With an approval from the Georgia Tech IRB, we are in the process of building and transcribing a corpus of recorded audio interviews with Georgia Tech students. (So far, we have recorded and transcribed 25 interviews, but we aim for over 100 to get enough data for each of the different demographic and political affiliations that interest us.) We use phonetic software to measure the...
This project brings together students of diverse backgrounds and disciplines to tell the story of Atlanta as a global city, and to increase access to global citizenship at Georgia Tech and nationally. We want to document and connect with the individuals and communities that are transforming Atlanta into a global metropolis, such as heritage and immigrant communities, foreign-born residents...
To develop 2-D to 2-D tunneling structures to enable for smaller, faster, more capable microelectronic devices applied to a broad range of applications such as energy, RF, and sensing.
The main goal of the ACT (Autonomous and Connected Transportation) Lab is to understand interactions between drivers/travelers, emerging vehicular technologies related to connectivity and autonomy, and novel infrastructure designs using a driving simulator environment, analytical modeling, and field test tracks. Using the collected data, we seek to develop analytical models and perform data...
Using artificial intelligence (AI)-based approaches (especially manifold learning) for understanding the delicate rules of nature and utilizing them for forming innovative software- and hardware-based tools for addressing the major challenges in a wide range of disciplines.
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To develop a system that will be able to drive like an expert human driver. In order to achieve this, we will initially monitor the driving styles of several drivers using a high-fidelity driving simulator. Based on the measurements, we will be able to classify drivers according to their skill using graphical inference models. We will then develop suitable models for drivers’ actions and...
For students to learn the theory and gain the skills necessary to fabricate next-generation batteries for EVs, spacecraft, and Smart Cities infrastructure.
Future wireless communication devices will need to dynamically learn their environment and opportunistically exploit spectrum. The goal of this project is to integrate machine learning algorithms into communication architectures to achieve the agility required for the task. The team will participate to the DARPA Spectrum Collaboration Challenge (SC2) and test its solutions against other...
The Laboratory for Intelligent Decision and Autonomous Robots (LIDAR) at Georgia Tech focus on planning, control, and decision-making algorithms of highly dynamic, under-actuated, and human-cooperative robots in complex environments. The VIP Team will explore the challenging research topics in mechanical design, mechatronics, control algorithm design, and perception of dynamic legged...
Aquabots will explore new research in maritime robotics including navigation of underwater and surface vehicles, mapping and exploration underwater, and other challenging maritime robotic technologies.
This project, a collaboration between Mark Leibert (LMC) and Betty Whitaker (GTRI), brings together histories and concepts of visual culture and image making with explorations of technology and artificial intelligence. We are an artist and AI researcher exploring approaches to applying machine learning to create artistic images. Our team is analyzing the application of machine learning to...
Enable the creation of augmented-reality applications and experiences using a wide range of delivery platforms and AR technologies. Current projects use Argon, an augmented reality software suite developed at Georgia Tech that is both a Javascript/HTML5 framework and a set of browsers and tools.
To develop a framework that fundamentally alters the development of algorithms. We desire to create an automated method that starts with the best human algorithms and then dispassionately develops hybrid algorithms that outperform existing methods. Next, we prove that these algorithms can also be studied by humans for inspiration in development of new algorithm and optimization methods.
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GOALS: To collect and analyze big data about bee-flower interactions on the Georgia Tech campus and beyond to inform property owners and policy makers about how land use can support pollinator health.
Leverage advances in machine learning and data analytics to enable faster and more accurate calculations of chemical properties using quantum-mechanical techniques such as density functional theory (DFT).
Model crack propagation, crack networks, particle crushing, and healing in salt rock; predict soil and rock THCM behavior during heat and fluid injection and extraction; design new geomaterials to optimize the fuel cycle; and recommend strategies for resource and waste management.
The Bits of Good VIP team is closely linked to the Bits of Good student organization. In order to participate in the VIP, you will need to be a member of the BoG student organization, as this is where teams, roles, and training will take place. As a member of VIP, you will have some additional responsibilities to support the assignment of individual grades for the VIP. These may include:...
Goals: To build a suite of mobile applications for iOS and Android devices that will be used to administer and collect data from individuals who have suffered brain traumas with lingering effects (e.g., stroke leading to Aphasia, Alzheimer’s, etc.).
