Conducting biological experiments can be time-consuming and expensive. Additionally, covering the range of experimental conditions, in today’s era of big and multidimensional data, poses even more challenges. With the continuous development of Machine Learning (ML) in biological sciences, ML based biological experimental design is revolutionizing the field of biology, making experiments more efficient and ultimate scientific discovery more successful. Immunai’s online symposium brings together top researchers from MIT to share their innovations in the field of ML and biological experimental design.

00:00:00 / Intro by Caroline Uhler
00:03:20 / Optimal Design of Interventions by Caroline Uhler
00:27:30 / Q&A with Caroline Uhler
00:29:45 / Personalized predictions from population data: A case study on Alzheimer's disease by Devavrat Shah
00:51:15 / Q&A with Devevrat Shah
00:55:05 / Rethinking ML-based Molecular Modells by Regina Barzilay
01:23:10 / Q&A with Regina Barzilay