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TRUST/UFRPE investigates methods for designing, evaluating, and operating computing and AI-enabled systems so that they behave as intended and remain dependable throughout their lifecycle. Our research encompasses software and AI engineering; dependability, performance, and system modeling; operational resilience; and the optimization and deployment of AI models in resource-constrained environments.
How our research connects
How our research connects
Our research addresses trustworthiness at three complementary stages of the system lifecycle.
Research focus
Research focus
01
Build Correctly
Build Correctly
We investigate software and AI engineering practices, including quality assurance, testing, maturity models, software engineering for AI (SE4AI), and AI for software engineering (AI4SE), to reduce faults during design and development.
02
Anticipate Behavior
Anticipate Behavior
We use modeling, simulation, and experimentation to assess dependability, performance, energy, cost, and resource needs, and to guide the optimization and deployment of AI models in environments with limited resources.
03
Sustain Operation
Sustain Operation
We study software aging and operational degradation and develop monitoring, anomaly detection, and predictive maintenance techniques to strengthen operational resilience and support adaptation and recovery.
Application Contexts
Application Contexts
The group investigates these challenges across AI systems and LLM-based applications, cloud platforms, edge environments with limited computational resources, databases, industrial equipment and manufacturing systems, UAVs, IoT, robotic telesurgery, and other cyber-physical systems and critical infrastructures.
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