Papers
5
Total Citations
224
H-Index
4
About
David A. Winkler is a computational chemist and materials scientist whose research sits at the intersection of machine learning, drug discovery, and advanced materials design. He has made substantial contributions to the application of artificial intelligence in nanosafety, earning significant recognition with his 2020 paper on AI and machine learning in nanosafety accumulating 162 citations — a landmark work demonstrating how modern ML methods can transform the synthesis, characterization, and risk assessment of nanomaterials. Winkler has also advanced the field of next-generation solar energy, contributing to machine learning-enhanced fabrication of quasi-2D Ruddlesden-Popper perovskite solar cells, work that has rapidly attracted 43 citations since its 2023 publication. His broader research philosophy, articulated in his work on biomimetic molecular design tools, reflects a deep commitment to adaptive, evolution-inspired computational strategies for exploring vast chemical spaces. A recipient of the prestigious Adrien Albert Award, Winkler has championed innovative approaches to mining chemical space for new drugs and biomedical therapies. His career exemplifies the power of integrating computational intelligence with experimental science to address challenges in medicine, materials, and sustainability.
Research Focus
Key Achievements
Top Papers
- 1Role of Artificial Intelligence and Machine Learning in Nanosafety162 citations · 2020
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- 3Biomimetic molecular design tools that learn, evolve, and adapt12 citations · 2017
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