The Duke MS in Computer Science propels coders into research-driven innovation. Students craft privacy-preserving federated-learning pipelines, harden quantum-safe cryptographic stacks, and benchmark exascale graph processors. Hackathons with Duke’s AI for Good Lab yield open-source tools for climate-risk analytics and language preservation. Graduates exit with refereed conference papers and venture-ready prototypes.
Zero-knowledge proof framework for carbon-credit verification
Graph neural network predicting protein-interaction pathways
Edge-optimized federated learning for wildlife camera traps
Quantum-resistant signature scheme for IoT firmware
Explainable recommender auditing bias in mental-health apps
Augmented-reality IDE overlaying code complexity metrics
Differential-privacy toolkit for open government datasets
Self-healing Kubernetes operator mitigating supply-chain attacks
Deep RL agents simulating renewable-grid stability
Open-source compiler for AI accelerators using MLIR
Cyber-range scenario generator for autonomous-vehicle security
VR platform teaching data-structures through spatial metaphors
Blockchain governance model for open-source contribution rewards
Natural-language-based code refactoring assistant
NLP pipeline translating endangered-language corpora
Master next-level computing and deploy solutions that matter through Duke CS.
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