I am pursuing a BS in Cybersecurity Analytics & Operations at Penn State World Campus, following postgraduate research at INRTU on neural networks for industrial control systems. My research looks at behavioral drift under poisoning attacks — how systems degrade under repeated adversarial pressure over many turns or long uptimes, across LLM agent pipelines.
Highlights
- Published RIPA, the first large-sample (n≥100) study of sensory-vector prompt injection on LLM-controlled ROS 2 robots, spanning visual, audio, and LiDAR injection channels across five models.
- Published Dynamic Separator Generation with Prof. Peng Liu, closing the pool-reuse blast radius in Polymorphic Prompt Assembling.
- Working on SOC-Bench with Prof. Peng Liu, synthesizing co-sourced network, host-log, and alert telemetry to train and evaluate blue-team AI agents.
Papers
Projects
Synthetic SOC log-synthesis research with Prof. Peng Liu, producing co-sourced PCAP, host-log, and alert datasets to train and evaluate blue-team AI agents.
A project for using neural networks in automatizaion of gold desorption process.
Research focus
Most defenses evaluate a single injected prompt against a single response. In practice, agents run for many turns and cyber-physical systems run for long uptimes — a payload that fails once doesn't disappear, it sits in context or in a sensor stream and compounds. That accumulation is the throughline connecting RIPA's work on LLM-controlled robots to using AI in SCADA systems. Separately, with Prof. Peng Liu I work on SOC-Bench, synthesizing realistic co-sourced telemetry — PCAP, host logs, and alerts — to train and evaluate blue-team AI agents.