AI-Driven Research Workflows: "Information Rich Strategies for Chemical Synthesis" - Tim Cernak

“Information Rich Strategies for Chemical Synthesis”
Presentation abstract: Advancing the synthesis of small molecules is critical to the advent of new medicines, materials, and agrochemicals. Our lab has been exploring strategies in chemical synthesis - both in reaction method development and total synthesis - that leverage modern data science techniques and robotics. This presentation will share some recent results using informatics to target novel amine-acid coupling reactions, and algorithms to streamline multistep synthesis. Chemical synthesis enabled by data science techniques and automation will be a consistent theme of the research, aiming towards a future state where medicines are invented at a rapid pace.
Tim Cernak, Assistant Professor of Medicinal Chemistry and Chemistry, University of Michigan
About this event: Significant advancements in Artificial Intelligence (AI), including Generative AI, and the hardware and software research environment are enabling researchers to develop AI-driven research workflows (ARWs): AI and Generative AI for hypothesis generation, experimental design and monitoring, as well as data acquisition, processing and analytics. Such ARWs will not only significantly accelerate research, but also enable new research possibilities.
This mini-symposium featured a keynote by Ian Foster (Argonne National Lab) and presentations from University of Michigan faculty members showcasing how they have developed and embedded AI-driven components in their research workflows.
For more information about the series and speakers, please visit the event page at: midas.umich.edu/ai-driven-res...
- Sign up for the MIDAS newsletter: myumi.ch/rrxW3
- Twitter: @um_midas
- LinkedIn: / michigan-institute-for...
#datascience #artificialintelligence #research #ai #generativeai