In the first week of the fall semester in 2007, Marco Carmosino dragged himself to a math class required for all computer science majors at the University of Massachusetts, Amherst. Carmosino, a sophomore, was considering dropping out of college to …
Imagine you visit a maze with some friends. You emerge from the exit shortly after going in, and wait around for hours before your friends emerge. Naturally, they ask about the path you took — surely you can retrace your …
Since the very first days of computer science — a field known for its methodical approach to problem-solving — randomness has played an important role. The first program to run on the world’s first general-purpose electronic computer used randomness to …
Bob Metcalfe has always been a believer in the power of networking. In the 1980s and 1990s he helped popularize the idea that a network’s value grows rapidly with the number of users, a precept now known as Metcalfe’s law. …
Machine learning is having a moment. Yet even while image generators like DALL·E 2 and language models like ChatGPT grab headlines, experts still don’t understand why they work so well. That makes it hard to understand how they might be …
For Shang-Hua Teng, theoretical computer science has never been purely theoretical. Now 58, Teng is a professor of computer science at the University of Southern California and a two-time winner of the Gödel Prize, an annual award recognizing groundbreaking theoretical …
In algorithms, as in life, negativity can be a drag. Consider the problem of finding the shortest path between two points on a graph — a network of nodes connected by links, or edges. Often, these edges aren’t interchangeable: A …
In what specific cases do quantum computers surpass their classical counterparts? That’s a hard question to answer, in part because today’s quantum computers are finicky things, plagued with errors that can pile up and spoil their calculations. By one measure, …