Ronald J. Williams is professor of computer science at Northeastern University, and one of the pioneers of neural networks. He co-authored a paper on the backpropagation algorithm which triggered a boom in neural network research.[1] He also made fundamental contributions to the fields of recurrent neural networks[2][3] and reinforcement learning.[4] Together with Wenxu Tong and Mary Jo Ondrechen he developed Partial Order Optimum Likelihood (POOL), a machine learning method used in the prediction of active amino acids in protein structures. POOL is a maximum likelihood method with a monotonicity constraint and is a general predictor of properties that depend monotonically on the input features.[5]