Speaker
Description
Abstract: In this talk, we will discuss an intelligent agent system that integrates multiple large language models for autonomous design, planning, and execution of scientific experiments. We will demonstrate the Agent's scientific research abilities using several examples, with the most complex one involving the successful execution of catalyzed cross-coupling reactions. Lastly, we address the safety concerns related to such systems and suggest measures to prevent their potential misuse.
Bio: Daniil Boiko obtained his MSc in organic chemistry from Lomonosov Moscow State University, researching machine learning applications in chemistry, including electron microscopy, mass spectrometry, and reaction discovery. He also worked at VK, developing machine learning models for web search. Now, he's pursuing a PhD in Chemical Engineering at Carnegie Mellon University, focusing on molecular machine learning, biocatalyst discovery recommender systems, and language model applications in natural sciences.
