
About
Chris Alvin is an Associate Professor at Furman University with expertise in artificial intelligence applications, particularly in drug discovery and educational technology. His research spans computational biology, algorithm design for geometric problems, and AI-driven educational tools. Alvin has published extensively on machine learning approaches to pharmaceutical challenges including COVID-19 therapeutics.
Current projects develop knowledge graph frameworks for drug-target affinity prediction and lattice-based systems for geometry education. His work appears in computational chemistry, AI, and computer science education venues. Alvin integrates industry experience from software engineering roles into his academic research and teaching methodology.
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