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We’re on the lookout for a dynamic Nuclear Engineer to join our forward-thinking team, someone who is not only passionate about nuclear engineering but also has a solid grounding in Bayesian inference, ideally with particle filtering. If you’re someone who dabbles in machine learning and are excited about applying these skills in the nuclear engineering … Read more

We are proud to announce that GTC has has successfully secured the GSA Multiple Award Schedule (MAS) government contract, a significant recognition of our commitment to excellence in federal procurement and our ability to meet the comprehensive requirements of federal agencies. Contract Details: The GSA MAS contract is a long-term agreement with the U.S. federal … Read more

We’re thrilled to announce that GTC will be participating in the upcoming Cyber-Physical Systems Symposium 2023, where we’ll be presenting a talk on “Unsupervised and Adaptive Cyberphysical Anomaly Detection in Sensored Systems.” This event brings together researchers, entrepreneurs, and industry leaders to discuss the latest advancements in Cyber-Physical Systems (CPS) and Internet of Things (IoT), … Read more

GTC researchers and our collaborators at the University of Colorado Denver and NASA JPL, published the paper “A Reusable Framework for Fault Detection and Isolation in Small Satellites,” at this year’s Small Satellite Conference in Logan, UT. GTC’s Jubilee Prasad Rao presented the poster at the conference on August 8th. This paper is an outcome of NASA … Read more

As part of our recent work developing IoT sensor suites to monitor woody biomass burial sites, GTC would like to share our GitHub repository for part of the project! In this repo, we’ll show you how to read data from an industrial soil moisture and temperature sensor from Seeed Studio, including required hardware, Python scripts, … Read more

We are proud to announce GTC with its collaborators at Georgia Tech have written a chapter for the upcoming Handbook of Smart Energy Systems. The chapter, titled “Smart Buildings in the IoT Era – Necessity, Challenges, and Opportunities,” which addresses how IoT-enabled smart buildings can help mitigate some of our most pressing urbanization and climate … Read more

We’re excited to share the results of our latest research project in collaboration with the U.S. Navy on attrition risk and aircraft suitability prediction in pilot training using machine learning. In this study, we developed models that accurately predict attrition risk and recommend suitable training aircraft types for student aviators, potentially saving millions of dollars … Read more

Cyberphysical systems refer to systems that have both software and hardware components, such as simple robots, unmanned aerial vehicles, and satellites. As they operate, these systems may experience faults or anomalies due to hardware degradation, erroneous software, or unexpected interactions with their environment. Detecting and identifying these issues is challenging, and it is difficult to … Read more

Phase Association via MCMC and Deep Learning.” While recent novel data-driven association techniques have shown promise for seismic phase association of local and regional earthquakes, their applicability on the global scale is still unclear.  Dr. Williams et al. attempt to solve this by leveraging two deep learning models and a Markov Chain Monte Carlo (MCMC) … Read more

GTC is excited to share an update on our technical support of Lets’s Own This! Foundation’s woody biomass burial (WBB) pilot study. WBB is a form of carbon sequestration,  and Let’s Own This! will be burying 100,000 tons of wood in upcoming deployments. During the pilot study, we are monitoring the buried wood to characterize … Read more