GTRI Graduate Student Research Fellowship Program Continues to Expand for Third Year
The Georgia Tech Research Institute (GTRI) solves the most pressing national security problems, from spacecraft innovations to artificial forensics, and has historically sought to partner with Georgia Tech faculty to enhance those solutions. The GTRI Graduate Student Research Fellowship Program (GSFP) is a competitive program for high-caliber Georgia Tech graduate students. Selected academic researchers and graduate students work on research that is aligned with GTRI strategic technology priorities. The GSFP fosters and cultivates long-term relationships between academic faculty and GTRI researchers to fulfill the mission of creating leaders who advance technology and improve the human condition. Find out more about the labs at GTRI.
The first eight projects in the inaugural cohort, along with the seven projects chosen last year, have been a great success. In this third year, the fellowship is expanding to include an additional seven projects that will further the research collaboration across Georgia Tech’s schools and colleges.
“We really want connectivity to manifest through research collaborations, and it’s advantageous for us to reach into the broad wealth of and depth of talent across the academic schools,” said Mark Whorton, GTRI’s chief technology officer. “From the theoretical research done on campus into the applied research we do at GTRI, we're seeking to take those great capabilities and bring applications into the national security space.”
Across the seven selected fellowship awards for the upcoming academic year, researchers from GTRI labs will co-advise students along with a Georgia Tech faculty member. This year’s projects will lead to innovations in everything from electronic warfare systems, artificial intelligence/machine learning, autonomous systems, and protein sequencing to international policy.
Faculty Research Pairs and Proposals
What: Reconfigurable Metasurfaces for High-Power Microwave Systems and Emerging EM Spectrum Operation Concepts
Who: Dr. Nima Ghalichechian, Dr. Joshua Kovitz, Walter Disharoon
Unit: School of Electrical and Computer Engineering; Advanced Concepts Laboratory (ACL)
Why It Matters: Reconfigurable metasurfaces have the potential to improve high-power microwave (HPM) systems, enabling applications such as adaptive beamforming and beam shaping, frequency tuning, and polarization timing for use in radar, communication systems, directed energy, and other electronic warfare systems. This research proposes to develop reconfigurable metasurfaces using vanadium dioxide (VO2) switch technologies for HPM systems, and demonstrate a reconfigurable reflectarray (RRA) and high-power limiter metasurface.
“Phase-change materials offer a completely new paradigm for the ubiquitous RF switch, a fundamental building block in sensor and electronic warfare systems,” said Kovitz and Ghalichechian. “As a part of this joint effort, we plan to design, fabricate, and test novel reconfigurable and high-power microwave structures based on these phase-change materials.”
What: Interactive Decision-making and Resilient Planning for Long-Horizon Collaborative Manipulation in Complex Military Environments
Who: Dr. Ye Zhao, Dr. Stephen Balakirsky, Maxwell Asselmeier
Unit: School of Mechanical Engineering; Aerospace Transportation & Advanced Systems Laboratory (ATAS)
Why It Matters: Collaborative manipulation, as a class of general-purpose autonomous systems, provides an expansive set of desirable capabilities to perform complex tasks in highly unstructured environments. These autonomous systems could operate in dangerous environments that are inaccessible to first responders, saving labor and reducing the risk to human life. This will open the opportunity of enabling human operators to focus on high-level, critical decisions.
“This fellowship will support human-robot teaming with a robot that has a high level of autonomy along with a sense of touch,” said Balakirsky. “This combination will allow a human operator to provide tasking of dexterous manipulation tasks to the robot without the burden of teleoperation or constant process monitoring. This system has wide-ranging applications from search and rescue to manufacturing.”
What: Trustworthy Edge Systems for Video Analytics: Robustness, Safety, and Resilience
Who: Dr. Ling Liu, Dr. Margaret Loper, Connor Geurin
Unit: School of Computer Science; Information and Communications Laboratory (ICL)
Why It Matters: Video as an edge Artificial Intelligence (AI) service will be a crucial component in many cyber-physical systems and applications. However, most of the video analytics today are typically done in the Cloud, which incurs overwhelming demand for bandwidth. This research is centered on developing trustworthy edge systems for video analytics, including developing the theory, algorithms, and techniques for boosting the robustness of real-time object detection. This will ensure safety and resilience against different types of disruptions and compromises.
“The proliferation of mobile computing and Internet of Things has created a paradigm that pushes computing tasks and services from the network core to the network edge,” said Loper. “Pushing AI to the edge is seen as a promising solution for processing the massive amounts of small data generated by these devices. The findings of this research could fundamentally change how AI-enhanced edge systems will be designed, developed, and deployed, and could lead to a new generation of security and safety-enhanced edge systems.”
What: Model-based Reinforcement Learning for Policy-perspective Explainable and Trusted Artificial Intelligence
Who: Dr. Sehoon Ha, Dr. Robert Wright, Morgan Byrd
Units: School of Interactive Computing; Cybersecurity, Information Protection, and Hardware Evaluation Research Laboratory (CIPHER)
Why It Matters: The emergence of capable artificial intelligence (AI) that can make sequential strategic decisions via deep reinforcement learning (deep RL) has revolutionized various fields, including computer games and robotic control, but they have not yet impacted safety-critical domains such as power grid control, medical treatment, and autonomous driving and far from real-world deployment. This research investigates scalable model-based RL approaches for explainable and trusted AI to develop explainable AI learning frameworks that can be applied to these safety-critical domains.
“AI technologies are becoming more and more capable every day and are on the verge of revolutionizing many fields and industries,” said Wright. “However, AI models are prone to mistakes, and their reasoning can be very opaque, leading to a [reasonable] lack of trust. This effort investigates novel explainable AI approaches for Reinforcement Learning (RL) to improve trust and practicality. Our intent is to develop model-based RL algorithms that can explicitly describe why it is making its decisions, visualize or describe what it expects to happen, and provide counterfactual examples for why it chose not to make decisions.”
What: Two-dimensional Nanopore Sensors for Real-time, Single Molecule Protein Sequencing
Who: Dr. Eric Vogel, Dr. Katherine Young, Noah Baughman
Units: School of Materials Science and Engineering; Cybersecurity, Information Protection, and Hardware Evaluation Research Laboratory (CIPHER)
Why It Matters: There is a significant need to develop rapid protein sequencing technologies that can be used by the warfighter in the field to identify the impact of biological warfare agents or to provide physiological monitoring to enhance soldier performance. A technology to rapidly sequence the primary and secondary structure of proteins at the single-molecule level in real-time does not currently exist. The objective of this work is to develop a rapid protein sequencing prototype technology based on two-dimensional (e.g., graphene, MoS2) nanopore sensors that can be used by the warfighter in the field and enable future research programs which apply this prototype to perform full protein sequencing.
“There is a significant need to develop rapid protein sequencing technologies that can be used to identify the impact of biological warfare agents or to provide physiological monitoring to enhance human performance,” said Vogel and Young. “This fellowship will support the fundamental research necessary to develop nanopore electrochemical sensors based on two-dimensional materials to rapidly sequence the primary and secondary structure of proteins at the single-molecule level in real-time.”
What: Generating Geopolitics: AI, Disinformation, and the Future of National Security
Who: Dr. Jon Lindsay, Mr. Nicholas Nelson, Dennis Murphy
Units: School of Cybersecurity and Privacy, Sam Nunn School of International Affairs, and School of Public Policy; Electronics, Optics, Systems Directorate (EOSD)
Why It Matters: The use of Artificial Intelligence/Machine Learning (AI/ML) in national security has the potential to enhance our ability to protect national interests greatly. However, there are also potential challenges and risks associated with this technology, such as the potential for bias or misuse. This research will engage in a multidisciplinary study that will bridge the gap between disparate research fields and reintroduce relevant security-related concepts from the social sciences. This will result in the generation of scientifically-grounded potential use cases for the technology in the support and protection of national interests.
“As AI/ML capabilities and use cases continue to evolve, it is critical for defense and national security actors to better innovate, scale, deploy, and integrate AI and autonomy-based technologies to form agile, system-wide solutions,” Nelson and Lindsay said.
What: Unmasking the "Status dilemma/competition" of the triad powers (Russia, China, and United States) in offensive-defensive behavior
Who: Dr. Adam Stulberg, Dr. Theresa Kessler, Megan Litz
Units: Sam Nunn School of International Affairs; Advanced Concepts Laboratory (ACL)
Why it matters: Unveiling the misperceptions of offensive and defensive signaling is needed in a time when offensive and defensive capabilities are becoming ever more difficult to decipher as technology is evolving. The goal of this research is to shed light on how misinterpreting states’ status can lead to international conflict and expand the initial scholarship that is starting to gain traction within the political science and security studies communities. Understanding and attempting to codify intention would be of great interest to U.S. strategists and tactical planners and aid in answering vital questions of National Security regarding the status of triad powers. Information of this nature will benefit U.S. leadership, departments, and inter-agencies that navigate relations with Russia and China.
“This fellowship will support the codification of offensive and defensive signals between Russian, Chinese, and American powers using an open-source literature repository,” said Kessler. “This will help unveil misperceptions and decipher intention.”
Writers: Georgia Parmelee, Tess Malone (Georgia Tech Research); Charles Domercant, Anna Akins (GTRI)
Georgia Tech Research Institute
The Georgia Tech Research Institute (GTRI) is the nonprofit, applied research division of the Georgia Institute of Technology (Georgia Tech). Founded in 1934 as the Engineering Experiment Station, GTRI has grown to more than 2,900 employees, supporting eight laboratories in over 20 locations around the country and performing more than $800 million of problem-solving research annually for government and industry. GTRI's renowned researchers combine science, engineering, economics, policy, and technical expertise to solve complex problems for the U.S. federal government, state, and industry.