The DAMS (DAta Management & Semantics) Research Group at UMBC is lead by Professor Roberto Yus. We focus on semantic and privacy-aware data management in IoT environments.
Read more about our group → Interested in joining the DAMS group?
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GenAIPABench assesses the effectiveness of GenAIPAs across multiple dimensions including accuracy, relevance, and consistency, using a curated set of privacy-related questions and metrics. The benchmark aims to advance the development of AI privacy assistants by providing a standard evaluation framework.
Framework aimed at discovering, collecting, and analyzing privacy policies of smart devices using NLP and ML algorithms, to provide insights to users, policy authors, and regulators.
Our paper on a benchmark to evaluate thermal comfort provision systems on smart buildings has been accepted at PerCom 2024. More information at the PerCom 2024 website.
Co-zyBench: Using Co-Simulation and Digital Twins to Benchmark Thermal Comfort Provision in Smart Buildings
Jun Ma (Telecom SudParis, France); Dimitrije Panic (Telecom SudParis, France); Roberto Yus (University of Maryland, Baltimore County, USA); Georgios Bouloukakis (Telecom SudParis, France)
Our paper on a benchmark to evaluate thermal comfort provision systems on smart buildings has been accepted at the 1st International Workshop on Middleware for Digital Twin (Midd4DT) collocated with Middleware 2023. More information at the Midd4DT 2023 website.
DEMSA: a DT-enabled Middleware for Self-adaptive Smart Spaces
Jun Ma (Telecom SudParis, France); Georgios Bouloukakis (Telecom SudParis, France); Ajay Kattepur (Ericsson AI Research, India); Roberto Yus (University of Maryland, Baltimore County, USA); Denis Conan (Telecom SudParis, France);