allow him to reach these goals.
Rachel St Clair is a doctoral student at Florida Atlantic University studying Complex Systems and Brain Sciences. Rachel’s main focus centers in multi-modal, translational machine learning in complex systems and brain sciences. Her background in both medicine and biology helps structure the integration of machine learning models for both academia and industry applications. Previous work involves a variety of research fields including mental disorder diagnosis, epileptic mice investigations, and synthetic drug detection. Drawing from interdisciplinary experiences drives her current integrative research in deep learning proteomics, computer vision, and therapeutic XR platforms. Her future accomplishments aim to include advancements in advanced machine perception and general AI. Rachel notes, ‘working with others who care deeply for the evolution of computerized cognitive task and their role in making the world a safer place would be a defining historical moment in my career path’.
The Department of Homeland Security – Advanced Research Projects Agency (DHS-ARPA) DA-E lab infrastructure consists of industry-standard servers and network gear, custom appliances built on the premise, and commercial and private cloud capabilities.
DHS’ identified Priority Areas:
Human Trafficking – Examining social media to aid in the fight against human trafficking focusing on Non-Text Data, Automating Search and Scalability
Real-time Analytics for Multi-party, Metro-scale Networks (RAMMMNets) – Data associated with the Internet-of-Things presents challenges to the analytic environments that inform human decision making.
Other Topics – Faculty fellows may propose other research topics for consideration.
Call for Participants: NSF fundedMultidisciplinary Online Training Program with Stipend Support in Spring 2019on Big Data + High-Performance Computing + Atmospheric Sciences
Funded as an NSF grant to train graduate students, post-docs, and junior faculty on “Big Data + High-Performance Computing + Atmospheric Sciences”, our training program is a new NSF-funded initiative in big data applied to atmospheric sciences and using high-performance computing as a vital tool. The training consists of instruction in the areas of data, computing, and atmospheric sciences supported by teaching assistants, followed by faculty-guided project research in a multidisciplinary team of participants from each area. Participants around the nation will be exposed to multidisciplinary research experiences and have the opportunity for significant career growth. Continue reading →
Faculty teams from the DataUp program during the Instructor Training Workshop on Nov 6 & 7, 2018.
Society is increasingly becoming more data-driven and data-literate. It is vital every institution has the capabilities and infrastructure to engage and develop learners prepared to interact and succeed in such a society. Numerous studies have identified the expanding data divide between institution types and the need to develop successful bridge initiatives. The South Hub begin to address this need by creating a 3-part program, DataUp. Through this program, the South Hub is directly impacting each participating institution’s data science education capacities.
The first component of the program is a hosted 2-day data or software workshop presented by the Carpentries. This provided an opportunity for each participating institution to engage in a workshop that specifically addressed their data knowledge gaps (for more information on these workshops, Click Here). Exposing students to these intensive workshops, students are able to gain hands-on training and exposure to principles and tools, such as shell and JupyterHub. Removing the associated ‘fear factors’ empowers learners to employ and address challenges with data. The second component of the DataUp program is a 2-day pedagogy intensive instructor training.
RTI’s Kristina Brunelle (left) moderates a panel discussion with Amy Roussel, RTI (center); Gracie Johnson-Lopez, Diversity and HR Solutions (right); and Sackeena Gordon-Jones, Transformation Edge and NC State University (on screen).
Data science is hot. That’s good news for workers with data science skills. It also means organizations competing to hire data scientists need to understand how to recruit talent that will solve their data science challenges and contribute to creating a productive and diverse workforce. Continue reading →
As organizational and societal decisions become more data-driven academic institutions, industry, and government officials continuously identify data literacy as an important skillset for individuals currently in and entering the workforce. Unfortunately, a dearth of qualified data literate employees exists producing a need for effective data science education and training for undergraduates. Continue reading →
Top Left: The South Hub SNAP award recipients with the Co-Executive Director, Renata-Rawlings Goss and an organizer of the Young CEOs Business Summit. Top Right: South Hub SNAP award recipients, Abdoulaye Gueye, Favour Ori, and Sylvester Ogbonda, pose with their awards during the Young CEOs Business Summit Awards Banquet. (R) The South Hub SNAP award recipients with the Co-Executive Director, Renata-Rawlings Goss, organizers of the Young CEOs Business Summit, and presenters.
The South Hub continually identifies opportunities to expose students and professionals to data science. For example, the South Hub awarded five student’s registration fellowships through the SNAP-DS program, “Stimulating New Activities and Projects in Data Science,” to attend the Young CEOs Business Summit’s (YCBS) 2018 Annual Summit in Atlanta. The South Hub developed the SNAP-DS program to provide travel support, student stipends, or registration fellowships for students to attend data-related workshops, conferences, and projects, such as the Young CEO’s Business Summit, that expose students to data science and the ways data science can better societies and businesses. Continue reading →
Participants in the international big data workshop in Versailles, France, take a break for a group photo.
In November 2017, the National Science Foundation’s Big Data Innovation Hubs sponsored a workshop in Versailles, France to discuss the formation of public-private partnerships in big data research among institutions in the United States and the European Union. Organized in conjunction with the Big Data Value Association, the PICASSO Project, and Inria, the workshop was the first of its kind to bring together international big data experts representing government, industry, and academia. Continue reading →
Earlier this year, the South Big Data Hub partnered with Microsoft Research to offer researchers in the South Hub region the opportunity to apply for cloud credits on Azure, the comprehensive cloud services platform offered through Microsoft. The opportunity was designed to provide cloud computing resources to support data-intensive research projects.
NSF’s Wendy Nilsen speaking at a South Big Data Hub Roundtable.
Each day countless devices—from monitors in hospitals to diagnostic tests to Fitbits—capture huge amounts of health data. That data could change how patients and doctors interact, how diseases are diagnosed and treated, and the amount of control individuals have over their health outcomes.
The data is plentiful, Nilsen acknowledged. The challenge, she said, is how to make that data easier to use, how to standardize it so it can be analyzed, how to scale it, keep it safe, and how to account for external factors such as the environment or a person’s genome.
Nilsen discussed these challenges and how to address them in a roundtable discussion hosted by the South Big Data Hub on October 14. Nilsen’s talk, titled “Smart Health and Our Future” provides an overview of the challenges that must be addressed as well as the ultimate goal: A system where patients use data to take more control of their health and where healthcare practitioners can use data from multiple sources to improve diagnoses and health outcomes.