We would like to introduce this year’s speakers
Prof. Herbert Mayr
The work demonstrates how widely accepted concepts of organic chemistry can be challenged by experimental evidence, questioning their general validity. Using examples such as the reactivity–selectivity principle, the Leffler–Hammond relationship, and Kornblum’s rule, it highlights their limitations and the need for a more nuanced interpretation of organic reactivity.
Department Chemie der Ludwig-Maximilians-Universität München
Butenandtstr
Prof. Holger Braunschweig
The work highlights recent advances in main-group chemistry, demonstrating that low-valent boron compounds can exhibit transition-metal-like behavior in small molecule activation. In particular, borylenes, diborenes, and diborynes are shown to bind and transform molecules such as H₂, CO, and even N₂ under mild conditions.
Institute for Inorganic Chemistry
Institute for Sustainable Chemistry & Catalysis with Boron
Prof. Wojciech Fendler
The work presents translational studies on microRNA biomarkers, illustrating the process of bridging basic research with clinical applications, including diagnostics of radiation exposure and cancer. It emphasizes the importance of integrating biological, clinical, statistical, and bioinformatic approaches, along with artificial intelligence, to develop reliable diagnostic tools.
Department of Biostatistics and Translational Medicine
Medical University of Łódź
Dr Jakub Brześkiewicz
The work introduces the concept of “deprotective functionalization”, enabling simultaneous deprotection and functionalization, thereby shortening traditional synthetic sequences. Central to this approach is the novel Nms (Nonafluoromesitylenesulfonyl) protecting group, whose unique reactivity allows direct conversion of amides into valuable nitrogen-containing compounds, supported by mechanistic studies and case examples.
Institute of Organic Chemistry, University of Vienna
The work shows how modern computational chemistry extends traditional DFT by combining improved functionals with machine learning corrections. It highlights the limitations of standard approximations and demonstrates how AI-enhanced methods can increase accuracy and enable deeper insight into molecular systems.
Department of Chemistry, Fudan University
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