Duke’s Computer Science Ph.D. propels researchers to the bleeding edge of algorithms, trustworthy AI, and planet-scale systems. Doctoral cohorts harden post-quantum crypto, design carbon-aware schedulers for exascale clusters, and audit large-language-model bias with causal graphs. A unique ‘User & Society’ practicum embeds every fellow with NGOs or city labs, ensuring code translates into equitable impact. Entrepreneurship sprints and policy fellowships round out a program that sends graduates to top faculty posts, Fortune-50 research labs, and mission-driven start-ups.
Zero-knowledge rollups for privacy-preserving elections
Graph neural network predicting protein–protein interactions
Carbon-aware Kubernetes autoscaler for green cloud computing
Explainable reinforcement learning for wildfire-drone swarms
Quantum-resistant signature scheme for IoT firmware
Differential-privacy toolkit for city open-data portals
Self-healing supply-chain-attack detector for CI/CD pipelines
Deep RL agents simulating resilience in micro-grid markets
Edge-optimized federated learning for wildlife-camera traps
Natural-language refactoring assistant for legacy COBOL code
Augmented-reality IDE overlaying live code performance metrics
Blockchain governance model for open-source contribution rewards
Large-language-model alignment via human value learning
VR classroom teaching NP-completeness with interactive puzzles
Cyber-range scenario generator for autonomous-vehicle security
Policy brief on algorithmic-audit standards for federal agencies
Citizen-science platform benchmarking broadband latencies
Invent algorithms and systems that serve society through Duke CS.
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