Hubbub! Blog

Latest Posts

iCompBio REU and Workshop Provides Training to Students and Faculty

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). The iCompBio REU is supported by NSF Award 1852042,  REU Site: ICompBio – Engaging Undergraduates in Interdisciplinary Computing for Biological Research. 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.

For discussion on research and education in bio big data, please join a LinkedIn group at https://www.linkedin.com/groups/12279083/

Participants from the first bootcamp on data wrangling using R taught by Hong Qin, a computational biologist at the University of Tennessee at Chattanooga (UTC). The bootcamp is supported by the NSF Big Data Spoke award, Integrating Biological Big Data Research into Student Training and Education.

Participants from the second bootcamp, Electronic Health Records, taught by Elvena Fong and Zhuqi Miao from the Center for Health Systems Innovation at the Oklahoma State University. The bootcamp is supported by the NSF Big Data Spoke award, Integrating Biological Big Data Research into Student Training and Education.

Biological REU

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 12 student participants in the 10-week Interdisciplinary Computing for Biological Research REU program at the University of Tennessee at Chattanooga. The REU was supported by the NSF Big Data Spoke award, Integrating Biological Big Data Research into Student Training and Education.

The 12 student participants of the 10-week Interdisciplinary Computing for Biological Research REU program presenting their REU research results at a poster symposium on July 31. The REU was supported by the NSF Big Data Spoke award, Integrating Biological Big Data Research into Student Training and Education.

2019 PEPI-G Fellows Selected

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).

2019 Fellows

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’.

2019 Partner

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.

NSF Invests $4 Million in Big Data for Southern United States

NSF Invests $4 Million in Big Data for Southern United States

Precision medicine and understanding health disparities, innovation to power competitive manufacturing, technology for smarter communities, and addressing coastal hazards such as hurricanes are among the challenges facing the Southern United States. A $4 million award from the National Science Foundation (NSF) will help apply data science and engineering to address those challenges.

The funding will continue support for the South Big Data Innovation Hub, an organization that helps 16 Southern States and the District of Columbia identify and utilize data science and engineering to address critical societal needs. One of four NSF-supported regional data hubs in the U.S., the South Big Data Hub is managed by the Georgia Institute of Technology and the University of North Carolina at Chapel Hill.

“The Big Data Hubs provide a connective tissue for the data science ecosystem across sectors and domains,” said Renata Rawlings-Goss, the Hub’s executive director. “I am deeply pleased by NSF’s recommitment to the growth of the South Hub and our community. Over the last three years, we have made great strides within our priority areas and are looking to broaden that reach in the next four years.”

The NSF-supported data hubs play four key roles: (1) Accelerating public-private partnerships that break down barriers between industry, academia, and government, (2) Growing R&D communities that connect data scientists with domain scientists and practitioners, (3) Facilitating data sharing and shared cyber infrastructure and services, and (4) Building data science capacity for education and workforce development.

“There is a global shortage of data science and analytics talent that is threatening the future of innovation,” added Rawlings-Goss. “By working across sectors, the South Hub joins in creating solutions to increase the capacity of universities and industry to work on pressing problems for our region and for the world.”

Priorities for the hubs are determined regionally to bring together collaborators that include academics, community leaders, local and state government executives, regional businesses, national laboratories and others, explained Srinivas Aluru and Stanley Ahalt, the two principal investigators for the South Big Data Hub, which was launched in 2015.

“We want to collaborate to help solve regional problems using the resources of the Hub,” explained Aluru. “We are addressing truly regional issues that affect more than one state and more than one set of collaborators. These are challenges that can only be addressed by bringing these groups together.”

The south region is pursuing five major big data priorities:

  • Health and Disparities: High impact applications of data science in precision medicine, health analytics, and health disparities. “If you look at the health outcomes, they differ by ethnic groups. Trying to understand and address these health disparities is one of our big data challenges,” Aluru said.
  • Smart Cities and Communities: Collection and integration of data on infrastructure, sensors, and behavior to design efficient use of resources and services, and to achieve a higher quality, affordable lifestyle, as well as concrete applications of analytics and machine learning to improve the nation’s energy production and smart grid.
  • Advanced Materials and Manufacturing: Access to data infrastructure for creating new materials for advanced manufacturing in every state. “Manufacturing is very important to the Southeast, and we plan to work with the state manufacturing extension partnerships in different states, trying to inject big data techniques into materials science and manufacturing to shorten the deployment cycle,” Aluru added.
  • Environment and Coastal Hazards: Prevention and enhanced response to natural and human-induced environmental hazards. Southern states are disproportionately affected by hurricanes on both the Atlantic and Gulf Coasts. Understanding these threats and how best to protect people and property is critical.
  • Social Cybersecurity: Best practices across sectors to forecast cyber-mediated changes in human behavior to ensure private, secure, and ethical data sharing, reporting, and use. “In modern times the virtual world is a force in and of itself; we want to support transparency in how it can change interactions and social outcomes,” adds Rawlings-Goss.

The new NSF award includes seed funding designed to evaluate the feasibility of new big data projects. Part of a hub-and-spoke system, the seed money should help create new spokes to address specific data issues identified by collaborators.

“Developing innovative, effective solutions to grand challenges requires linking scientists and engineers with local communities,” said Jim Kurose, Assistant Director for Computer and Information Science and Engineering at the NSF. “The Big Data Hubs provide the glue to achieve those links, bringing together teams of data science researchers with cities, municipalities and anchor institutions.”

Ultimately, the goal is to harness the synergy of the collaborators to address issues that require the use of data science and engineering techniques.

“Data science is having a transformative effect on the entire scientific community,” said Ahalt. “The South Hub enables us to leverage data science expertise in order to have an impact for good throughout the entire southeast region.”

The South Big Data Hub is funded through the National Science Foundation’s Big Data Science & Engineering Program, Awards 1916589 and 1916454 and previously 1550305 and 1550291.