collaborators

8 papers

cs.CR2026

Anywhere, Any-Stymie: Remote Activation of Trojan Malware on LiDAR with Modulated Signals

R. Spencer Hallyburton, Miroslav Pajic

LiDAR sensors are widely deployed in autonomous systems for 3D perception and safety-critical decision-making. We identify a previously unexplored attack surface in which dormant m…

eess.IV2026

Scaling Datasets for Multi-Sensor, Multi-Agent, and Multi-Domain Learning in Autonomous Systems

R. Spencer Hallyburton, David Hunt, Miroslav Pajic

Existing datasets cannot support large-scale learning in multi-agent, multi-sensor, or multi-domain autonomy, where diversity and coordination are essential. We present a modular d…

math-ph2025

Shell energies derived from three-dimensional isotropic strain-gradient elasticity

C. Balitactac, Y. Canzani, R. S. Hallyburton +2

We derive a class of two-dimensional shell energies for thin elastic bodies exhibiting small-length scale effects modeled via strain-gradient elasticity. Building on the final auth…

eess.SY2025

Trusted Data Fusion, Multi-Agent Autonomy, Autonomous Vehicles

R. Spencer Hallyburton, Miroslav Pajic

Multi-agent collaboration enhances situational awareness in intelligence, surveillance, and reconnaissance (ISR) missions. Ad hoc networks of unmanned aerial vehicles (UAVs) allow…

cs.AI2025

Assured Autonomy with Neuro-Symbolic Perception

R. Spencer Hallyburton, Miroslav Pajic

Many state-of-the-art AI models deployed in cyber-physical systems (CPS), while highly accurate, are simply pattern-matchers.~With limited security guarantees, there are concerns f…

cs.CR2025

What Would Trojans Do? Exploiting Partial-Information Vulnerabilities in Autonomous Vehicle Sensing

R. Spencer Hallyburton, Qingzhao Zhang, Z. Morley Mao +2

Safety-critical sensors in autonomous vehicles (AVs) form an essential part of the vehicle's trusted computing base (TCB), yet they are highly susceptible to attacks. Alarmingly, T…