RESEARCH
7 areas that share a single question: how does a machine earn the right to act on its own reading of the world?
AREA 01
Training and unlearning across distributed clients, with Byzantine robustness and privacy budgets that survive contact with real edge hardware.
AREA 02
V2X and MANET security: authentication protocols, digital-twin traffic environments, and defences against routing and forwarding attacks.
AREA 03
Clinical and assistive models built to be checked — ECG arrhythmia detection, breast-ultrasound diagnosis, and multi-sensor elderly-care monitoring.
AREA 04
LLM-based formative feedback and exemplar selection for school mathematics, evaluated for feasibility before deployment.
AREA 05
A Wireless Sensor Network (WSN) consists of a spatially distributed collection of dedicated, autonomous devices equipped with sensors to cooperatively monitor physical or environmental conditions. These compact nodes track data—such as temperature, pressure, motion, or acoustics—and leverage radio signals to pass their measurements through the network infrastructure to a central location, known as a base station or sink, where the data is analyzed. Because these networks typically operate in remote or hazardous environments, they rely heavily on low-power, ad-hoc wireless routing protocols and localized battery power to maintain long-term, self-healing communication without human intervention.
AREA 06
Signal-level models for sensing and interaction, from sEMG recognition to energy forecasting on constrained devices.
AREA 07
Wireless sensor networks, protocol performance under noise, and the systems work that makes distributed intelligence deployable.
FACILITIES
Hardware and compute the lab runs experiments on.
Primary autonomous ground-vehicle fleet acquired through a $500,000 DOD grant in 2023. Used for autonomous navigation, perception, localization, path planning, lane following, multi-vehicle coordination, and student research.
Controlled test environment for lane following, path planning, localization, navigation, multi-vehicle coordination, and autonomous-system demonstrations.
Supports programming, simulation, data collection, QCar development, and research workflows using Python, ROS, MATLAB, and related autonomous-systems software.
Supports driving-simulator experiments, human-in-the-loop research, manual driving-data collection, driver-assistance demonstrations, and control-interface development.
SUPPORT
Sponsored projects and the partners the lab works with.
No awards recorded yet.
Awards support students, hardware and field deployment. Each project is listed with its sponsor and period; joint work with the partners below runs across several of them.
COLLABORATORS
Institutions the lab has published with. The number on each tile is joint papers.
Partners are added from the console — upload their logo and it appears here.