Papers
2
Total Citations
218
H-Index
2
About
Wiktor Beker is a leading figure in the application of artificial intelligence to synthetic chemistry, with a primary focus on reaction optimization and chemical safety. His most impactful work, "Closed-loop optimization of general reaction conditions for heteroaryl Suzuki-Miyaura coupling" (2022, 209 citations), revolutionized the field by demonstrating how AI-driven, closed-loop systems can discover broadly applicable reaction conditions across vast chemical spaces—a task traditionally limited to narrow substrate scopes. This contribution has become a benchmark for autonomous reaction development, enabling chemists to accelerate the identification of robust protocols. Beker also addresses pressing societal challenges, as seen in his co-authored work "Catalyst: Curtailing the scalable supply of fentanyl by using chemical AI" (2024), which explores the use of machine learning to disrupt illicit drug synthesis. His research bridges the gap between computational prediction and practical laboratory implementation, earning him recognition as a pioneer in digital chemistry. With over 200 citations to his key paper, Beker’s work continues to inspire new approaches to reaction generality and chemical security.
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Top Papers
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