Arup K Chakraborty – MIT
Wednesday, September 9, 2026
Zoom opens: 10:30AM EDT
Seminar begins: 10:45AM EDT
How the Immune System Learns
The humoral immune system, comprised of B cells and their antibody and memory B cell products, plays an important role in protecting us from infection. This system is also a learning algorithm. Antibodies and memory B cells are produced by a Darwinian evolutionary process. This is a non-equilibrium stochastic dynamic process that allows the immune system to learn about a new antigen (pathogen or vaccine component). I will first describe results obtained from statistical physics-based models of these processes and complementary data from animals and humans. These studies show that the human immune system has a remarkable ability to learn to develop responses that can respond to previously unseen variant antigens upon “training” with only a few exposures to the same antigen. The mechanism underlying this ability to generalize will be discussed. I will then discuss how exploring and exploiting analogies between how the immune system learns and how machines learn is now enabling us to address basic scientific questions that can potentially guide better strategies to cure and prevent disease. Finally, I will comment on similarities and differences between learning in the immune system and deep learning networks.