Presents a machine learning-based framework for identifying breakthrough technologies early by using link prediction on science-driven innovation networks — detecting weak signals of technological…
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Applies machine learning to discover new catalyst compositions for methane dry reforming — a process that converts CO₂ and methane into synthesis gas, offering a route to reduce greenhouse gas…
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Reviews how LLMs are being applied to computational social science — covering their use in modeling social phenomena, scaling research, and the key challenges of data bias, privacy, and integration…
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Surveys the state-of-the-art in AI/ML for cybersecurity — covering adversarial AI, automated threat intelligence, AI-driven security orchestration, and future paradigms for how AI will reshape…
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Surveys post-quantum cryptographic approaches for securing IoT devices — covering lattice-based, code-based, and hash-based schemes that can resist quantum attacks while remaining practical for…
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Reviews the integration of AI with quantum computing — spanning quantum-enhanced classical ML, native quantum algorithms, and hybrid approaches with applications in optimization, drug discovery, and…
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