Christopher Beck is a Ph.D. student at Princeton University. He graduated from the California Institute of Technology with a Bachelor of Science with honors in Computer Science and Mathematics. Beck’s work seeks to establish the limits of how efficiently we can solve computational problems. One of his papers studies a popular class of algorithms known as SAT solvers and shows that if their memory is restricted, then they can require exponential running time. Another result concerns how well we can approximately sample from certain distributions when our computation must be small depth, that is, highly parallelizable. Beck and his co-authors showed that even exponentially large bounded depth circuits cannot sample with even exponentially small success from a certain simple distribution.