Amber Spinks

I am a PhD-trained chemist with over 15 years of experience in academic research, industrial R&D, and AI model evaluation. My expertise spans analytical, physical, and computational chemistry, with a specific focus on evaluating, annotating, and curating high-quality chemistry datasets for generative AI systems. I'm adept at transforming complex scientific concepts into clear evaluation frameworks, structured tasks, and practical training materials, and I frequently collaborate with data scientists, machine-learning engineers, and subject-matter experts. My core strengths include a deep understanding of theoretical and practical chemistry, covering DFT, spectroscopy, kinetics, and thermodynamics. I have extensive experience in reviewing AI-generated scientific content for accuracy and experimental feasibility, backed by peer-reviewed publications and patents. I'm also skilled in technical writing, assessment creation, and providing actionable feedback, ensuring clear communication and robust evaluation criteria.