
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.
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Addressing the current gap in IoT mode definitions by introducing and analyzing passive mode designations for smart devices
Heating, Ventilation, and Air Conditioning (HVAC) systems account for 40% to 50% of energy usage in commercial buildings, so controlling them while preserving occupants' comfort matters. State-of-the-art solutions use pervasive systems with sensors or smart devices to gauge individual thermal sensations, but assessing those methods is hard: real-world experiments are expensive, limited in access, and often overlook occupant and regional diversity.
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.
Best Artifact Award
PerCom 2025
For Your Smart Home Exchanged 3M Messages: Defining and Analyzing Smart Device Passive Mode.
Mark Weiser Best Paper Award
PerCom 2022
For SmartSPEC: Customizable Smart Space Datasets via Event-Driven Simulations.
2nd place, Sandpit Challenge on Digital Trust
INCS-CoE 2022
With Royal Holloway University of London and Keio University Tokyo.