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2020 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 2020) from the 16 states that comprise the South Big Data Regional Innovation Hub (South BD Hub).

2020 Fellows

Dr. Elie Alhajjar is a research scientist at the Army Cyber Institute (ACI) and an Assistant Professor in the Department of Mathematical Sciences at the United States Military Academy (USMA) in West Point, NY, where he teaches and mentors cadets from all academic disciplines. His research interests include mathematical modeling, machine learning and network analysis. He has presented his research work in international meetings in North America, Europe, and Asia. Before coming to West Point, Dr. Elie Alhajjar had a research appointment at the National Institute of Standards and Technology (NIST) in Gaithersburg, MD. He holds a Master of Science and a PhD in mathematics from George Mason University, as well as master’s and bachelor’s degrees from Notre Dame University.

Jasper Johnson is a doctoral candidate at the University of Minnesota. With an undergraduate degree in political science and Master’s in Geographic Information Science, his doctoral research revolves around machine learning. His academic studies involve convolutional neural network model attention interpretability for remote sensing, deployment on large datasets, and neuromorphic model development. Jasper notes that “It has been exciting and interesting to be in such a fast-moving field. Some of my favorite parts of the PEPI-G program so far have been the critical evaluation of proposed machine learning models, and envisioning policy/strategy related to machine learning. It’s been rewarding to deal with the real-world, applied side of machine learning.”

Lindsay Rand is a doctoral student at the University of Maryland School of Public Policy. Rand has a BA in physics and an MS in nuclear physics. Her previous work includes research experience at the Laboratory for Atmospheric and Space Physics and the Carderock Naval Research Center. Rand’s current research is focused on nuclear and quantum technology governance; she began improving her policy skill base because she believes that policies related to science and technology must be rooted in a working technical knowledge. With the PEPI-G fellowship, Rand is interested in applying her technical and policy backgrounds to real world challenges related to quantum technology innovation. 

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.

2020 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.
Accelerating the Pace of Big Data

Just how Big is Big Data? It’s difficult to wrap our heads around it. We now carry in our pockets computers (a.k.a. smartphones) that have 1 million times more memory than NASA’s Apollo Guidance Computer, which was used to land the first human beings on the moon. The world’s most powerful supercomputer is the Summit housed at the Oakridge National Laboratory. It can perform 200 quadrillion (1 x 1015) calculations per second. 

It’s an indescribable number, somewhere between the number of ants alive on earth at one time and the number of grains of sand on earth. Suffice it to say, today’s researchers have some freakin’ amazing computer power at their disposal.

The truth, however, is that many scientific fields have yet to realize the potential of Big Data. That’s where the National Science Foundation’s (NSF) Big Idea, Harnessing the Data Revolution (HDR), comes in. This $30 million initiative is among 10 Big Ideas identified by NSF in 2017. Projects funded by this initiative are doing everything from improving our chances of detecting dark matter to resolving the tree of life

Coordinating the building of a national data infrastructure, sharing best practices and identifying gaps that need to be addressed by the community is no small effort. In April, 160 researchers — all of whom are Principal Investigators on HDR-funded projects — gathered online for the KI-facilitated 2020 HDR All-hands Meeting. Organizers from the NSF Big Data Innovation Hubs converted the meeting, originally scheduled to take place in the Washington, D.C. area, to a virtual event due to the COVID-19 pandemic.

“We want this to be a connected ecosystem so that results and findings and expertise that are generated in one project really can be circulated and built upon,” says Renata Rawlings-Goss, Ph.D., Executive Director of the South Big Data Innovation Hub (SouthBDHub), one of four regional Hubs across the country. “This meeting was about identifying projects, community building and forming collaborations — especially among those from disciplines that don’t normally work together.”

Tufts University’s Lenore Cowen, Ph.D., was impressed by the number of collaborators she was able to meet at the virtual meeting. “We are already pursuing some of these collaborations and others we are just beginning to follow-up on as the semester ends, summer begins and we have more time to talk further,” says Cowen, Professor of Computer Science and Director of T-Tripods.

Given the fairly recent start of the HDR Big Idea, Cowen says it was important not to cancel this meeting. “This is very new territory and the community got a lot out of it.”

The University of Utah’s Chris Meyers, Ph.D., says the meeting was perhaps even better virtual than in-person. “It was very seamless to move from discussions. The KIStorm software was great. I plan to use this as a model for future virtual meetings,” says Meyers, who is a Professor of Electrical and Computer Engineering.

Anastasios Sidiropoulos, Ph.D., agreed. “I was hoping to meet new colleagues, exchange ideas, and learn interesting research directions that the HDR projects are pursuing. My expectations were met fully,” says Sidiropoulos, an Associate Professor of Computer Science at the University of Illinois, Chicago. “I think virtual meetings like this are the future of scientific discourse.”

By Camille Mojica Rey, PhD, Science Communications Director, Knowinnovation

Using a Virtual Ecological Research Assistant (VERA) to explain the impact of social distancing

COVID-19 continues to spread across the country and around the world. The current strategy for managing the spread of COVID-19 is social distancing, and a new white paper from Georgia Tech applies the use of an interactive Artificial Intelligence (AI) tool to conceptualize the impact of social distancing on the spread of COVID-19.

Funded with a South Big Data Hub SPOKE grant, the Virtual Ecological Research Assistant (VERA) is web application that enables users to construct conceptual models of ecological systems, and run interactive simulations of these models. This allows users to explore ecological systems and perform “what if” experiments to either explain an existing ecological system or attempt to predict the outcome of future changes to one.

Researchers using VERA have now documented utilizing the tool to develop develop a SIR model for the spread of COVID-19 and its relationship with healthcare capacity.

Read the full white paper here.