Under the theme “A materially better future for everyone” the Acceleration Consortium hosted the Accelerate Conference 2023 in Toronto from 22nd to 25th of August. For me it was the first chance to meet people from the field of machine learning based material design in person after reading many papers over the last months.
The conference started with very interesting workshops on Bayesian optimization and best software practice in machine learning. Over the next two days, I attended many great lectures and panels in topics from large language models and their application in sciences to material development in self-driven labs. Remarkable were the number of industrial lecturers and panelists, which showcased the development of artificial intelligence and machine learning from a commercial perspective.
For me among the highlights were the very vivid poster sessions, where I could discuss about machine learning in chemical design with many researchers and gained valuable ideas and insights for our project. On the last day, I participated in the workshop on AI/machine learning in green chemistry hosted by P2 sciences. The workshop brought together a very diverse group of participants, including representatives from start-ups, large cooperations, policymakers and researchers. P2 Sciences facilitated discussions on the challenges and opportunities of applying machine learning and self-driving labs in the materials industry. One significant opportunity highlighted was the potential of machine learning-based material design to develop new materials sustainably, by incorporating considerations like biocompatibility, toxicity, and bioaccumulation at the design stage.
Overall, the conference was a great experience. Thank you to the Acceleration Consortium for organizing a very smooth and interesting conference and thank you to the Stockholm University Center for Sustainable and Circular Systems (SUCCeSS) for funding my participation.
