Georgia Tech CS PhD students author state-of-the-art models at NeurIPS, crash test OS kernels in Google’s micro-datacenter, and draft policy for Senate AI hearings. Research spans machine learning robustness, post-quantum crypto, XR interfaces, and carbon-aware cloud orchestration.
LLM red-teaming framework with automated exploit synthesis
Energy-adaptive scheduler for carbon-aware Kubernetes clusters
Zero-knowledge proof compiler for post-quantum signatures
Neural rendering pipeline for real-time telepresence holography
Rust-based micro-kernel with formally verified isolation
Federated-learning privacy attack taxonomies and defenses
Graph RL optimizer for chip floor-planning placement
Human-in-the-loop explainability toolkit for medical imaging AI
Differential-privacy OLAP engine on geospatial census data
Quantum-inspired heuristic for NP-hard scheduling
Serverless stream-processing for global wildfire telemetry
Edge-AI vision stack for wildlife poaching detection
Bias mitigation in recommender systems via causal inference
WebGPU-accelerated physics sandbox for STEM education
Formal-methods-based patch generator for memory-safety bugs
Invent foundational computing that reshapes society.
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